WO2025043093A1 - Extended beamspace in massive mimo radar - Google Patents

Abstract

Provided are methods for an extended beamspace in massive MIMO radar, which can include determining beamformed phase centers for non-uniform groups of transmit elements corresponding to a center of gravity of transmit elements in respective groups. The method may also include activating respective groups of transmit elements to output coherent signals, extracting received signals reflected from an environment to form an extended beamspace, wherein the received signals are obtained by receive elements. Systems and computer program products are also provided.

Description

Extended Beamspace in Massive MIMO Radar

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present application claims priority to US Patent Application No 63/534, 182, filed on August 23, 2023, entitled “Beamspace Massive MIMO Radar in Automotive Application,” which is herein incorporated by reference in its entirety.

BACKGROUND

[0002] Radar is used to determine range, velocity, elevation, or azimuth of objects in an environment. Radar systems typically transmit a radio frequency (RF) signal and capture the reflection of the radio signal from objects in the environment.

BRIEF DESCRIPTION OF THE FIGURES

[0003] FIG. 1 is an example environment in which a vehicle including one or more components of an autonomous system can be implemented;

[0004] FIG. 2 is a diagram of one or more systems of a vehicle including an autonomous system;

[0005] FIG. 3 is a diagram of components of one or more devices and/or one or more systems of FIGS. 1 and 2;

[0006] FIG. 4 is a diagram of certain components of an autonomous system;

[0007] FIG. 5 is a diagram of an implementation of a process for extended beamspace in massive MIMO radar.

[0008] FIG. 6 shows a physical array of a MIMO radar system.

[0009] FIG. 7A shows limited beamforming applied to a physical array.

[0010] FIG. 7B shows beamformed phase centers from limited beamforming with receiver elements.

[0011] FIG. 7C shows an array factor of the elevation array.

[0012] FIG. 8A shows an array geometry of beamformed phase centers from extended beamforming with receiver elements.

[0013] FIG. 8B shows an extended beamspace based on phase centers of FIG. 8A. [0014] FIG. 8C shows an array factor of the elevation array.

[0015] FIG. 9 is a flowchart of a process for extended beamspace in massive MIMO radar.

DETAILED DESCRIPTION

[0016] In the following description numerous specific details are set forth in order to provide a thorough understanding of the present disclosure for the purposes of explanation. It will be apparent, however, that the embodiments described by the present disclosure can be practiced without these specific details. In some instances, well-known structures and devices are illustrated in block diagram form in order to avoid unnecessarily obscuring aspects of the present disclosure.

[0017] Specific arrangements or orderings of schematic elements, such as those representing systems, devices, modules, instruction blocks, data elements, and/or the like are illustrated in the drawings for ease of description. However, it will be understood by those skilled in the art that the specific ordering or arrangement of the schematic elements in the drawings is not meant to imply that a particular order or sequence of processing, or separation of processes, is required unless explicitly described as such. Further, the inclusion of a schematic element in a drawing is not meant to imply that such element is required in all embodiments or that the features represented by such element may not be included in or combined with other elements in some embodiments unless explicitly described as such.

[0018] Further, where connecting elements such as solid or dashed lines or arrows are used in the drawings to illustrate a connection, relationship, or association between or among two or more other schematic elements, the absence of any such connecting elements is not meant to imply that no connection, relationship, or association can exist. In other words, some connections, relationships, or associations between elements are not illustrated in the drawings so as not to obscure the disclosure. In addition, for ease of illustration, a single connecting element can be used to represent multiple connections, relationships or associations between elements. For example, where a connecting element represents communication of signals, data, or instructions (e.g., “software instructions”), it should be understood by those skilled in the art that such element can represent one or multiple signal paths (e.g., a bus), as may be needed, to affect the communication.

[0019] Although the terms first, second, third, and/or the like are used to describe various elements, these elements should not be limited by these terms. The terms first, second, third, and/or the like are used only to distinguish one element from another. For example, a first contact could be termed a second contact and, similarly, a second contact could be termed a first contact without departing from the scope of the described embodiments. The first contact and the second contact are both contacts, but they are not the same contact.

[0020] The terminology used in the description of the various described embodiments herein is included for the purpose of describing particular embodiments only and is not intended to be limiting. As used in the description of the various described embodiments and the appended claims, the singular forms “a,” “an” and “the” are intended to include the plural forms as well and can be used interchangeably with “one or more” or “at least one,” unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will be further understood that the terms “includes,” “including,” “comprises,” and/or “comprising,” when used in this description specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

[0021] As used herein, the terms “communication” and “communicate” refer to at least one of the reception, receipt, transmission, transfer, provision, and/or the like of information (or information represented by, for example, data, signals, messages, instructions, commands, and/or the like). For one unit (e.g., a device, a system, a component of a device or system, combinations thereof, and/or the like) to be in communication with another unit means that the one unit is able to directly or indirectly receive information from and/or send (e.g., transmit) information to the other unit. This may refer to a direct or indirect connection that is wired and/or wireless in nature. Additionally, two units may be in communication with each other even though the information transmitted may be modified, processed, relayed, and/or routed between the first and second unit. For example, a first unit may be in communication with a second unit even though the first unit passively receives information and does not actively transmit information to the second unit. As another example, a first unit may be in communication with a second unit if at least one intermediary unit (e.g., a third unit located between the first unit and the second unit) processes information received from the first unit and transmits the processed information to the second unit. In some embodiments, a message may refer to a network packet (e.g., a data packet and/or the like) that includes data.

[0022] As used herein, the term “if” is, optionally, construed to mean “when”, “upon”, “in response to determining,” “in response to detecting,” and/or the like, depending on the context. Similarly, the phrase “if it is determined” or “if [a stated condition or event] is detected” is, optionally, construed to mean “upon determining,” “in response to determining,” “upon detecting [the stated condition or event],” “in response to detecting [the stated condition or event],” and/or the like, depending on the context. Also, as used herein, the terms “has”, “have”, “having”, or the like are intended to be open-ended terms. Further, the phrase “based on” is intended to mean “based at least partially on” unless explicitly stated otherwise.

[0023] Reference will now be made in detail to embodiments, examples of which are illustrated in the accompanying drawings. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the various described embodiments. However, it will be apparent to one of ordinary skill in the art that the various described embodiments can be practiced without these specific details. In other instances, well-known methods, procedures, components, circuits, and networks have not been described in detail so as not to unnecessarily obscure aspects of the embodiments.

[0024] General Overview

[0025] In some aspects and/or embodiments, systems, methods, and computer program products described herein include and/or implement an extended beamspace in massive multiple-input multiple-output (MIMO) radar. In some embodiments, a first set of transmit elements and a second set of transmit elements configured to be selectively coupled in non-uniform groups. Receive elements are configured in a physical array with the first set of transmit elements and the second set of transmit elements, wherein the physical array comprises rows and columns comprising the first set of transmit elements, the second set of transmit elements, and receive elements. An extended beamspace is created from beamformed phase centers determined for the non-uniform groups, wherein a respective phase center of each non-uniform group is paired with the receive elements. [0026] By virtue of the implementation of systems, methods, and computer program products described herein, techniques for an extended beamspace in massive MIMO radar enables an expanded virtual array without increasing the number of physical transmit and receive elements in a radar system. As automotive radar systems are especially sensitive to cost factors, it is desirable to hold the number of transmit-antenna outputs and receive-antenna inputs to a minimum. Further, the extended beamspace improves a dynamic range, degree of freedom, and angular ambiguity associated with the physical elements of the radar system.

