技术领域technical field
本发明属于无人机分析技术领域，尤其涉及一种无人机反制系统。The invention belongs to the technical field of UAV analysis, and in particular relates to a UAV countermeasure system.
背景技术Background technique
近年来，随着无人机等航空器的快速发展与低空空域管制的逐渐开放，出现了“低慢小”无人机违规升空与黑飞等事件日益增多的现象，因此需要实现对“低慢小”无人机进行跟踪与摧毁，以抵制“低慢小”无人机违规升空。In recent years, with the rapid development of drones and other aircraft and the gradual opening of low-altitude airspace control, there have been more and more incidents of "low, slow and small" drones taking off illegally and flying in the sky. "Slow and small" drones are tracked and destroyed to resist the illegal launch of "low, slow and small" drones.
“低慢小”无人机具有飞行高度低、运动速度慢、雷达散射面积小等特点，因此，对“低慢小”无人机的防御、打击和反制控制难度较大。现有技术中对“低慢小”无人机反制时，确定无人机的位置后直接对无人机进行跟踪，当无人机的位置发生变化后则可能导致跟踪或者摧毁失败。"Low, slow and small" UAVs have the characteristics of low flight height, slow movement speed, and small radar scattering area. Therefore, it is difficult to control the defense, strike and countermeasures of "low, slow and small" UAVs. In the prior art, when counteracting a "low, slow and small" UAV, the UAV is directly tracked after the position of the UAV is determined. When the position of the UAV changes, the tracking or destruction may fail.
发明内容SUMMARY OF THE INVENTION
有鉴于此，本发明实施例提供了一种无人机反制系统，以解决现有技术中当无人机的位置发生变化后则可能导致跟踪失败或者摧毁失败的问题。In view of this, the embodiments of the present invention provide a UAV countermeasure system to solve the problem in the prior art that when the position of the UAV changes, the tracking failure or the destruction failure may be caused.
本发明实施例的第一方面提供了一种无人机反制系统，包括：探测模块、地面测控模块以及攻击无人机；A first aspect of the embodiments of the present invention provides a UAV countermeasure system, including: a detection module, a ground measurement and control module, and an attack UAV;
所述探测模块，用于对获取的地面探测数据以及空中探测数据进行数据融合，根据融合后的数据对空中飞行的无人机进行目标识别以及目标跟踪，获取目标无人机的位置信息，并将所述目标无人机的位置信息发送给所述地面测控模块；The detection module is used to perform data fusion on the acquired ground detection data and aerial detection data, perform target recognition and target tracking on the drone flying in the air according to the fused data, obtain the position information of the target drone, and sending the position information of the target UAV to the ground measurement and control module;
所述地面测控模块，用于根据接收到的所述目标无人机的位置信息对攻击无人机的航线进行规划，获得预规划航线；以及将所述预规划航线和所述目标无人机的位置信息上传至所述攻击无人机；The ground measurement and control module is used to plan the route of the attacking drone according to the received position information of the target drone to obtain a pre-planned route; and connect the pre-planned route and the target drone upload the location information to the attack drone;
所述攻击无人机，用于接收所述预规划航线和所述目标无人机的位置信息，根据所述目标无人机的位置信息检测目标无人机的位置是否发生改变，当所述目标无人机的位置发生改变时，根据所述目标无人机的位置改变信息、所述攻击无人机实时探测到的信息以及实时接收到的所述地面测控模块监测到的信息对所述预规划航线进行重规划，并按照重规划的航线飞行至可攻击区域后对所述目标无人机进行攻击。The attack UAV is used to receive the pre-planned route and the position information of the target UAV, and detect whether the position of the target UAV changes according to the position information of the target UAV. When the position of the target UAV changes, according to the position change information of the target UAV, the information detected by the attacking UAV in real time, and the information monitored by the ground measurement and control module received in real time The pre-planned route is re-planned, and the target UAV is attacked after flying to the attackable area according to the re-planned route.
在一实施例中，所述根据接收到的所述目标无人机的位置信息对攻击无人机的航线进行规划，获得预规划航线，包括：In one embodiment, the planning of the route of the attacking drone according to the received position information of the target drone to obtain a pre-planned route includes:
根据接收到的所述目标无人机的位置信息以及飞行约束信息对攻击无人机的航线进行规划，获得预规划航线；According to the received position information of the target UAV and the flight constraint information, plan the route of the attacking UAV, and obtain the pre-planned route;
采用航迹代价评估模型对所述预规划航线进行评估，确定最优预规划航线。The pre-planned route is evaluated using a track cost evaluation model to determine the optimal pre-planned route.
在一实施例中，所述飞行约束信息包括无人机本体性能约束信息和外部环境约束信息；In one embodiment, the flight constraint information includes UAV body performance constraint information and external environment constraint information;
所述无人机本体性能约束信息包括最大航程、最大爬升角、最小步长以及最小转弯半径中的至少一种；The UAV body performance constraint information includes at least one of a maximum range, a maximum climb angle, a minimum step size and a minimum turning radius;
所述外部环境约束信息包括大气威胁、雷达威胁、导弹威胁、高炮威胁及地形碰撞威胁中的至少一种。The external environment constraint information includes at least one of atmospheric threats, radar threats, missile threats, anti-aircraft artillery threats, and terrain collision threats.
