技术领域technical field
本发明属于雷达技术领域，涉及一种雷达航迹起始方法，具体涉及一种基于位置信息和多普勒信息的雷达航迹起始方法，可用于目标跟踪。The invention belongs to the technical field of radar and relates to a method for starting a radar track, in particular to a method for starting a radar track based on position information and Doppler information, which can be used for target tracking.
背景技术Background technique
航迹起始是目标跟踪的第一步，它是建立新的档案目标的决策方法，主要包括暂时航迹和航迹确定两个方面，其主要原理是利用观测数据与实际场景数据构造约束条件选取相应的量测向量建立航迹，是目标航迹处理的首要问题，其任务是根据雷达多次的观测数据确定扫描区域中潜在的目标，并给出目标的初始状态估计。航迹起始作为目标跟踪的前提和基础，直接影响着雷达系统的跟踪性能。Track initiation is the first step in target tracking. It is a decision-making method for establishing a new archive target. It mainly includes two aspects: temporary track and track determination. The main principle is to use observation data and actual scene data to construct constraints Selecting the corresponding measurement vector to establish the track is the primary problem of target track processing. Its task is to determine the potential target in the scanning area according to the radar observation data many times, and give the initial state estimation of the target. As the premise and basis of target tracking, track initiation directly affects the tracking performance of the radar system.
按照数据处理方式的不同，航迹起始方法分为两大类：顺序处理技术类和批处理技术类。顺序处理技术的代表方法有直观法和逻辑法。直观法的主要处理思路是，利用最大速度与最大加速度作为约束条件，关联满足该约束条件的量测向量作为有效量测向量，如果连续N次扫描中有效量测向量超过M个，则认为由M个有效量测向量构成的航迹，是目标航迹。逻辑法的主要处理思路是，首先利用最大速度约束等条件形成暂态航迹，然后通过航迹预测和关联波门来筛选目标量测向量，如果连续N次扫描中有效量测向量数目超过M个，则认为由M个有效量测向量构成的航迹是目标航迹，但是由于顺序处理技术利用最大速度约束选取有效量测向量，导致关联区域较大，容易形成虚假航迹，造成航迹起始效率低。逻辑法利用航迹预测与关联波门对目标量测向量进行筛选，剔除了虚假航迹，与用两个简单规则来减少可能起始航迹的直观法相比，提高了航迹起始的概率，有效地提升了航迹起始效率。批处理技术的代表有Hough变换法及其改进方法。Hough变换法的主要处理思路是，将多次扫描的回波数据视做一副图像，通过Hough变换检测图像中是否存在直线元素，以此判断是否存在目标航迹，但是批处理技术利用Hough变换将多次扫描的数据联合处理，尽管可以提供较好的航迹起始性能，但计算量较大，不利于工程应用。According to the different data processing methods, track initiation methods are divided into two categories: sequential processing technology and batch processing technology. Representative methods of sequential processing techniques include intuitive method and logical method. The main processing idea of the intuitive method is to use the maximum velocity and maximum acceleration as constraints, and associate the measurement vectors that meet the constraints as effective measurement vectors. If there are more than M effective measurement vectors in consecutive N scans, it is considered to be The track formed by the M effective measurement vectors is the target track. The main processing idea of the logic method is to first form a transient track by using the maximum speed constraint and other conditions, and then filter the target measurement vector through track prediction and associated gates. If the number of effective measurement vectors in consecutive N scans exceeds M , then it is considered that the track composed of M effective measurement vectors is the target track. However, due to the sequential processing technology using the maximum speed constraint to select effective measurement vectors, the associated area is relatively large, and it is easy to form false tracks, resulting in track Low initial efficiency. The logic method uses track prediction and correlation gate to filter the target measurement vector, and eliminates the false track. Compared with the intuitive method that uses two simple rules to reduce the possible initial track, the probability of track initiation is improved. , which effectively improves the track initiation efficiency. Representatives of batch processing techniques include the Hough transform method and its improved methods. The main processing idea of the Hough transform method is to treat the echo data of multiple scans as an image, and detect whether there are linear elements in the image through the Hough transform to judge whether there is a target track, but the batch processing technology uses the Hough transform Although the joint processing of multiple scanning data can provide better track initiation performance, the calculation amount is large, which is not conducive to engineering applications.