[0027] Referring now to FIG. 1 , illustrated is example environment 100 in which vehicles that include autonomous systems, as well as vehicles that do not, are operated. As illustrated, environment 100 includes vehicles 102a-102n, objects 104a-104n, routes 106a-106n, area 108, vehicle-to-infrastructure (V2I) device 110, network 112, remote autonomous vehicle (AV) system 114, fleet management system 116, and V2I system 118. Vehicles 102a-102n, vehicle-to-infrastructure (V2I) device 110, network 112, autonomous vehicle (AV) system 114, fleet management system 116, and V2I system 118 interconnect (e.g., establish a connection to communicate and/or the like) via wired connections, wireless connections, or a combination of wired or wireless connections. In some embodiments, objects 104a-104n interconnect with at least one of vehicles 102a- 102n, vehicle-to-infrastructure (V2I) device 110, network 112, autonomous vehicle (AV) system 114, fleet management system 116, and V2I system 118 via wired connections, wireless connections, or a combination of wired or wireless connections.

[0028] Vehicles 102a-102n (referred to individually as vehicle 102 and collectively as vehicles 102) include at least one device configured to transport goods and/or people. In some embodiments, vehicles 102 are configured to be in communication with V2I device 110, remote AV system 114, fleet management system 116, and/or V2I system 118 via network 112. In some embodiments, vehicles 102 include cars, buses, trucks, trains, and/or the like. In some embodiments, vehicles 102 are the same as, or similar to, vehicles 200, described herein (see FIG. 2). In some embodiments, a vehicle 200 of a set of vehicles 200 is associated with an autonomous fleet manager. In some embodiments, vehicles 102 travel along respective routes 106a-106n (referred to individually as route 106 and collectively as routes 106), as described herein. In some embodiments, one or more vehicles 102 include an autonomous system (e.g., an autonomous system that is the same as or similar to autonomous system 202).

[0029] Objects 104a-104n (referred to individually as object 104 and collectively as objects 104) include, for example, at least one vehicle, at least one pedestrian, at least one cyclist, at least one structure (e.g., a building, a sign, a fire hydrant, etc.), and/or the like. Each object 104 is stationary (e.g., located at a fixed location for a period of time) or mobile (e.g., having a velocity and associated with at least one trajectory). In some embodiments, objects 104 are associated with corresponding locations in area 108.

[0030] Routes 106a-106n (referred to individually as route 106 and collectively as routes 106) are each associated with (e.g., prescribe) a sequence of actions (also known as a trajectory) connecting states along which an AV can navigate. Each route 106 starts at an initial state (e.g., a state that corresponds to a first spatiotemporal location, velocity, and/or the like) and ends at a final goal state (e.g., a state that corresponds to a second spatiotemporal location that is different from the first spatiotemporal location) or goal region (e.g. a subspace of acceptable states (e.g., terminal states)). In some embodiments, the first state includes a location at which an individual or individuals are to be picked-up by the AV and the second state or region includes a location or locations at which the individual or individuals picked-up by the AV are to be dropped-off. In some embodiments, routes 106 include a plurality of acceptable state sequences (e.g., a plurality of spatiotemporal location sequences), the plurality of state sequences associated with (e.g., defining) a plurality of trajectories. In an example, routes 106 include only high level actions or imprecise state locations, such as a series of connected roads dictating turning directions at roadway intersections. Additionally, or alternatively, routes 106 may include more precise actions or states such as, for example, specific target lanes or precise locations within the lane areas and targeted speed at those positions. In an example, routes 106 include a plurality of precise state sequences along the at least one high level action sequence with a limited lookahead horizon to reach intermediate goals, where the combination of successive iterations of limited horizon state sequences cumulatively correspond to a plurality of trajectories that collectively form the high level route to terminate at the final goal state or region.

[0031] Area 108 includes a physical area (e.g., a geographic region) within which vehicles 102 can navigate. In an example, area 108 includes at least one state (e.g., a country, a province, an individual state of a plurality of states included in a country, etc.), at least one portion of a state, at least one city, at least one portion of a city, etc. In some embodiments, area 108 includes at least one named thoroughfare (referred to herein as a “road”) such as a highway, an interstate highway, a parkway, a city street, etc. Additionally, or alternatively, in some examples area 108 includes at least one unnamed road such as a driveway, a section of a parking lot, a section of a vacant and/or undeveloped lot, a dirt path, etc. In some embodiments, a road includes at least one lane (e.g., a portion of the road that can be traversed by vehicles 102). In an example, a road includes at least one lane associated with (e.g., identified based on) at least one lane marking.

[0032] Vehicle-to-lnfrastructure (V2I) device 110 (sometimes referred to as a Vehicle- to-lnfrastructure or Vehicle-to-Everything (V2X) device) includes at least one device configured to be in communication with vehicles 102 and/or V2I infrastructure system 118. In some embodiments, V2I device 110 is configured to be in communication with vehicles 102, remote AV system 114, fleet management system 116, and/or V2I system 118 via network 112. In some embodiments, V2I device 110 includes a radio frequency identification (RFID) device, signage, cameras (e.g., two-dimensional (2D) and/or three- dimensional (3D) cameras), lane markers, streetlights, parking meters, etc. In some embodiments, V2I device 110 is configured to communicate directly with vehicles 102. Additionally, or alternatively, in some embodiments V2I device 110 is configured to communicate with vehicles 102, remote AV system 114, and/or fleet management system 116 via V2I system 118. In some embodiments, V2I device 110 is configured to communicate with V2I system 118 via network 112.

[0033] Network 112 includes one or more wired and/or wireless networks. In an example, network 112 includes a cellular network (e.g., a long term evolution (LTE) network, a third generation (3G) network, a fourth generation (4G) network, a fifth generation (5G) network, a code division multiple access (CDMA) network, etc.), a public land mobile network (PLMN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a telephone network (e.g., the public switched telephone network (PSTN), a private network, an ad hoc network, an intranet, the Internet, a fiber optic-based network, a cloud computing network, etc., a combination of some or all of these networks, and/or the like.

[0034] Remote AV system 114 includes at least one device configured to be in communication with vehicles 102, V2I device 110, network 112, fleet management system 116, and/or V2I system 118 via network 112. In an example, remote AV system 114 includes a server, a group of servers, and/or other like devices. In some embodiments, remote AV system 114 is co-located with the fleet management system 116. In some embodiments, remote AV system 114 is involved in the installation of some or all of the components of a vehicle, including an autonomous system, an autonomous vehicle compute, software implemented by an autonomous vehicle compute, and/or the like. In some embodiments, remote AV system 114 maintains (e.g., updates and/or replaces) such components and/or software during the lifetime of the vehicle.

[0035] Fleet management system 116 includes at least one device configured to be in communication with vehicles 102, V2I device 110, remote AV system 114, and/or V21 infrastructure system 118. In an example, fleet management system 116 includes a server, a group of servers, and/or other like devices. In some embodiments, fleet management system 116 is associated with a ridesharing company (e.g., an organization that controls operation of multiple vehicles (e.g., vehicles that include autonomous systems and/or vehicles that do not include autonomous systems) and/or the like).

[0036] In some embodiments, V2I system 118 includes at least one device configured to be in communication with vehicles 102, V2I device 110, remote AV system 114, and/or fleet management system 116 via network 112. In some examples, V2I system 118 is configured to be in communication with V2I device 110 via a connection different from network 112. In some embodiments, V2I system 118 includes a server, a group of servers, and/or other like devices. In some embodiments, V2I system 118 is associated with a municipality or a private institution (e.g., a private institution that maintains V2I device 110 and/or the like).

[0037] The number and arrangement of elements illustrated in FIG. 1 are provided as an example. There can be additional elements, fewer elements, different elements, and/or differently arranged elements, than those illustrated in FIG. 1. Additionally, or alternatively, at least one element of environment 100 can perform one or more functions described as being performed by at least one different element of FIG. 1. Additionally, or alternatively, at least one set of elements of environment 100 can perform one or more functions described as being performed by at least one different set of elements of environment 100.