在一实施例中，所述攻击无人机飞行到所述可攻击区域的过程中，当探测到威胁信号时，确定所述预规划航线中的突发威胁段航线；In an embodiment, during the flight of the attack drone to the attackable area, when a threat signal is detected, a sudden threat segment route in the pre-planned route is determined;
根据所述突发威胁段航线以及实时接收到的所述地面测控模块监测到的信息进行邻域搜索，确定更新航线；According to the route of the sudden threat segment and the information monitored by the ground measurement and control module received in real time, a neighborhood search is performed to determine an updated route;
采用航迹代价评估模型对所述更新航线进行评估，确定最优航线；Evaluate the updated route by using the track cost evaluation model to determine the optimal route;
根据所述最优航线修正所述突发威胁段航线，获得更新后的航线；Correct the route of the sudden threat segment according to the optimal route, and obtain the updated route;
按照上述更新航线的方式反复修正所述预规划航线，直至飞行到所述可攻击区域。The pre-planned route is revised repeatedly according to the above-mentioned way of updating the route until the flight reaches the attackable area.
在一实施例中，所述航迹代价评估模型为：In one embodiment, the track cost evaluation model is:
其中，所述C表示航线代价值，所述li表示第i段航线的长度，所述hi表示所述攻击无人机的海拔高度，所述fTAi表示第i段航线的威胁指数，所述w1、所述w2和所述w3分别表示加权系数。Wherein, the C represents the route cost value, the li represents the length of thei -th route, the hi represents the altitude of the attack drone, and the fTAi represents the threat index of the i-th route, The w1 , the w2 and the w3 represent weighting coefficients, respectively.
在一实施例中，所述攻击无人机飞行到所述可攻击区域中后，获取所述目标无人机的态势信息；In one embodiment, after the attacking drone flies into the attackable area, the situation information of the target drone is acquired;
根据所述目标无人机的态势信息以及自身的态势信息进行分析，获得分析结果；Analyze according to the situation information of the target UAV and its own situation information, and obtain the analysis result;
根据所述分析结果，获得攻击航迹；According to the analysis result, obtain the attack track;
根据所述攻击航迹以及自身的机动飞行动作信息，获得最优自主攻击轨迹。According to the attack track and its own maneuvering flight action information, the optimal autonomous attack track is obtained.
在一实施例中，所述攻击无人机，还用于对所述目标无人机的毁伤情况进行评估，获得评估结果，并根据所述评估结果确定攻击行为。In one embodiment, the attacking UAV is further configured to evaluate the damage of the target UAV, obtain an evaluation result, and determine the attack behavior according to the evaluation result.
在一实施例中，当所述评估结果大于或等于第一阈值时，则再次飞行至可攻击区域后对所述目标无人机进行再次攻击；In one embodiment, when the evaluation result is greater than or equal to the first threshold, the target drone is re-attacked after flying to the attackable area again;
当所述评估结果为小于所述第一阈值时，则启动自毁撞击程序，撞击所述目标无人机。When the evaluation result is less than the first threshold, a self-destruction impact procedure is started to impact the target UAV.
在一实施例中，当所述攻击无人机启动自毁撞击程序后，通过所述攻击无人机上设置的机器视觉拍摄的所述目标无人机的图像进行分析，获得所述目标无人机的当前速度以及位置；In one embodiment, after the attack drone starts the self-destruction impact program, the image of the target drone captured by the machine vision set on the attack drone is analyzed to obtain the target drone. the current speed and position of the machine;
根据所述目标无人机的当前速度以及位置，预测下一时刻的目标无人机的速度以及位置；According to the current speed and position of the target drone, predict the speed and position of the target drone at the next moment;
根据预测的下一时刻的目标无人机的速度以及位置对所述目标无人机进行跟踪延迟补偿，获得撞击时刻目标无人机的位置；Perform tracking delay compensation on the target UAV according to the predicted speed and position of the target UAV at the next moment, and obtain the position of the target UAV at the moment of impact;
根据所述撞击时刻目标无人机的位置撞击目标无人机。The target drone is hit according to the position of the target drone at the impact moment.
在一实施例中，当所述目标无人机的位置未发生改变时，根据所述预规划航线进行重规划飞行至可攻击区域后对所述目标无人机进行攻击。In one embodiment, when the position of the target UAV has not changed, the target UAV is attacked after replanning the flight to an attackable area according to the pre-planned route.
本发明实施例与现有技术相比存在的有益效果是：通过地面测控模块根据接收到的目标无人机的位置信息对攻击无人机的航线进行规划，获得预规划航线，然后攻击无人机根据接收到的目标无人机的位置信息检测目标无人机的位置是否发生改变，当所述目标无人机的位置发生改变时，攻击无人机根据所述目标无人机的位置改变信息、所述攻击无人机实时探测到的信息以及实时接收到的所述地面测控模块监测到的信息对所述预规划航线进行重规划，并按照重规划的航线飞行至可攻击区域后对所述目标无人机进行攻击，从而可以实现当目标无人机的位置发生改变时仍然可以对目标无人机进行攻击，可以解决现有技术中当无人机的位置发生变化后则可能导致跟踪失败或者摧毁失败的问题。Compared with the prior art, the embodiment of the present invention has the beneficial effect of planning the route of attacking the UAV according to the received position information of the target UAV through the ground measurement and control module, obtaining the pre-planned route, and then attacking the UAV. The drone detects whether the position of the target drone changes according to the received position information of the target drone. When the position of the target drone changes, the attack drone changes according to the position of the target drone. information, the information detected by the attacking drone in real time, and the information monitored by the ground measurement and control module received in real time to re-plan the pre-planned route, and fly to the attackable area according to the re-planned route. The target drone is attacked, so that when the position of the target drone changes, the target drone can still be attacked, which can solve the problem that in the prior art, when the position of the drone changes, the problem may be caused. Track failures or failures to destroy.
附图说明Description of drawings
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。In order to illustrate the technical solutions in the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only for the present invention. In some embodiments, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without any creative effort.
图1是本发明实施例提供的无人机反制系统的示意图；1 is a schematic diagram of a UAV countermeasure system provided by an embodiment of the present invention;
图2是本发明实施例提供的攻击无人机修正预规划航线的过程的示意图；2 is a schematic diagram of a process for correcting a pre-planned route for an attack drone provided by an embodiment of the present invention;
图3是本发明另一实施例提供的无人机反制系统的示意图。FIG. 3 is a schematic diagram of a UAV countermeasure system provided by another embodiment of the present invention.