发明内容Contents of the invention
本发明的目的在于克服上述现有技术存在的缺陷，提出了一种基于位置信息和多普勒信息的雷达航迹起始方法，用于解决现有顺序处理技术类的方法中存在的航迹起始效率低的技术问题。The purpose of the present invention is to overcome the defect that the above-mentioned prior art exists, propose a kind of radar track initiation method based on position information and Doppler information, be used to solve the track that exists in the method of existing sequential processing technology class Technical problem with low initial efficiency.
本发明的技术思路是：首先利用航迹头构建距离约束条件，同时利用最大速度构建空间位置约束条件，关联雷达下次扫描中与航迹头处于同一多普勒通道且同时满足距离约束条件和空间位置约束条件的量测向量，然后更新距离约束条件，继续关联，直至所有的量测向量都完成关联操作，最后根据关联结果按照航迹起始准则建立稳定起始航迹。其具体步骤包括如下：The technical idea of the present invention is: firstly use the track head to construct the distance constraint condition, and at the same time use the maximum velocity to construct the spatial position constraint condition, in the next scan of the associated radar, it is in the same Doppler channel as the track head and satisfies the distance constraint condition at the same time and the measurement vectors of the spatial position constraints, and then update the distance constraints, and continue to associate until all the measurement vectors are associated, and finally establish a stable initial trajectory according to the trajectory initiation criteria according to the association results. Its concrete steps include as follows:
基于位置信息和多普勒信息的雷达航迹起始方法，包括如下步骤：The radar track initiation method based on position information and Doppler information comprises the following steps:
(1)计算雷达最大不模糊速度Vf；(1) Calculate the maximum unambiguous velocity Vf of the radar;
(2)将第k-N次扫描中得到的未被已有稳定航迹关联的量测向量集合中第i个量测向量zk-N,i作为航迹头，记该航迹头所在多普勒通道为L，根据航迹头中包含的多普勒测量值fk-N,i，计算航迹头对应的径向速度集合vk-N,i，其中，k是当前雷达扫描的时刻，N是航迹起始的时间窗长；(2) Take the i-th measurement vector zkN,i in the measurement vector set not associated with the existing stable track obtained in the kNth scan as the track head, and record the Doppler channel where the track head is located is L, according to the Doppler measurement value fkN,i contained in the track head, calculate the radial velocity set vkN,i corresponding to the track head, where k is the moment of the current radar scan, N is the starting point of the track The starting time window length;
(3)从航迹头对应的径向速度集合vk-N,i中选取模糊次数为m的径向速度vk-N,i,m；(3) Selecting the radial velocityvkN,i,m whose fuzzy times are m from the radial velocity setvkN,i corresponding to the track head;
(4)设当前径向速度为v＝vk-N,i,m，令l＝k-N，n＝1；(4) Set the current radial velocity as v=vkN,i,m , let l=kN, n=1;
(5)根据当前径向速度v，按照下式计算其对应的距离预测值和距离预测标准差(5) According to the current radial velocity v, calculate the corresponding distance prediction value according to the following formula and distance prediction standard deviation
其中，表示第l次扫描的有效量测向量集合中第il个有效量测向量包含的距离测量值，表示有效量测向量对应的测距精度，表示有效量测向量对应的测速精度，Ts表示对当前波位的下次扫描所需的时间间隔；in, Indicates the ith effective measurement vector in the effective measurement vector set of thelth scan Included distance measurements, Represents the effective measurement vector The corresponding ranging accuracy, Represents the effective measurement vector Corresponding speed measurement accuracy, Ts represents the time interval required for the next scan of the current wave position;