[0038] Referring now to FIG. 2, vehicle 200 (which may be the same as, or similar to vehicles 102 of FIG. 1 ) includes or is associated with autonomous system 202, powertrain control system 204, steering control system 206, and brake system 208. In some embodiments, vehicle 200 is the same as or similar to vehicle 102 (see FIG. 1 ). In some embodiments, autonomous system 202 is configured to confer vehicle 200 autonomous driving capability (e.g., implement at least one driving automation or maneuver-based function, feature, device, and/or the like that enable vehicle 200 to be partially or fully operated without human intervention including, without limitation, fully autonomous vehicles (e.g., vehicles that forego reliance on human intervention such as Level 5 ADS- operated vehicles), highly autonomous vehicles (e.g., vehicles that forego reliance on human intervention in certain situations such as Level 4 ADS-operated vehicles), conditional autonomous vehicles (e.g., vehicles that forego reliance on human intervention in limited situations such as Level 3 ADS-operated vehicles) and/or the like. In one embodiment, autonomous system 202 includes operational or tactical functionality required to operate vehicle 200 in on-road traffic and perform part or all of Dynamic Driving Task (DDT) on a sustained basis. In another embodiment, autonomous system 202 includes an Advanced Driver Assistance System (ADAS) that includes driver support features. Autonomous system 202 supports various levels of driving automation, ranging from no driving automation (e.g., Level 0) to full driving automation (e.g., Level 5). For a detailed description of fully autonomous vehicles and highly autonomous vehicles, reference may be made to SAE International's standard J3016: Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems, which is incorporated by reference in its entirety. In some embodiments, vehicle 200 is associated with an autonomous fleet manager and/or a ridesharing company.

[0039] Autonomous system 202 includes a sensor suite that includes one or more devices such as cameras 202a, LiDAR sensors 202b, radar sensors 202c, and microphones 202d. In some embodiments, autonomous system 202 can include more or fewer devices and/or different devices (e.g., ultrasonic sensors, inertial sensors, GPS receivers (discussed below), odometry sensors that generate data associated with an indication of a distance that vehicle 200 has traveled, and/or the like). In some embodiments, autonomous system 202 uses the one or more devices included in autonomous system 202 to generate data associated with environment 100, described herein. The data generated by the one or more devices of autonomous system 202 can be used by one or more systems described herein to observe the environment (e.g., environment 100) in which vehicle 200 is located. In some embodiments, autonomous system 202 includes communication device 202e, autonomous vehicle compute 202f, drive-by-wire (DBW) system 202h, and safety controller 202g.

[0040] Cameras 202a include at least one device configured to be in communication with communication device 202e, autonomous vehicle compute 202f, and/or safety controller 202g via a bus (e.g., a bus that is the same as or similar to bus 302 of FIG. 3). Cameras 202a include at least one camera (e.g., a digital camera using a light sensor such as a Charge-Coupled Device (CCD), a thermal camera, an infrared (IR) camera, an event camera, and/or the like) to capture images including physical objects (e.g., cars, buses, curbs, people, and/or the like). In some embodiments, camera 202a generates camera data as output. In some examples, camera 202a generates camera data that includes image data associated with an image. In this example, the image data may specify at least one parameter (e.g., image characteristics such as exposure, brightness, etc., an image timestamp, and/or the like) corresponding to the image. In such an example, the image may be in a format (e.g., RAW, JPEG, PNG, and/or the like). In some embodiments, camera 202a includes a plurality of independent cameras configured on (e.g., positioned on) a vehicle to capture images for the purpose of stereopsis (stereo vision). In some examples, camera 202a includes a plurality of cameras that generate image data and transmit the image data to autonomous vehicle compute 202f and/or a fleet management system (e.g., a fleet management system that is the same as or similar to fleet management system 116 of FIG. 1 ). In such an example, autonomous vehicle compute 202f determines depth to one or more objects in a field of view of at least two cameras of the plurality of cameras based on the image data from the at least two cameras. In some embodiments, cameras 202a is configured to capture images of objects within a distance from cameras 202a (e.g., up to 100 meters, up to a kilometer, and/or the like). Accordingly, cameras 202a include features such as sensors and lenses that are optimized for perceiving objects that are at one or more distances from cameras 202a.

[0041] In an embodiment, camera 202a includes at least one camera configured to capture one or more images associated with one or more traffic lights, street signs and/or other physical objects that provide visual navigation information. In some embodiments, camera 202a generates traffic light data associated with one or more images. In some examples, camera 202a generates TLD (Traffic Light Detection) data associated with one or more images that include a format (e.g., RAW, JPEG, PNG, and/or the like). In some embodiments, camera 202a that generates TLD data differs from other systems described herein incorporating cameras in that camera 202a can include one or more cameras with a wide field of view (e.g., a wide-angle lens, a fish-eye lens, a lens having a viewing angle of approximately 120 degrees or more, and/or the like) to generate images about as many physical objects as possible.

[0042] Light Detection and Ranging (LiDAR) sensors 202b include at least one device configured to be in communication with communication device 202e, autonomous vehicle compute 202f, and/or safety controller 202g via a bus (e.g., a bus that is the same as or similar to bus 302 of FIG. 3). LiDAR sensors 202b include a system configured to transmit light from a light emitter (e.g., a laser transmitter). Light emitted by LiDAR sensors 202b include light (e.g., infrared light and/or the like) that is outside of the visible spectrum. In some embodiments, during operation, light emitted by LiDAR sensors 202b encounters a physical object (e.g., a vehicle) and is reflected back to LiDAR sensors 202b. In some embodiments, the light emitted by LiDAR sensors 202b does not penetrate the physical objects that the light encounters. LiDAR sensors 202b also include at least one light detector which detects the light that was emitted from the light emitter after the light encounters a physical object. In some embodiments, at least one data processing system associated with LiDAR sensors 202b generates an image (e.g., a point cloud, a combined point cloud, and/or the like) representing the objects included in a field of view of LiDAR sensors 202b. In some examples, the at least one data processing system associated with LiDAR sensor 202b generates an image that represents the boundaries of a physical object, the surfaces (e.g., the topology of the surfaces) of the physical object, and/or the like. In such an example, the image is used to determine the boundaries of physical objects in the field of view of LiDAR sensors 202b.

[0043] Radio Detection and Ranging (radar) sensors 202c include at least one device configured to be in communication with communication device 202e, autonomous vehicle compute 202f, and/or safety controller 202g via a bus (e.g., a bus that is the same as or similar to bus 302 of FIG. 3). Radar sensors 202c include a system configured to transmit radio waves (either pulsed or continuously). The radio waves transmitted by radar sensors 202c include radio waves that are within a predetermined spectrum. In some embodiments, during operation, radio waves transmitted by radar sensors 202c encounter a physical object and are reflected back to radar sensors 202c. In some embodiments, the radio waves transmitted by radar sensors 202c are not reflected by some objects. In some embodiments, at least one data processing system associated with radar sensors 202c generates signals representing the objects included in a field of view of radar sensors 202c. For example, the at least one data processing system associated with radar sensor 202c generates an image that represents the boundaries of a physical object, the surfaces (e.g., the topology of the surfaces) of the physical object, and/or the like. In some examples, the image is used to determine the boundaries of physical objects in the field of view of radar sensors 202c.

[0044] Microphones 202d includes at least one device configured to be in communication with communication device 202e, autonomous vehicle compute 202f, and/or safety controller 202g via a bus (e.g., a bus that is the same as or similar to bus 302 of FIG. 3). Microphones 202d include one or more microphones (e.g., array microphones, external microphones, and/or the like) that capture audio signals and generate data associated with (e.g., representing) the audio signals. In some examples, microphones 202d include transducer devices and/or like devices. In some embodiments, one or more systems described herein can receive the data generated by microphones 202d and determine a position of an object relative to vehicle 200 (e.g., a distance and/or the like) based on the audio signals associated with the data.

[0045] Communication device 202e includes at least one device configured to be in communication with cameras 202a, LiDAR sensors 202b, radar sensors 202c, microphones 202d, autonomous vehicle compute 202f, safety controller 202g, and/or DBW (Drive-By-Wire) system 202h. For example, communication device 202e may include a device that is the same as or similar to communication interface 314 of FIG. 3. In some embodiments, communication device 202e includes a vehicle-to-vehicle (V2V) communication device (e.g., a device that enables wireless communication of data between vehicles).