具体实施方式Detailed ways
以下描述中，为了说明而不是为了限定，提出了诸如特定系统结构、技术之类的具体细节，以便透彻理解本发明实施例。然而，本领域的技术人员应当清楚，在没有这些具体细节的其它实施例中也可以实现本发明。在其它情况中，省略对众所周知的系统、装置、电路以及方法的详细说明，以免不必要的细节妨碍本发明的描述。In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are set forth in order to provide a thorough understanding of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
为了说明本发明所述的技术方案，下面通过具体实施例来进行说明。In order to illustrate the technical solutions of the present invention, the following specific embodiments are used for description.
图1为本发明实施例提供的一种无人机反制系统的示意图，详述如下。FIG. 1 is a schematic diagram of a UAV countermeasure system provided by an embodiment of the present invention, which is described in detail as follows.
如图1所示，一种无人机反制系统，可以包括：探测模块101、地面测控模块102以及攻击无人机103；As shown in FIG. 1, a UAV countermeasure system may include: a detection module 101, a ground measurement and control module 102, and an attack UAV 103;
所述探测模块101，用于对获取的地面探测数据以及空中探测数据进行数据融合，根据融合后的数据对空中飞行的无人机进行目标识别以及目标跟踪，获取目标无人机的位置信息，并将所述目标无人机的位置信息发送给所述地面测控模块102；The detection module 101 is used to perform data fusion on the acquired ground detection data and aerial detection data, perform target identification and target tracking on the drone flying in the air according to the fused data, and obtain the position information of the target drone, and sending the position information of the target UAV to the ground measurement and control module 102;
所述地面测控模块102，用于根据接收到的所述目标无人机的位置信息对攻击无人机的航线进行规划，获得预规划航线；以及将所述预规划航线和所述目标无人机的位置信息上传至所述攻击无人机103；The ground measurement and control module 102 is used to plan the route of the attacking drone according to the received position information of the target drone, and obtain a pre-planned route; and combine the pre-planned route and the target unmanned aerial vehicle. The location information of the drone is uploaded to the attack drone 103;
所述攻击无人机103，用于接收所述预规划航线和所述目标无人机的位置信息，根据所述目标无人机的位置信息检测目标无人机的位置是否发生改变，当所述目标无人机的位置发生改变时，根据所述目标无人机的位置改变信息、所述攻击无人机实时探测到的信息以及实时接收到的所述地面测控模块监测到的信息对所述预规划航线进行重规划，并按照重规划的航线飞行至可攻击区域后对所述目标无人机进行攻击。The attacking UAV 103 is used to receive the pre-planned route and the position information of the target UAV, and detect whether the position of the target UAV changes according to the position information of the target UAV. When the position of the target UAV changes, according to the position change information of the target UAV, the information detected in real time by the attacking UAV, and the information monitored by the ground measurement and control module received in real time The pre-planned route is re-planned, and the target UAV is attacked after flying to the attackable area according to the re-planned route.
当所述目标无人机的位置未发生改变时，根据所述预规划航线进行重规划飞行至可攻击区域后对所述目标无人机进行攻击。When the position of the target UAV has not changed, the target UAV is attacked after replanning the flight to an attackable area according to the pre-planned route.
上述无人机反制系统，通过地面测控模块根据接收到的所述目标无人机的位置信息对攻击无人机的航线进行规划，获得预规划航线，然后攻击无人机根据接收到的目标无人机的位置信息检测目标无人机的位置是否发生改变，当所述目标无人机的位置发生改变时，根据所述目标无人机的位置改变信息、所述攻击无人机实时探测到的信息以及实时接收到的所述地面测控模块监测到的信息对所述预规划航线进行重规划，并按照重规划的航线飞行至可攻击区域后对所述目标无人机进行攻击，从而可以实现当目标无人机的位置发生改变时仍然可以对目标无人机进行攻击，可以解决现有技术中当无人机的位置发生变化后则可能导致跟踪失败或者摧毁失败的问题。The above-mentioned UAV countermeasure system plans the route of the attacking UAV according to the received position information of the target UAV through the ground measurement and control module, obtains the pre-planned route, and then attacks the UAV according to the received target. The position information of the UAV detects whether the position of the target UAV has changed. When the position of the target UAV changes, according to the position change information of the target UAV, the attack UAV detects in real time. The information received and the information monitored by the ground measurement and control module received in real time are re-planned to the pre-planned route, and the target UAV is attacked after flying to the attackable area according to the re-planned route, thereby It can be realized that when the position of the target UAV changes, the target UAV can still be attacked, which can solve the problem that the tracking failure or the destruction failure may be caused when the position of the UAV changes in the prior art.
实时准确识别目标和跟踪目标并获取目标状态信息是实现对“低慢小”无人机精确打击的首要环节。“低慢小”无人机是指飞行高度低(通常50-1000米)、飞行速度慢(小于200公里/小时)、雷达反射面积小(小于2平方米)的无人驾驶飞机。“低慢小”无人机具有起降灵活、携带操作容易、成本低廉、机动性强、隐蔽性好、发现处置难、作战伤亡小等特点，特别是一些商用的无人机，技术相对成熟，易于获取和改造，危害相对较大。“低慢小”无人机工作特点包括：飞行高度低，航线不固定；起降简单，突防能力强；反射面积小，雷达探测难；飞行速度慢，隐藏杂波中。“低慢小”无人机的这些特性决定了对其进行防御、打击和反制控制难度较大。Accurately identifying and tracking targets in real time and obtaining target status information are the primary steps to achieve precise strikes against "low-slow-small" UAVs. "Low, slow and small" UAVs refer to UAVs with low flight altitude (usually 50-1000 meters), slow flight speed (less than 200 km/h), and small radar reflection area (less than 2 square meters). "Low, slow and small" UAVs have the characteristics of flexible take-off and landing, easy carrying and operation, low cost, strong maneuverability, good concealment, difficult discovery and disposal, and small combat casualties, especially some commercial UAVs, the technology is relatively mature , easy to obtain and transform, and relatively harmful. The working characteristics of "low, slow and small" UAVs include: low flight altitude and unfixed route; simple take-off and landing, strong penetration ability; small reflection area, difficult to detect by radar; slow flight speed, hidden in clutter. These characteristics of "low, slow and small" UAVs make it difficult to defend, strike and counter control them.