[0046] Autonomous vehicle compute 202f includes at least one device configured to be in communication with cameras 202a, LiDAR sensors 202b, radar sensors 202c, microphones 202d, communication device 202e, safety controller 202g, and/or DBW system 202h. In some examples, autonomous vehicle compute 202f includes a device such as a client device, a mobile device (e.g., a cellular telephone, a tablet, and/or the like), a server (e.g., a computing device including one or more central processing units, graphical processing units, and/or the like), and/or the like. In some embodiments, autonomous vehicle compute 202f is the same as or similar to autonomous vehicle compute 400, described herein. Additionally, or alternatively, in some embodiments autonomous vehicle compute 202f is configured to be in communication with an autonomous vehicle system (e.g., an autonomous vehicle system that is the same as or similar to remote AV system 114 of FIG. 1 ), a fleet management system (e.g., a fleet management system that is the same as or similar to fleet management system 116 of FIG. 1 ), a V2I device (e.g., a V2I device that is the same as or similar to V2I device 110 of FIG. 1 ), and/or a V2I system (e.g., a V2I system that is the same as or similar to V2I system 118 of FIG. 1 ).

[0047] Safety controller 202g includes at least one device configured to be in communication with cameras 202a, LiDAR sensors 202b, radar sensors 202c, microphones 202d, communication device 202e, autonomous vehicle computer 202f, and/or DBW system 202h. In some examples, safety controller 202g includes one or more controllers (electrical controllers, electromechanical controllers, and/or the like) that are configured to generate and/or transmit control signals to operate one or more devices of vehicle 200 (e.g., powertrain control system 204, steering control system 206, brake system 208, and/or the like). In some embodiments, safety controller 202g is configured to generate control signals that take precedence over (e.g., overrides) control signals generated and/or transmitted by autonomous vehicle compute 202f.

[0048] DBW system 202h includes at least one device configured to be in communication with communication device 202e and/or autonomous vehicle compute 202f. In some examples, DBW system 202h includes one or more controllers (e.g., electrical controllers, electromechanical controllers, and/or the like) that are configured to generate and/or transmit control signals to operate one or more devices of vehicle 200 (e.g., powertrain control system 204, steering control system 206, brake system 208, and/or the like). Additionally, or alternatively, the one or more controllers of DBW system 202h are configured to generate and/or transmit control signals to operate at least one different device (e.g., a turn signal, headlights, door locks, windshield wipers, and/or the like) of vehicle 200.

[0049] Powertrain control system 204 includes at least one device configured to be in communication with DBW system 202h. In some examples, powertrain control system 204 includes at least one controller, actuator, and/or the like. In some embodiments, powertrain control system 204 receives control signals from DBW system 202h and powertrain control system 204 causes vehicle 200 to make longitudinal vehicle motion, such as start moving forward, stop moving forward, start moving backward, stop moving backward, accelerate in a direction, decelerate in a direction or to make lateral vehicle motion such as performing a left turn, performing a right turn, and/or the like. In an example, powertrain control system 204 causes the energy (e.g., fuel, electricity, and/or the like) provided to a motor of the vehicle to increase, remain the same, or decrease, thereby causing at least one wheel of vehicle 200 to rotate or not rotate.

[0050] Steering control system 206 includes at least one device configured to rotate one or more wheels of vehicle 200. In some examples, steering control system 206 includes at least one controller, actuator, and/or the like. In some embodiments, steering control system 206 causes the front two wheels and/or the rear two wheels of vehicle 200 to rotate to the left or right to cause vehicle 200 to turn to the left or right. In other words, steering control system 206 causes activities necessary for the regulation of the y-axis component of vehicle motion.

[0051] Brake system 208 includes at least one device configured to actuate one or more brakes to cause vehicle 200 to reduce speed and/or remain stationary. In some examples, brake system 208 includes at least one controller and/or actuator that is configured to cause one or more calipers associated with one or more wheels of vehicle 200 to close on a corresponding rotor of vehicle 200. Additionally, or alternatively, in some examples brake system 208 includes an automatic emergency braking (AEB) system, a regenerative braking system, and/or the like.

[0052] In some embodiments, vehicle 200 includes at least one platform sensor (not explicitly illustrated) that measures or infers properties of a state or a condition of vehicle 200. In some examples, vehicle 200 includes platform sensors such as a global positioning system (GPS) receiver, an inertial measurement unit (IMU), a wheel speed sensor, a wheel brake pressure sensor, a wheel torque sensor, an engine torque sensor, a steering angle sensor, and/or the like. Although brake system 208 is illustrated to be located in the near side of vehicle 200 in FIG. 2, brake system 208 may be located anywhere in vehicle 200.

[0053] Referring now to FIG. 3, illustrated is a schematic diagram of a device 300. As illustrated, device 300 includes processor 304, memory 306, storage component 308, input interface 310, output interface 312, communication interface 314, and bus 302. In some embodiments, device 300 corresponds to at least one device of vehicles 102 (e.g., at least one device of a system of vehicles 102) and/or one or more devices of network 112 (e.g., one or more devices of a system of network 112). In some embodiments, one or more devices of vehicles 102 (e.g., one or more devices of a system of vehicles 102) and/or one or more devices of network 112 (e.g., one or more devices of a system of network 112) include at least one device 300 and/or at least one component of device 300. As shown in FIG. 3, device 300 includes bus 302, processor 304, memory 306, storage component 308, input interface 310, output interface 312, and communication interface 314. [0054] Bus 302 includes a component that permits communication among the components of device 300. In some cases, processor 304 includes a processor (e.g., a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), and/or the like), a microphone, a digital signal processor (DSP), and/or any processing component (e.g., a field-programmable gate array (FPGA), an application specific integrated circuit (ASIC), and/or the like) that can be programmed to perform at least one function. Memory 306 includes random access memory (RAM), readonly memory (ROM), and/or another type of dynamic and/or static storage device (e.g., flash memory, magnetic memory, optical memory, and/or the like) that stores data and/or instructions for use by processor 304.

[0055] Storage component 308 stores data and/or software related to the operation and use of device 300. In some examples, storage component 308 includes a hard disk (e.g., a magnetic disk, an optical disk, a magneto-optic disk, a solid state disk, and/or the like), a compact disc (CD), a digital versatile disc (DVD), a floppy disk, a cartridge, a magnetic tape, a CD-ROM, RAM, PROM, EPROM, FLASH-EPROM, NV-RAM, and/or another type of computer readable medium, along with a corresponding drive.

[0056] Input interface 310 includes a component that permits device 300 to receive information, such as via user input (e.g., a touchscreen display, a keyboard, a keypad, a mouse, a button, a switch, a microphone, a camera, and/or the like). Additionally or alternatively, in some embodiments input interface 310 includes a sensor that senses information (e.g., a global positioning system (GPS) receiver, an accelerometer, a gyroscope, an actuator, and/or the like). Output interface 312 includes a component that provides output information from device 300 (e.g., a display, a speaker, one or more lightemitting diodes (LEDs), and/or the like).

[0057] In some embodiments, communication interface 314 includes a transceiver-like component (e.g., a transceiver, a separate receiver and transmitter, and/or the like) that permits device 300 to communicate with other devices via a wired connection, a wireless connection, or a combination of wired and wireless connections. In some examples, communication interface 314 permits device 300 to receive information from another device and/or provide information to another device. In some examples, communication interface 314 includes an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, a Wi-Fi® interface, a cellular network interface, and/or the like.

[0058] In some embodiments, device 300 performs one or more processes described herein. Device 300 performs these processes based on processor 304 executing software instructions stored by a computer-readable medium, such as memory 305 and/or storage component 308. A computer-readable medium (e.g., a non-transitory computer readable medium) is defined herein as a non-transitory memory device. A non-transitory memory device includes memory space located inside a single physical storage device or memory space spread across multiple physical storage devices.