在本实施例中，如图3所示，探测模块101可以包括空中探测子模块1011和地面探测子模块1012，可以采用空中探测子模块1011以及地面探测子模块1012协同探测的方式，通过雷达探测设备搜索远距离的空中目标，发现目标无人机后引导光电探测设备实现全景周视搜索，再根据雷达探测设备以及光电探测设备等多个设备获取的探测信息进行误差校正、时间统一、特征提取、目标识别以及目标跟踪等处理，完成对“低慢小”无人机目标的识别与跟踪。In this embodiment, as shown in FIG. 3 , the detection module 101 may include an air detection sub-module 1011 and a ground detection sub-module 1012 , and the air detection sub-module 1011 and the ground detection sub-module 1012 may be used for cooperative detection to detect by radar. The equipment searches for long-distance aerial targets, and guides the photoelectric detection equipment to realize a panoramic search after finding the target UAV, and then performs error correction, time unification, and feature extraction according to the detection information obtained by radar detection equipment and photoelectric detection equipment. , target recognition and target tracking, etc., to complete the identification and tracking of "low, slow and small" UAV targets.
可选的，如图3所示空中探测子模块1011可以获取到无人机的空中探测数据，地面探测子模块1012可以获取到无人机的地面探测数据，空中探测数据和地面探测数据对无人机的位置描述的角度不同，因此为了获得精确的无人机的位置信息，可以对空中探测数据和地面探测数据进行数据融合，对融合后的数据进行处理，可以获得更精确的目标无人机的位置信息。Optionally, as shown in FIG. 3, the aerial detection sub-module 1011 can acquire the aerial detection data of the drone, and the ground detection sub-module 1012 can acquire the ground detection data of the drone. The angle of the position description of the man and the machine is different, so in order to obtain the precise position information of the UAV, the air detection data and the ground detection data can be data fused, and the fused data can be processed to obtain a more accurate target unmanned aerial vehicle. location information of the machine.
可选的，在无人机反制系统中包括的探测模块101可以完成对“低慢小”无人机目标的识别与跟踪。探测模块101获取目标无人机的位置信息，可以包括：首先建立目标模型和目标数据库，然后在拍摄的视频图像中识别出感兴趣的目标并检测目标位置，对目标当前状态和下一状态进行估计和预测，根据预测结果调整跟踪机构的状态，从而完成对感兴趣目标的实时识别与跟踪。Optionally, the detection module 101 included in the UAV countermeasure system can complete the identification and tracking of "low, slow and small" UAV targets. The detection module 101 obtains the position information of the target UAV, which may include: firstly establishing a target model and a target database, then identifying the target of interest in the captured video image and detecting the target position, and performing the current state and the next state of the target. Estimate and forecast, adjust the status of the tracking mechanism according to the forecast result, so as to complete the real-time identification and tracking of the target of interest.
可选的，目标识别可以包括图像分割、图像特征提取和目标特征匹配等几个部分。视频传感器对侦察区域成像后得到视频帧，把视频帧分割成若干个子图像，对各个子图像进行特征提取，并和数据库中的目标特征进行匹配，匹配成功即完成目标识别，否则继续重复分割视频以及进行特征匹配等过程，构成目标识别的循环。Optionally, target recognition may include several parts such as image segmentation, image feature extraction and target feature matching. The video sensor obtains a video frame after imaging the reconnaissance area, divides the video frame into several sub-images, extracts the features of each sub-image, and matches with the target features in the database. If the matching is successful, the target recognition is completed, otherwise, the video continues to be segmented repeatedly. And the process of feature matching, etc., constitutes a cycle of target recognition.
目标跟踪可以包括目标识别、目标状态估计、目标预测和机构调整等几个部分。目标识别完成后还需要检测目标在图像中的位置，并对目标的当前状态进行估计，其中目标的当前状态可以包括经纬度、姿态、速度等，同时对目标下一时刻的状态进行预测。根据预测结果对无人机的飞行轨迹和姿态进行调整，使得目标保持在视频图像的中心。调整之后在预测的位置附近重新检测目标，完成一个目标跟踪循环。Target tracking can include several parts such as target recognition, target state estimation, target prediction and mechanism adjustment. After the target recognition is completed, it is necessary to detect the position of the target in the image, and estimate the current state of the target. Adjust the flight trajectory and attitude of the UAV according to the prediction results, so that the target remains in the center of the video image. After the adjustment, the target is re-detected near the predicted position to complete a target tracking loop.
可选的，在目标识别阶段，对图像分割可以采用对图像进行超像素分割的方式。由于光照、噪声、视角等因素的影响，图像分割技术很难把目标完整地从背景分离出来。超像素可以认为是图像的最小分割单元，把图像分割为以超像素为单元的多个子图，然后对超像素单元进行组合可以得到完整的目标图像。Optionally, in the target recognition stage, the image segmentation can be performed by performing superpixel segmentation on the image. Due to the influence of factors such as illumination, noise, and viewing angle, it is difficult for image segmentation technology to completely separate the target from the background. A superpixel can be considered as the smallest segmentation unit of an image. The image is divided into multiple sub-images with superpixels as a unit, and then a complete target image can be obtained by combining the superpixel units.