[0059] In some embodiments, software instructions are read into memory 306 and/or storage component 308 from another computer-readable medium or from another device via communication interface 314. When executed, software instructions stored in memory 306 and/or storage component 308 cause processor 304 to perform one or more processes described herein. Additionally or alternatively, hardwired circuitry is used in place of or in combination with software instructions to perform one or more processes described herein. Thus, embodiments described herein are not limited to any specific combination of hardware circuitry and software unless explicitly stated otherwise.

[0060] Memory 306 and/or storage component 308 includes data storage or at least one data structure (e.g., a database and/or the like). Device 300 is capable of receiving information from, storing information in, communicating information to, or searching information stored in the data storage or the at least one data structure in memory 306 or storage component 308. In some examples, the information includes network data, input data, output data, or any combination thereof.

[0061] In some embodiments, device 300 is configured to execute software instructions that are either stored in memory 306 and/or in the memory of another device (e.g., another device that is the same as or similar to device 300). As used herein, the term “module” refers to at least one instruction stored in memory 306 and/or in the memory of another device that, when executed by processor 304 and/or by a processor of another device (e.g., another device that is the same as or similar to device 300) cause device 300 (e.g., at least one component of device 300) to perform one or more processes described herein. In some embodiments, a module is implemented in software, firmware, hardware, and/or the like.

[0062] The number and arrangement of components illustrated in FIG. 3 are provided as an example. In some embodiments, device 300 can include additional components, fewer components, different components, or differently arranged components than those illustrated in FIG. 3. Additionally or alternatively, a set of components (e.g., one or more components) of device 300 can perform one or more functions described as being performed by another component or another set of components of device 300.

[0063] Referring now to FIG. 4A, illustrated is an example block diagram of an autonomous vehicle compute 400 (sometimes referred to as an “AV stack”). As illustrated, autonomous vehicle compute 400 includes perception system 402 (sometimes referred to as a perception module), planning system 404 (sometimes referred to as a planning module), localization system 406 (sometimes referred to as a localization module), control system 408 (sometimes referred to as a control module), and database 410. In some embodiments, perception system 402, planning system 404, localization system 406, control system 408, and database 410 are included and/or implemented in an autonomous navigation system of a vehicle (e.g., autonomous vehicle compute 202f of vehicle 200). Additionally, or alternatively, in some embodiments perception system 402, planning system 404, localization system 406, control system 408, and database 410 are included in one or more standalone systems (e.g., one or more systems that are the same as or similar to autonomous vehicle compute 400 and/or the like). In some examples, perception system 402, planning system 404, localization system 406, control system 408, and database 410 are included in one or more standalone systems that are located in a vehicle and/or at least one remote system as described herein. In some embodiments, any and/or all of the systems included in autonomous vehicle compute 400 are implemented in software (e.g., in software instructions stored in memory), computer hardware (e.g., by microprocessors, microcontrollers, application-specific integrated circuits (ASICs), Field Programmable Gate Arrays (FPGAs), and/or the like), or combinations of computer software and computer hardware. It will also be understood that, in some embodiments, autonomous vehicle compute 400 is configured to be in communication with a remote system (e.g., an autonomous vehicle system that is the same as or similar to remote AV system 114, a fleet management system 116 that is the same as or similar to fleet management system 116, a V2I system that is the same as or similar to V2I system 118, and/or the like).

[0064] In some embodiments, perception system 402 receives data associated with at least one physical object (e.g., data that is used by perception system 402 to detect the at least one physical object) in an environment and classifies the at least one physical object. In some examples, perception system 402 receives image data captured by at least one camera (e.g., cameras 202a), the image associated with (e.g., representing) one or more physical objects within a field of view of the at least one camera. In such an example, perception system 402 classifies at least one physical object based on one or more groupings of physical objects (e.g., bicycles, vehicles, traffic signs, pedestrians, and/or the like). In some embodiments, perception system 402 transmits data associated with the classification of the physical objects to planning system 404 based on perception system 402 classifying the physical objects.

[0065] In some embodiments, planning system 404 receives data associated with a destination and generates data associated with at least one route (e.g., routes 106) along which a vehicle (e.g., vehicles 102) can travel along toward a destination. In some embodiments, planning system 404 periodically or continuously receives data from perception system 402 (e.g., data associated with the classification of physical objects, described above) and planning system 404 updates the at least one trajectory or generates at least one different trajectory based on the data generated by perception system 402. In other words, planning system 404 may perform tactical function-related tasks that are required to operate vehicle 102 in on-road traffic. Tactical efforts involve maneuvering the vehicle in traffic during a trip, including but not limited to deciding whether and when to overtake another vehicle, change lanes, or selecting an appropriate speed, acceleration, deacceleration, etc. In some embodiments, planning system 404 receives data associated with an updated position of a vehicle (e.g., vehicles 102) from localization system 406 and planning system 404 updates the at least one trajectory or generates at least one different trajectory based on the data generated by localization system 406. [0066] In some embodiments, localization system 406 receives data associated with (e.g., representing) a location of a vehicle (e.g., vehicles 102) in an area. In some examples, localization system 406 receives LiDAR data associated with at least one point cloud generated by at least one LiDAR sensor (e.g., LiDAR sensors 202b). In certain examples, localization system 406 receives data associated with at least one point cloud from multiple LiDAR sensors and localization system 406 generates a combined point cloud based on each of the point clouds. In these examples, localization system 406 compares the at least one point cloud or the combined point cloud to two-dimensional (2D) and/or a three-dimensional (3D) map of the area stored in database 410. Localization system 406 then determines the position of the vehicle in the area based on localization system 406 comparing the at least one point cloud or the combined point cloud to the map. In some embodiments, the map includes a combined point cloud of the area generated prior to navigation of the vehicle. In some embodiments, maps include, without limitation, high-precision maps of the roadway geometric properties, maps describing road network connectivity properties, maps describing roadway physical properties (such as traffic speed, traffic volume, the number of vehicular and cyclist traffic lanes, lane width, lane traffic directions, or lane marker types and locations, or combinations thereof), and maps describing the spatial locations of road features such as crosswalks, traffic signs or other travel signals of various types. In some embodiments, the map is generated in real-time based on the data received by the perception system. [0067] In another example, localization system 406 receives Global Navigation Satellite System (GNSS) data generated by a global positioning system (GPS) receiver. In some examples, localization system 406 receives GNSS data associated with the location of the vehicle in the area and localization system 406 determines a latitude and longitude of the vehicle in the area. In such an example, localization system 406 determines the position of the vehicle in the area based on the latitude and longitude of the vehicle. In some embodiments, localization system 406 generates data associated with the position of the vehicle. In some examples, localization system 406 generates data associated with the position of the vehicle based on localization system 406 determining the position of the vehicle. In such an example, the data associated with the position of the vehicle includes data associated with one or more semantic properties corresponding to the position of the vehicle.

[0068] In some embodiments, control system 408 receives data associated with at least one trajectory from planning system 404 and control system 408 controls operation of the vehicle. In some examples, control system 408 receives data associated with at least one trajectory from planning system 404 and control system 408 controls operation of the vehicle by generating and transmitting control signals to cause a powertrain control system (e.g., DBW system 202h, powertrain control system 204, and/or the like), a steering control system (e.g., steering control system 206), and/or a brake system (e.g., brake system 208) to operate. For example, control system 408 is configured to perform operational functions such as a lateral vehicle motion control or a longitudinal vehicle motion control. The lateral vehicle motion control causes activities necessary for the regulation of the y-axis component of vehicle motion. The longitudinal vehicle motion control causes activities necessary for the regulation of the x-axis component of vehicle motion. In an example, where a trajectory includes a left turn, control system 408 transmits a control signal to cause steering control system 206 to adjust a steering angle of vehicle 200, thereby causing vehicle 200 to turn left. Additionally, or alternatively, control system 408 generates and transmits control signals to cause other devices (e.g., headlights, turn signal, door locks, windshield wipers, and/or the like) of vehicle 200 to change states.

[0069] In some embodiments, perception system 402, planning system 404, localization system 406, and/or control system 408 implement at least one machine learning model (e.g., at least one multilayer perceptron (MLP), at least one convolutional neural network (CNN), at least one recurrent neural network (RNN), at least one autoencoder, at least one transformer, and/or the like). In some examples, perception system 402, planning system 404, localization system 406, and/or control system 408 implement at least one machine learning model alone or in combination with one or more of the above-noted systems. In some examples, perception system 402, planning system 404, localization system 406, and/or control system 408 implement at least one machine learning model as part of a pipeline (e.g., a pipeline for identifying one or more objects located in an environment and/or the like). [0070] Database 410 stores data that is transmitted to, received from, and/or updated by perception system 402, planning system 404, localization system 406 and/or control system 408. In some examples, database 410 includes a storage component (e.g., a storage component that is the same as or similar to storage component 308 of FIG. 3) that stores data and/or software related to the operation and uses at least one system of autonomous vehicle compute 400. In some embodiments, database 410 stores data associated with 2D and/or 3D maps of at least one area. In some examples, database 410 stores data associated with 2D and/or 3D maps of a portion of a city, multiple portions of multiple cities, multiple cities, a county, a state, a State (e.g., a country), and/or the like). In such an example, a vehicle (e.g., a vehicle that is the same as or similar to vehicles 102 and/or vehicle 200) can drive along one or more drivable regions (e.g., single-lane roads, multi-lane roads, highways, back roads, off road trails, and/or the like) and cause at least one LiDAR sensor (e.g., a LiDAR sensor that is the same as or similar to LiDAR sensors 202b) to generate data associated with an image representing the objects included in a field of view of the at least one LiDAR sensor.

[0071] In some embodiments, database 410 can be implemented across a plurality of devices. In some examples, database 410 is included in a vehicle (e.g., a vehicle that is the same as or similar to vehicles 102 and/or vehicle 200), an autonomous vehicle system (e.g., an autonomous vehicle system that is the same as or similar to remote AV system 114, a fleet management system (e.g., a fleet management system that is the same as or similar to fleet management system 116 of FIG. 1 , a V2I system (e.g., a V2I system that is the same as or similar to V2I system 118 of FIG. 1 ) and/or the like.

[0072] Referring now to FIG. 5, illustrated is a diagram of an implementation 500 a MIMO radar system with an extended beamspace. In some embodiments, implementation 500 includes a MIMO radar system 504. In some embodiments, the MIMO radar system 504 is the same as, similar to, or includes radar sensors 202c of Fig. 2. In some embodiments, the physical antennas of the MIMO radar system are arranged as described with respect to FIGs. 6-9.

[0073] In some embodiments, the vehicle 502 navigates through an environment (e.g., environment 100 of Figure 1 ) using devices such as the MIMO radar system 504 to observe the environment. Vehicle 502 (which may be the same as, or similar to vehicles 102 of FIG. 1 or vehicle 200 or FIG. 2) includes an autonomous vehicle compute 504 (which may be the same as, or similar to autonomous vehicle compute 202f of FIG. 2). In examples, a control system 506 (which may be the same as, or similar to control system 408 of FIG. 4). In examples, the control system 506 receives data associated with at least one trajectory from a planning system (e.g., planning system 404 of FIG. 4), and control system 506 controls operation of the vehicle. In some examples, the at least one trajectory is generated based on data captured from the environment, such as data captured by the MIMO radar system 504. For example, a perception system (e.g., perception system 402 of FIG. 4) receives data associated with at least one physical object (e.g., data captured by MIMO radar system 504 that is used by perception system 402 to detect the at least one physical object) in an environment and classifies the at least one physical object. In examples, the planning system periodically or continuously receives data from the perception system, and the planning system updates the at least one trajectory or generates at least one different trajectory based on the data generated by perception system. The control system 506 controls operation of the vehicle in accordance with the at least one trajectory or the at least one different trajectory.

[0074] In an advanced massive MIMO automotive radar system, multiple-inputs and multiple-outputs (antennas) are arranged to exploit multipath propagation, where radio frequency (RF) signals reach receive antennas (e.g., receivers, RX) by two or more paths. MIMO radar implements receive antennas and transmit antennas (e.g., transmitters, TX) in a physical array distributed across an aperture. Each transmitter of a radio frequency chain is connected to a radiation subarray/element. MIMO radar signals propagate using closely-spaced antennas within the physical array to increase spatial resolution and dynamic range. Traditionally, to improve spatial resolution traditional MIMO radar systems transmit mutually orthogonal signals from multiple transmit antennas, and these signals are reflected by objects in the environment and extracted from each of the receive antennas. For example, a MIMO radar system with physical elements including 48 transmit antennas and 48 receive antennas can be used to derive 2304 signals reflected in the environment and captured by the receive antennas due to the orthogonality of the transmitted signals. Each of the N_tx transmitters outputs an orthogonal waveform that can be separated at each of the N_rx receivers, forming a N_txx N_rx virtual array. A limited 2304- element virtual array is created using 48 transmit antennas and 48 receive antennas by performing radio frequency (RF) management on the received signals, also known as beamforming. The virtual array is referred to as a beamspace.

[0075] The number of physical elements (transmitters and receivers) of the radar system directly impacts the size and density of the beamspace. Additionally, the number of physical elements directly influences the cost of the MIMO radar system, where a greater number of transmitters and receivers enable increased system functionality at an increased cost when compared with a lower number of transmitters and receivers. Embodiments described herein enable an extended beamspace in massive MIMO radar by strategically grouping of transmitters in a beamforming scheme, thereby extending the beamspace by creating additional phase centers that are used to expand virtual arrays derived from the physical elements. The present techniques improve performance indicators of the physical array including dynamic range, degree of freedom, angular ambiguity, and the like. Moreover, the improvements described herein enable a finer spatial coverage and resolution of the MIMO radar system without increasing the number of physical elements of the MIMO radar system.

[0076] FIG. 6 shows a physical array 600 of a MIMO radar system. In the example of FIG. 6, the physical elements of the physical array include 48 transmit elements 602 and 48 receive elements 604. The physical array 600 includes transmitter and receiver elements / subarrays, with each physical element being driven by an independent RF chain. In examples, an independent RF chain transmits a signal that is independent from other RF chains. For example, a respective transmit element 602 transmits an orthogonal signal that can be separated from signals transmitted by other transmit elements at each respective receiver element. A position of a phase center of each respective transmit element 602 and receive element 604 is denoted by p-^x and p , where i is the index of the transmitter elements, and j is the index of the receiver elements. In some embodiments, phase centers of the virtual elements created by beamforming is determined by the following: Pij^ir = Pi^X + Pj^x. for all i and j. For a system with N_tx transmitters and N_rx receivers, the virtual array has N_txx N_rx elements, each with a phase center [0077] FIG. 7A shows limited beamforming applied to a physical array 700. In some embodiments, the physical array 700 is the same as or similar to the physical array 600 of FIG. 6. In the example of FIG. 7, the physical elements of the physical array includes 48 transmit elements 702 and 48 receive elements 704. In the example of FIG. 7A, adjacent transmitter elements are combined to improve a directivity and maximum detection range of a radar system, as shown by group 706. As an example, at each time step, each of the running K transmitter elements operates in a beamforming mode by transmitting coherent waveforms. The beamformed phase centers are given by the following:

[0078] FIG. 7B shows beamformed phase centers 706 from limited beamforming with receiver elements 704 in a plot 700B. Groups of six adjacent transmitters in columns of the corresponding physical array (e.g., physical array 700A of FIG. 7A) outputs a beamformed waveform, which creates twenty-eight phase centers 712 each near the center-of-gravity of the active transmit elements. In examples, active transmit element refers to a transmitter element actively transmitting signals at a given time. In the example of FIG. 7B, the grouping of adjacent transmitters causes a spatial aliasing effect in which plane waves incident to the array from visible angles other than the desired direction are coherently added, causing grating lobes in the received signals. FIG. 7C shows an array factor of the elevation array 700C, with grating lobes 732 and 734 created from limited beamforming shown in FIGs. 7A and 7B. In examples, the elevation array 700C shows an elevation angle on the X-axis and an array pattern (in decibels, d B) on the Y-axis. For example, elevation angle represents an angle above the horizontal plane. The array pattern shows the magnitude of the array factor or the signal strength in decibels (dB).