可选的，对图像分割完成后，对图像进行特征提取，可以采用超像素单元的形状进行描述的方式。用于图像目标识别的特征应具有光照、尺度、旋转、倾斜不变性。面积、周长等具备光照和旋转不变性，但是不具备尺度和倾斜不变性。超像素形状和超像素单元具有很强的对应关系，因此超像素形状可以作为超像素单元的特征，同时超像素的形状可以组合出目标的形状。因此对超像素单元的形状进行描述，使采用超像素单元描述获得的形状具有光照、尺度、旋转、倾斜不变性，这样就完成了超像素特征的提取。Optionally, after the image segmentation is completed, feature extraction is performed on the image, which may be described by the shape of the superpixel unit. Features used for image object recognition should be invariant to illumination, scale, rotation, and tilt. Area, perimeter, etc. have illumination and rotation invariance, but not scale and tilt invariance. The superpixel shape and the superpixel unit have a strong correspondence, so the superpixel shape can be used as the feature of the superpixel unit, and the shape of the superpixel can combine the shape of the target. Therefore, the shape of the superpixel unit is described, so that the shape obtained by using the superpixel unit description has the invariance of illumination, scale, rotation and tilt, thus completing the extraction of superpixel features.
可选的，提取出图像特征后，可与目标特征进行匹配，以便判断提取出的图像特征是否为目标无人机的特征。由于超像素单元是最小的图像分割单元，而目标的形状在各个图像中是基本不变的，因此即使各个图像由于光照等分割后的超像素单元不同，它们也可以分别组合出目标的形状。因此，当图像的超像素单元可以和目标的超像素单元匹配时，可以判定图像中含有目标。如果超像素单元不能匹配，还可以通过机器学习的方法找到超像素单元的组合作为新的目标特征。Optionally, after the image features are extracted, they can be matched with the target features, so as to determine whether the extracted image features are the features of the target UAV. Since the superpixel unit is the smallest image segmentation unit, and the shape of the target is basically unchanged in each image, even if the superpixel unit of each image is different due to illumination, they can combine the shape of the target separately. Therefore, when the superpixel unit of the image can be matched with the superpixel unit of the target, it can be determined that the image contains the target. If the superpixel units cannot be matched, the combination of superpixel units can also be found as new target features by machine learning methods.
可选的，在对目标跟踪阶段，可以将目标跟踪转化在贝叶斯滤波框架下的推理目标状态后验概率密度的过程。利用无参概率密度估计的方法，通过一个迭代过程来优化目标模板和候选区域之间的距离，从而减小目标搜索区域。根据具体情况来判断是启用均值漂移和卡尔曼滤波算法还是进行线性预测，通过这种交互的方式来进行目标跟踪。针对目标轨迹跟踪控制问题，可以采用一种基于隐马尔科夫的运动目标轨迹跟踪控制算法，即根据飞行区域内的地理位置信息和目标移动速度等信息建立隐马尔科夫模型，然后利用Viterbi解码算法对最佳路径和最佳状态概率进行最优化求解，实现对运动目标轨迹的实时跟踪。Optionally, in the target tracking stage, the target tracking can be transformed into a process of inferring the target state posterior probability density under the framework of Bayesian filtering. Using the method of parameter-free probability density estimation, the distance between the target template and the candidate region is optimized through an iterative process, thereby reducing the target search region. According to the specific situation, it is judged whether to enable the mean shift and Kalman filtering algorithm or perform linear prediction, and perform target tracking through this interaction. Aiming at the target trajectory tracking control problem, a hidden Markov-based moving target trajectory tracking control algorithm can be used, that is, a hidden Markov model is established according to the geographic location information and target moving speed in the flight area, and then the Viterbi decoding is used. The algorithm optimizes the optimal path and the optimal state probability, and realizes the real-time tracking of the moving target trajectory.
为了降低在下一帧图像中检测目标的计算工作量，需要事先对运动目标的运动状态进行估计，以得到下一帧图像中目标识别的大致范围。可以采用贝叶斯滤波方法进行目标状态预测，贝叶斯滤波方法是基于概率论的统计方法，由于图像像素是离散的，其概率密度的表示往往也是离散的。目标状态预测往往和离散概率的极值求解相关联，模糊理论可以把离散问题模糊化、连续化，提高离散概率极值求解的准确性，同时提高目标状态预测的准确性。In order to reduce the computational workload of detecting the target in the next frame of image, it is necessary to estimate the motion state of the moving target in advance to obtain the approximate range of target recognition in the next frame of image. The Bayesian filtering method can be used to predict the target state. The Bayesian filtering method is a statistical method based on probability theory. Since the image pixels are discrete, the representation of the probability density is often discrete. The prediction of target state is often related to the solution of the extreme value of discrete probability. Fuzzy theory can fuzzify and continuousize discrete problems, improve the accuracy of solution of extreme value of discrete probability, and improve the accuracy of target state prediction.
飞行预规划和实时规划能力是攻击无人机实现对“低慢小”无人机跟踪摧毁所必需的，无人机反制系统可根据探测到的态势变化，实时或近实时地规划、修改决策系统的任务目标，从而自动生成完成任务的可行飞行轨迹，根据所形成的轨迹及飞机当前的状态产生制导和调度指令，控制飞机精确跟踪所生成的轨迹，完成对目标的跟踪。Flight pre-planning and real-time planning capabilities are necessary for attack UAVs to track and destroy "low, slow and small" UAVs. The UAV countermeasure system can plan and modify in real time or near real time according to the detected situation changes. The task target of the decision-making system, so as to automatically generate a feasible flight trajectory to complete the task, generate guidance and scheduling instructions according to the formed trajectory and the current state of the aircraft, and control the aircraft to accurately track the generated trajectory to complete the tracking of the target.
可选的，如图3所示采用探测模块对空中飞行的无人机进行目标识别以及目标跟踪后可以获取目标无人机的位置信息，将所述目标无人机的位置信息发送给地面测控模块，以便地面测控模块进一步规划接近目标无人机的航线，并采用攻击无人机实现攻击。Optionally, as shown in FIG. 3, the position information of the target UAV can be obtained after the detection module is used to identify and track the target of the UAV flying in the air, and the position information of the target UAV can be sent to the ground measurement and control. module, so that the ground measurement and control module can further plan the route close to the target UAV, and use the attack UAV to achieve the attack.
无人机航迹规划是为圆满完成任务而作的飞行计划，是任务规划的关键技术之一，任务规划的实现均由航迹规划来完成。考虑到目标无人机的动态随机性，要求不仅具有静态航迹预规划的能力，还需具有实时修正航迹的能力，以便使无人机能够实时跟踪目标，顺利完成预定任务。根据航迹规划的执行步骤，可以将一个完整的飞行规划过程划分为不同的等级：首先是任务前规划，这一级规划中所有的信息都是静态的，静态参考预规划航迹在确定战场环境下，攻击无人机起飞前在地面控制站上进行的规划。可选的，地面测控模块根据探测模块发送的目标无人机的位置信息进行规划，可以获得预规划航线。UAV trajectory planning is a flight plan for the successful completion of the mission, and it is one of the key technologies of mission planning. The realization of mission planning is completed by trajectory planning. Considering the dynamic randomness of the target UAV, it is required not only to have the ability to pre-plan the static trajectory, but also to have the ability to correct the trajectory in real time, so that the UAV can track the target in real time and successfully complete the predetermined task. According to the execution steps of track planning, a complete flight planning process can be divided into different levels: the first is pre-mission planning, all information in this level of planning is static, and the static reference pre-planned track is used to determine the battlefield. environment, planning at the ground control station before the attack drone takes off. Optionally, the ground measurement and control module performs planning according to the position information of the target UAV sent by the detection module, and can obtain a pre-planned route.
可选的，地面测控模块获得预规划航线，可以包括：根据接收到的目标无人机的位置信息以及飞行约束信息对攻击无人机的航线进行规划，获得预规划航线；以及采用航迹代价评估模型对所述预规划航线进行评估，确定最优预规划航线。Optionally, obtaining the pre-planned route by the ground measurement and control module may include: planning the route of the attacking drone according to the received position information and flight constraint information of the target drone to obtain the pre-planned route; and using the track cost The evaluation model evaluates the pre-planned route to determine the optimal pre-planned route.
可选的，所述飞行约束信息包括无人机本体性能约束信息和外部环境约束信息。无人机本体性能约束主要与无人机本体的结构设计及动力性能有关，无人机本体性能约束信息包括最大航程、最大爬升角、最小步长以及最小转弯半径中的至少一种。外部环境约束信息包括大气威胁、雷达威胁、导弹威胁、高炮威胁及地形碰撞威胁中的至少一种。Optionally, the flight constraint information includes UAV body performance constraint information and external environment constraint information. The performance constraints of the UAV body are mainly related to the structural design and dynamic performance of the UAV body. The UAV body performance constraint information includes at least one of the maximum range, the maximum climb angle, the minimum step length and the minimum turning radius. The external environment constraint information includes at least one of atmospheric threats, radar threats, missile threats, anti-aircraft artillery threats, and terrain collision threats.
可选的，航迹评价是航迹规划中一个重要组成部分。需要综合考虑影响航迹性能的各项因素，对各项指标进行量化和计算，确定影响航迹综合性能的指标权重，完成综合指标的计算、航迹的选优等工作。特别是在对抗性环境中，航迹性能的好坏直接影响到无人机完成任务的能力。Optionally, track evaluation is an important part of track planning. It is necessary to comprehensively consider various factors affecting the track performance, quantify and calculate each index, determine the weight of the index affecting the comprehensive performance of the track, and complete the calculation of the comprehensive index and the selection of the track. Especially in the adversarial environment, the quality of the track performance directly affects the ability of the UAV to complete the mission.
航迹评价是一个由相互关联、相互制约的众多因素构成的复杂决策系统。为了表征航迹的综合性能，需要将各方面的影响因素按照某种标准转化为可直接比较的无量纲值，然后再确定各个单项指标在综合指标中的权重，最后就得到一个表征航迹综合指标的无量纲值。航迹的评价实质上就是求解每条航迹的综合表征值，从而选择综合表征值最优的航迹。所述航迹代价评估模型可以为：Track evaluation is a complex decision-making system composed of many interrelated and mutually restricting factors. In order to characterize the comprehensive performance of the track, it is necessary to convert the influencing factors of various aspects into dimensionless values that can be directly compared according to a certain standard, and then determine the weight of each individual index in the comprehensive index, and finally obtain a comprehensive track that characterizes the track. The dimensionless value of the indicator. The evaluation of the track is essentially to solve the comprehensive characterization value of each track, so as to select the track with the best comprehensive characterization value. The track cost evaluation model can be:
其中，所述C表示航线代价值，所述li表示第i段航线的长度，li通过缩短航迹的总长度，减少无人机在敌控区域的飞行时间，一方面降低无人机的危险系数，另一方面也可节省油耗；所述hi表示所述攻击无人机的海拔高度，hi通过降低无人机的高度，利用地形的遮挡作用和地面杂波来达到隐蔽的目的，以降低被敌方雷达发现并被地面防御系统摧毁的概率；所述fTAi表示第i段航线的威胁指数，fTAi限制无人机不要与已知的地面威胁距离太近，使得无人机尽量通过威胁较小的区域飞行；所述w1、所述w2和所述w3分别表示加权系数。Among them, the C represents the cost value of the route, the li represents the length of thei -th route, and li reduces the total length of the track to reduce the flight time of the UAV in the enemy-controlled area, and on the one hand, reduces the UAV’s flight time. On the other hand, it can also save fuel consumption; thehi represents the altitude of the attacking UAV,hi reduces the height of the UAV, and uses the occlusion effect of the terrain and ground clutter to achieve a concealed The purpose is to reduce the probability of being detected by the enemy radar and destroyed by the ground defense system; the fTAi represents the threat index of the i-th route, and fTAi restricts the UAV not to be too close to the known ground threat, so that no The man-machine flies through areas with less threat as far as possible; the w1 , the w2 and the w3 respectively represent the weighting coefficients.