[0079] As shown in FIG. 7C, grating lobes 732 and grating lobes 734 are created at +/-41 .81 °. Grating lobes are undesirable and identical to the main lobe 730. The main lobe refers to the peak of the plot, indicating the direction of maximum radiation or reception. In examples, grating lobes are a lobe other than the main lobe, produced by an array antenna when the inter-element spacing is sufficiently large to permit the in- phase addition of radiated fields in more than one direction. In examples, grating lobes can occur in uniformly spaced arrays (arrays with an equal distance between adjacent elements) when the antenna element separation is too large. As shown by FIGs. 7A-7C, limited beamforming causes grating lobes and also creates a number of beamformed transmitter elements that is strictly smaller than the physical transmitter elements, ultimately reducing the degree of freedom of a radar system. Further, an aperture of the beamformed transmitter array is smaller than the physical array size. Reducing the aperture causes a reduced angular resolution of a radar system.

[0080] FIG. 8A shows an array geometry of beamformed phase centers 812 from extended beamforming with receiver elements 804 in a plot 800A. In some embodiments, the beamformed phase centers 812 are created by applying an extended beamforming scheme to a physical array, such as the physical array 600 of FIG. 6. In particular, for each time step, a non-uniform number of transmit elements (e.g., transmit elements 602 of FIG. 6) outputs coherent signals to generate beams with predetermined spatial characteristics. In examples, the spatial characteristics form a finger shaped beam pattern. In examples, the number of active transmit element changes over time. Accordingly, at each time step a varying, non-uniform number of transmit elements are transmitting signals.

[0081] Consider an example using the 48 transmitter elements 602 and 48 receiver elements 602 described in FIG. 6. FIG. 8A shows beamformed phase centers 812 are determined for each non-uniform group of transmitter elements. The plot 800A shows an array geometry of 68-element beamformed phase centers 812 and 48 receiver elements 804 generated by the beamforming scheme in Table 1. In Table 1 , the expanded beamforming scheme groups transmit elements according to the existence of an individual, independent phase center for the respective group, where a location of each phase center is different from other phase centers. In examples, the individual, independent phase center is a unique phase center that is not the same as or similar to other phase centers.

[0082] FIG. 8B shows an extended beamspace 800B based on phase centers 812 of FIG. 8A. Phase centers 812 are created for each group of transmitter elements. Variable T_k denotes the set of indexes of transmitter elements used to form the k-th beam and the associated k-th beamformed phase center. Phase centers are created as follows: bf _ ( .iET_k Pi^{X Pk} |r_fc|

[0083] where p%^f is an expanded beamformed phase center. In some embodiments, the phase centers are calculated as a weighted average of the positions of the transmitters in each group of transmitters, where the groups of transmitters have individual, independent phase centers as determined by the center of gravity associated with each respective group of transmitters. Each of the phase center p*^f is paired with each of the physical receiver subarrays pj^x to form an expanded beamspace 800B as follows: p^rj = p^ + p"

[0084] The number of virtual elements 820 in the expanded beamspace is therefore K x N_rx. For the 68-element beamformed phase centers 812 and 48 receiver elements 804 shown in FIG. 8A, the corresponding extended beamspace 800B is a 3264-element virtual array.

[0085] FIG. 8C shows an array factor of the elevation array 800C. In examples, the elevation array 8000 shows an elevation angle on the X-axis and an array pattern (in decibels, dB) on the Y-axis. In examples, the array factor is calculated based on array geometry and beam weights (amplitude and phase) of the extended beamspace. In the example of FIG. 8C, grating lobes are suppressed down to -17.4dB. The expanded beamforming scheme as described herein enables a greater degree of freedom of the MIMO radar system. In examples, the degree of freedom refers to the number of objects a radar array can simultaneously detect and localize in each of the range-doppler bin. Further, the aperture of the beamformed transmitter array is larger than the physical array size, thereby increasing the aperture and the angular resolution of the MIMO radar system. Angular ambiguity is improved, where angular ambiguity describes the field of view of the MIMO radar system in angles. Improved angular ambiguity enables unique localization of objects in an angle domain. Moreover, the virtual array in the expanded beamspace does not from grating lobe issues, as the grating lobes are suppressed as shown in FIG. 8C.

[0086] Referring now to FIG. 9, illustrated is a flowchart of a process 900 for an extended beamspace in massive MIMO radar. In some embodiments, one or more of the steps described with respect to process 900 are performed (e.g., completely, partially, and/or the like) by autonomous system 502.

[0087] At block 902, beamformed phase centers are determined for non-uniform groups of transmit elements based on a center of gravity for each respective group, wherein a respective phase center of each non-uniform group is paired with receive elements to form an extended beamspace. In some embodiments, the center of gravity is determined by identifying transmitter positions and averaging the positions of transmitters in a respective group. In some embodiments, the center of gravity is determined by identifying transmitter positions and assigning weights to each transmitter based on a power or phase of a respective transmitter. The center of gravity is determined by calculating a weighted average of the positions of transmitters in a respective group.

[0088] At block 904, each respective group is activated to output corresponding coherent signals. In examples, transmitters of each respective group transmit a set of correlated signals so that the signals are concentrated (e.g., combined) in a desired direction and supressed in the undesired directions. In examples, respective groups of transmit elements are activated iteratively over time to output coherent signals.

[0089] At block 906, received signals reflected from the environment are extracted to form an extended beamspace (e.g., beamspace 800B). In examples, Varying numbers of transmit elements in the non-uniform groups increases a resolution of the extended beamspace. In some embodiments, predetermined weights are applied to the received signals to form the extended beamspace. In examples, the predetermined weights enable phase and amplitude modifications to the received signals that transform the signals to the extended beamspace. For example, the predetermined weights are calculated based on a beam direction associated with the received signals and an array geometry associated with the physical elements of the MIMO radar system. In some embodiments, the extracted signals are used to generate an image that represents the boundaries of a physical object, the surfaces (e.g., the topology of the surfaces) of the physical object, and/or the like. In some examples, the image is used to determine the boundaries of physical objects in the field of view of the MIMO radar system. Additionally, in some embodiments an autonomous vehicle navigates through an environment based on the objects detected in the expanded beamspace. Navigation by the autonomous vehicle is more efficient, as the signal strength associated with physical transmit elements and receive elements of a massive MIMO radar is enhanced and signal quality is increased. Further, object detection and tracking is improved by the increased resolution of the extended beamspace.

[0090] Embodiments/Examples

[0091] According to some non-limiting embodiments or examples, provided is a system, including: transmit elements selectively coupled in non-uniform groups based on beamformed phase centers of respective groups of transmit elements; receive elements configured in a physical array with the transmit elements, wherein the respective groups of transmit elements are activated to output coherent signals and the receive elements receive reflected signals from an environment; and an extended beamspace including the beamformed phase centers, wherein varying numbers of transmit elements in the non- uniform groups increases a resolution of the extended beamspace.

[0092] According to some non-limiting embodiments or examples, provided is a method, including: determining beamformed phase centers for non-uniform groups of transmit elements corresponding to a center of gravity of transmit elements in respective groups; activating respective groups of transmit elements to output coherent signals; and extracting received signals reflected from an environment to form an extended beamspace, wherein the received signals are obtained by receive elements.

[0093] According to some non-limiting embodiments or examples, provided is at least one non-transitory computer-readable medium including one or more instructions that, when executed by at least one processor, cause the at least one processor to: determine beamformed phase centers for non-uniform groups of transmit elements corresponding to a center of gravity of transmit elements in respective groups; activate respective groups of transmit elements to output coherent signals; and extract received signals reflected from an environment to form an extended beamspace, wherein the received signals are obtained by receive elements.