通常威胁存在一定的作用范围，无人机预规划航线应尽可能规避威胁，即绕过这些区域。这些威胁可能不断变化，事先很难获得有关规划空间中威胁的准确个数，以及每个威胁的类型、位置、覆盖范围、威胁强度等信息。此外，即使是同一威胁源，对无人机的威胁程度还会因为所接收到预警信号的不同而变化。因此攻击无人机在飞行过程中，还需要实时探测威胁信号，根据不断获得的威胁信息，确定突发威胁段航线，并反复修正预规划航线，直至最终达到可攻击区域。Usually the threat has a certain scope of action, and the pre-planned route of the UAV should avoid the threat as much as possible, that is, bypass these areas. These threats can be constantly changing, and it is difficult to obtain in advance information about the exact number of threats in the planning space, as well as the type, location, coverage, threat intensity, etc. of each threat. In addition, even for the same threat source, the level of threat to UAVs will vary depending on the early warning signals received. Therefore, during the flight of the attack drone, it is also necessary to detect threat signals in real time, determine the route of the sudden threat segment according to the continuously obtained threat information, and repeatedly modify the pre-planned route until it finally reaches the attackable area.
可选的，如图2所示，所述攻击无人机从起飞到飞行至所述可攻击区域的过程中，当探测到威胁信号时，攻击无人机修正预规划航线的过程可以包括以下步骤。Optionally, as shown in FIG. 2 , during the process of the attack drone from taking off to flying to the attackable area, when a threat signal is detected, the process of correcting the pre-planned route by the attack drone may include the following: step.
步骤201，当探测到威胁信号时，确定所述预规划航线中的突发威胁段航线。Step 201, when a threat signal is detected, determine a sudden threat segment route in the pre-planned route.
步骤202，根据所述突发威胁段航线以及实时接收到的所述地面测控模块监测到的信息进行邻域搜索，确定更新航线。In step 202, a neighborhood search is performed according to the route of the sudden threat segment and the information monitored by the ground measurement and control module received in real time, and an updated route is determined.
由于威胁具有突发性，要求新生成的航迹算法必须实时、高效，以便规避威胁，因此可以根据蜂群算法具有邻域搜索的特性，以突发威胁段作为引领蜂航迹，采蜜蜂及跟随蜂只需要对参考航迹的突发威胁段进行邻域搜索，而无需对其它航迹段搜索，从而可以节省搜索时间，快速确定新航线。Due to the sudden nature of the threat, it is required that the newly generated track algorithm must be real-time and efficient in order to avoid the threat. Therefore, according to the characteristics of the neighborhood search of the bee colony algorithm, the sudden threat segment is used as the leading bee track, and the bees and the bees are collected. The follower bee only needs to perform a neighborhood search on the sudden threat segment of the reference track, without searching for other track segments, which can save search time and quickly determine a new route.
可选的，地面测控模块可以实时对攻击无人机的飞行状态以及飞行环境进行测控，并将测控到的信息实时发送给攻击无人机，以便攻击无人机进行准确的航线修正。Optionally, the ground measurement and control module can measure and control the flight status and flight environment of the attacking drone in real time, and send the measured and controlled information to the attacking drone in real time, so that the attacking drone can perform accurate route correction.
步骤203，采用航迹代价评估模型对所述更新航线进行评估，确定最优航线。Step 203, using a track cost evaluation model to evaluate the updated route to determine the optimal route.
可选的，所述航迹代价评估模型可以为：Optionally, the track cost evaluation model may be:
当C最小时，获得的航线为最优。When C is the smallest, the obtained route is the best.
步骤204，根据所述最优航线修正所述突发威胁段航线，获得更新后的航线。Step 204, correcting the route of the sudden threat segment according to the optimal route to obtain an updated route.
按照上述更新航线的方式反复修正所述预规划航线，直至飞行到所述可攻击区域。The pre-planned route is revised repeatedly according to the above-mentioned way of updating the route until the flight reaches the attackable area.
攻击无人机飞行到所述可攻击区域中后，锁定目标无人机，获取所述目标无人机的态势信息。根据所述目标无人机的态势信息以及自身的态势信息进行分析，获得分析结果，即攻击无人就进行态势评估以及战术决策，获得决策结果。然后根据所述分析结果，获得攻击航迹，即将决策结果输入到拟攻击线路计算系统中，经过计算得出适合攻击无人机的攻击航迹。然后根据所述攻击航迹以及自身的机动飞行动作信息，获得最优自主攻击轨迹。攻击无人机进入可攻击区域后快速控制攻击无人机上的火控系统锁定目标并发射武器。After the attack drone flies into the attackable area, the target drone is locked to obtain situation information of the target drone. According to the situational information of the target UAV and its own situational information, the analysis result is obtained, that is, the situational assessment and tactical decision-making are carried out when attacking the unmanned aerial vehicle, and the decision-making result is obtained. Then, according to the analysis result, the attack track is obtained, that is, the decision result is input into the calculation system of the line to be attacked, and the attack track suitable for attacking the UAV is obtained through calculation. Then, the optimal autonomous attack trajectory is obtained according to the attack trajectory and its own maneuvering flight action information. After the attack drone enters the attackable area, quickly control the fire control system on the attack drone to lock the target and launch the weapon.
发射完毕后，所述攻击无人机通过机载侦察设备对所述目标无人机的毁伤情况进行评估，获得评估结果，并根据所述评估结果确定攻击行为。After the launch, the attacking UAV evaluates the damage of the target UAV through the airborne reconnaissance equipment, obtains the evaluation result, and determines the attack behavior according to the evaluation result.
可选的，评估结果可以为目标无人机的毁伤值，第一阈值可以为毁伤阈值，即目标无人机的毁伤值小于毁伤阈值时，说明攻击无人机的武器攻击没有效果，目标无人机的毁伤值大于或等于毁伤阈值时，说明攻击无人机的武器攻击有一定效果，但是还没有达到理想毁伤效果，因此需要进行再次攻击。Optionally, the evaluation result may be the damage value of the target drone, and the first threshold may be the damage threshold, that is, when the damage value of the target drone is less than the damage threshold, it means that the weapon attack against the drone has no effect, and the target has no effect. When the damage value of the man-machine is greater than or equal to the damage threshold, it means that the weapon attack against the drone has a certain effect, but the ideal damage effect has not been achieved, so it is necessary to attack again.
当所述评估结果大于或等于第一阈值时，则再次飞行至可攻击区域后对所述目标无人机进行再次攻击；When the evaluation result is greater than or equal to the first threshold, the target drone is re-attacked after flying to the attackable area again;
当所述评估结果为小于所述第一阈值时，则启动自毁撞击程序，撞击所述目标无人机。When the evaluation result is less than the first threshold, a self-destruction impact procedure is started to impact the target UAV.
可选的呢，当所述攻击无人机启动自毁撞击程序后，通过所述攻击无人机上设置的机器视觉拍摄的所述目标无人机的图像进行分析，获得所述目标无人机的当前速度以及位置；根据所述目标无人机的当前速度以及位置，预测下一时刻的目标无人机的速度以及位置，实现对目标无人机的状态估计，根据预测的下一时刻的目标无人机的速度以及位置对所述目标无人机进行跟踪延迟补偿，获得撞击时刻目标无人机的位置；根据所述撞击时刻目标无人机的位置撞击目标无人机。Optionally, after the attack drone starts the self-destruction impact program, the image of the target drone captured by the machine vision set on the attack drone is analyzed to obtain the target drone. According to the current speed and position of the target UAV, predict the speed and position of the target UAV at the next moment, and realize the state estimation of the target UAV, according to the predicted speed and position of the target UAV at the next moment. The speed and position of the target UAV perform tracking delay compensation on the target UAV to obtain the position of the target UAV at the time of impact; and hit the target UAV according to the position of the target UAV at the time of impact.
上述自毁撞击采用航迹规划控制策略实现机载传感器对动态目标的连续覆盖，这种方法是通过使用自适应估计器对目标的速度进行快速地估计，并预测目标的位置，再根据当前时刻无人机的位置、姿态信息来预测下一个时刻的控制指令，进而实现对目标跟踪延迟的补偿，从而可以准确预测目标无人机的位置，进行准确有效地撞击。The above self-destruction collision adopts the trajectory planning control strategy to realize the continuous coverage of the dynamic target by the airborne sensors. This method uses the adaptive estimator to quickly estimate the speed of the target and predict the position of the target, and then according to the current time The position and attitude information of the UAV can be used to predict the control command at the next moment, so as to realize the compensation for the target tracking delay, so that the position of the target UAV can be accurately predicted and the collision can be carried out accurately and effectively.
上述无人机反制系统，通过地面测控模块根据目标无人机的位置信息规划的预规划航线，攻击无人机在目标无人机的位置未发生改变时根据预规划航线接近目标无人机并进行攻击，在目标无人机的位置发生改变时，根据检测到的实时威胁、自身态势以及实时接收到的所述地面测控模块监测到的信息等信息实时更新预规划航线，并通过航迹代价评估模型获得最优航线，从而可以根据修正后的航线接近目标无人机并实施攻击行为。另外，在攻击无人机后，还可以根据攻击结果，进行再次攻击或者自毁撞击，并最终达到将目标无人机摧毁的理想效果。The above-mentioned UAV countermeasure system uses the pre-planned route planned by the ground monitoring and control module according to the position information of the target UAV, and the attacking UAV approaches the target UAV according to the pre-planned route when the position of the target UAV has not changed. And attack, when the position of the target UAV changes, the pre-planned route is updated in real time according to the detected real-time threat, its own situation and the information monitored by the ground measurement and control module received in real time, and through the track The cost evaluation model obtains the optimal route, so that the target UAV can be approached and attacked according to the corrected route. In addition, after attacking the drone, it can also attack again or self-destruct according to the attack result, and finally achieve the ideal effect of destroying the target drone.
以上所述实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的精神和范围，均应包含在本发明的保护范围之内。The above-mentioned embodiments are only used to illustrate the technical solutions of the present invention, but not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it can still be used for the foregoing implementations. The technical solutions described in the examples are modified, or some technical features thereof are equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the within the protection scope of the present invention.
| Application Number | Priority Date | Filing Date | Title |
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| CN201910912187.5ACN110597264B (en) | 2019-09-25 | 2019-09-25 | drone countermeasure system |
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| CN201910912187.5ACN110597264B (en) | 2019-09-25 | 2019-09-25 | drone countermeasure system |
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| CN201910912187.5AActiveCN110597264B (en) | 2019-09-25 | 2019-09-25 | drone countermeasure system |
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