[0094] Further non-limiting aspects or embodiments are set forth in the following numbered embodiments:

[0095] Embodiment 1 : A system, including: transmit elements selectively coupled in non-uniform groups based on beamformed phase centers of respective groups of transmit elements; receive elements configured in a physical array with the transmit elements, wherein the respective groups of transmit elements are activated to output coherent signals and the receive elements receive reflected signals from an environment; and an extended beamspace including the beamformed phase centers, wherein varying numbers of transmit elements in the non-uniform groups increases a resolution of the extended beamspace.

[0096] Embodiment 2: The system of any preceding embodiment, wherein a beamformed phase center of a respective group of transmit elements is determined by calculating a center of gravity for the respective group of transmit elements.

[0097] Embodiment 3. The system of any preceding embodiment, wherein the beamformed phase centers correspond to locations that are different from locations of other beamformed phase centers.

[0098] Embodiment 4: The system of any preceding embodiment, wherein respective groups of transmit elements are activated iteratively over time to output the coherent signals.

[0099] Embodiment 5: The system of any preceding embodiment, wherein the beamspace is a virtual array with a greater resolution when compared with a resolution of a corresponding physical array including the transmit elements and the receive elements.

[0100] Embodiment 6: The system of any preceding embodiment, wherein the non- uniform groups include different numbers of transmit elements in each respective group. [0101] Embodiment 7: The system of any preceding embodiment, wherein coherent signals output by activating respective groups of transmit elements are associated with predetermined spatial characteristics.

[0102] Embodiment 8: A method, including: determining beamformed phase centers for non-uniform groups of transmit elements corresponding to a center of gravity of transmit elements in respective groups; activating respective groups of transmit elements to output coherent signals; and extracting received signals reflected from an environment to form an extended beamspace, wherein the received signals are obtained by receive elements.

[0103] Embodiment 9: The method of any preceding embodiment, wherein the beamformed phase centers correspond to locations that are different from locations of other beamformed phase centers.

[0104] Embodiment 10: The method of any preceding embodiment, wherein respective groups of transmit elements are activated iteratively over time to output coherent signals.

[0105] Embodiment 11 : The method of any preceding embodiment, wherein the beamspace is a virtual array with a greater resolution when compared with a resolution of a corresponding physical array including the transmit elements and the receive elements.

[0106] Embodiment 12: The method of any preceding embodiment, wherein the non- uniform groups include different numbers of transmit elements in each respective group. [0107] Embodiment 13: The method of any preceding embodiment, wherein coherent signals output by activating respective groups of transmit elements are associated with predetermined spatial characteristics.

[0108] Embodiment 14: The method of any preceding embodiment, wherein the center of gravity is calculated as a weighted average of the positions of transmitters in a respective group. [0109] Embodiment 15: At least one non-transitory storage media storing instructions that, when executed by at least one processor, cause the at least one processor to: determine beamformed phase centers for non-uniform groups of transmit elements corresponding to a center of gravity of transmit elements in respective groups; activate respective groups of transmit elements to output coherent signals; and extract received signals reflected from an environment to form an extended beamspace, wherein the received signals are obtained by receive elements.

[0110] Embodiment 16: The at least one non-transitory storage media of any preceding embodiment, wherein the beamformed phase centers correspond to locations that are different from locations of other beamformed phase centers.

[0111] Embodiment 17: The at least one non-transitory storage media of any preceding embodiment, wherein the instructions further cause the at least one processor to iteratively activate respective groups of transmit elements over time to output coherent signals.

[0112] Embodiment 18: The at least one non-transitory storage media of any preceding embodiment, wherein the beamspace is a virtual array with a greater resolution when compared with a resolution of a corresponding physical array including the transmit elements and the receive elements.

[0113] Embodiment 19: The at least one non-transitory storage media of any preceding embodiment, wherein the non-uniform groups include different numbers of transmit elements in each respective group.

[0114] Embodiment 20: The at least one non-transitory storage media of any preceding embodiment, wherein coherent signals output by activating respective groups of transmit elements are associated with predetermined spatial characteristics.

[0115] In the foregoing description, aspects and embodiments of the present disclosure have been described with reference to numerous specific details that can vary from implementation to implementation. Accordingly, the description and drawings are to be regarded in an illustrative rather than a restrictive sense. The sole and exclusive indicator of the scope of the invention, and what is intended by the applicants to be the scope of the invention, is the literal and equivalent scope of the set of claims that issue from this application, in the specific form in which such claims issue, including any subsequent correction. Any definitions expressly set forth herein for terms contained in such claims shall govern the meaning of such terms as used in the claims. In addition, when we use the term “further comprising,” in the foregoing description or following claims, what follows this phrase can be an additional step or entity, or a sub-step/sub- entity of a previously-recited step or entity.

Claims

WHAT IS CLAIMED IS:

1. A system, comprising: transmit elements selectively coupled in non-uniform groups based on beamformed phase centers of respective groups of transmit elements; receive elements configured in a physical array with the transmit elements, wherein the respective groups of transmit elements are activated to output coherent signals and the receive elements receive reflected signals from an environment; and an extended beamspace comprising the beamformed phase centers, wherein varying numbers of transmit elements in the non-uniform groups increases a resolution of the extended beamspace.

2. The system of any preceding claim, wherein a beamformed phase center of a respective group of transmit elements is determined by calculating a center of gravity for the respective group of transmit elements.

3. The system of any preceding claim, wherein the beamformed phase centers correspond to locations that are different from locations of other beamformed phase centers.

4. The system of any preceding claim, wherein respective groups of transmit elements are activated iteratively over time to output the coherent signals.

5. The system of any preceding claim, wherein the beamspace is a virtual array with a greater resolution when compared with a resolution of a corresponding physical array comprising the transmit elements and the receive elements.

6. The system of any preceding claim, wherein the non-uniform groups comprise different numbers of transmit elements in each respective group.

7. The system of any preceding claim, wherein coherent signals output by activating respective groups of transmit elements are associated with predetermined spatial characteristics.

8. A method, comprising: determining beamformed phase centers for non-uniform groups of transmit elements corresponding to a center of gravity of transmit elements in respective groups; activating respective groups of transmit elements to output coherent signals; and extracting received signals reflected from an environment to form an extended beamspace, wherein the received signals are obtained by receive elements.

9. The method of any preceding claim, wherein the beamformed phase centers correspond to locations that are different from locations of other beamformed phase centers.

10. The method of any preceding claim, wherein respective groups of transmit elements are activated iteratively over time to output coherent signals.

11. The method of any preceding claim, wherein the beamspace is a virtual array with a greater resolution when compared with a resolution of a corresponding physical array comprising the transmit elements and the receive elements.

12. The method of any preceding claim, wherein the non-uniform groups comprise different numbers of transmit elements in each respective group.

13. The method of any preceding claim, wherein coherent signals output by activating respective groups of transmit elements are associated with predetermined spatial characteristics.

14. The method of any preceding claim, wherein the center of gravity is calculated as a weighted average of the positions of transmitters in a respective group.

15. At least one non-transitory storage media storing instructions that, when executed by at least one processor, cause the at least one processor to: determine beamformed phase centers for non-uniform groups of transmit elements corresponding to a center of gravity of transmit elements in respective groups; activate respective groups of transmit elements to output coherent signals; and extract received signals reflected from an environment to form an extended beamspace, wherein the received signals are obtained by receive elements.

16. The at least one non-transitory storage media of any preceding claim, wherein the beamformed phase centers correspond to locations that are different from locations of other beamformed phase centers.

17. The at least one non-transitory storage media of any preceding claim, wherein the instructions further cause the at least one processor to iteratively activate respective groups of transmit elements over time to output coherent signals.

18. The at least one non-transitory storage media of any preceding claim, wherein the beamspace is a virtual array with a greater resolution when compared with a resolution of a corresponding physical array comprising the transmit elements and the receive elements.

19. The at least one non-transitory storage media of any preceding claim, wherein the non-uniform groups comprise different numbers of transmit elements in each respective group.

20. The at least one non-transitory storage media of any preceding claim, wherein coherent signals output by activating respective groups of transmit elements are associated with predetermined spatial characteristics.