当l＝k-N时，第l次扫描的有效量测向量集合中仅包含zk-N,i；当l＞k-N时，第l次扫描的有效量测向量集合包含以下量测向量：第l次扫描中所有与航迹头关联且位于第L个多普勒通道的量测向量；When l=kN, only zkN,i is included in the effective measurement vector set of the lth scan; when l>kN, the effective measurement vector set of the lth scan contains the following measurement vectors: the lth scan All measurement vectors associated with the track head and located in the L-th Doppler channel in ;
(6)根据步骤(5)中得到的距离预测值和距离预测标准差构建距离约束条件：(6) According to the distance prediction value obtained in step (5) and distance prediction standard deviation Build distance constraints:
其中，g表示约束系数，ρl+n,j表示第l+n次扫描位于第L个多普勒通道的量测向量集合z(l+n)∩L中第j个量测向量z(l+n)∩L,j包含的距离测量值，σρ,l+n,j表示量测向量z(l+n)∩L,j对应的测距精度；Among them, g represents the constraint coefficient, ρ l+n,j represents the jth measurement vector z( l+n)∩L,j contains the distance measurement value, σρ,l+n,j represents the ranging accuracy corresponding to the measurement vector z(l+n)∩L,j ;
(7)设定目标的最大空间速度为Vmax，构建空间位置约束条件：选取量测向量集合z(l+n)∩L中与有效量测向量的得到笛卡尔空间距离小于等于nVmaxTs；(7) Set the maximum space velocity of the target as Vmax , and construct the space position constraints: select the measurement vector set z(l+n)∩L and the effective measurement vector The obtained Cartesian space distance is less than or equal to nVmax Ts ;
(8)判断量测向量集合z(l+n)∩L中是否存在同时满足距离约束条件和空间位置约束条件的量测向量：(8) Determine whether there is a measurement vector that satisfies both the distance constraint and the spatial position constraint in the measurement vector set z(l+n)∩L :
若是，当l+n≠k-1时，将有效量测向量与同时满足两个约束条件的量测向量分别进行关联，并更新当前径向速度v，令n＝1，l＝l+n，并执行步骤(5)；当l+n＝k-1时，将有效量测向量与同时满足两个约束条件的量测向量分别进行关联，并执行步骤(9)；If so, when l+n≠k-1, the effective measurement vector Respectively correlate with the measurement vectors satisfying the two constraints simultaneously, and update the current radial velocity v, make n=1, l=l+n, and execute step (5); when l+n=k-1 , will effectively measure the vector Respectively correlating with the measurement vectors satisfying the two constraint conditions simultaneously, and performing step (9);
若否，当l+n≠k-1时，令n＝n+1，并执行步骤(5)；当l+n＝k-1，执行步骤(9)；If not, when l+n≠k-1, make n=n+1, and perform step (5); when l+n=k-1, perform step (9);
(9)按照航迹起始准则，建立稳定起始航迹；(9) Establish a stable initial trajectory according to the trajectory initiation criteria;
(10)对径向速度集合vk-N,i中的所有径向速度进行遍历，当径向速度集合vk-N,i中的所有径向速度均被遍历，遍历第k-N次扫描中得到的所有未被已有稳定航迹关联的量测向量，得到一条或多条稳定起始航迹。(10) Traversing all the radial velocities in the radial velocity set v kN,i , when all the radial velocities in the radial velocity set vkN,i are traversed, traversing all the unidentified One or more stable initial trajectories are obtained by correlating the measurement vectors with the existing stable trajectories.
本发明与现有技术相比，具有如下优点：Compared with the prior art, the present invention has the following advantages:
本发明由于在判断量测向量的过程中，采用多普勒测量信息构建距离约束条件，同时采用位置信息构建空间约束条件，并关联同时符合距离约束条件和空间约束条件的量测向量，有效地剔除了虚假量测向量，抑制虚假航迹，进而提高了航迹起始的概率，与现有航迹起始技术相比，有效地提升了航迹起始效率。In the process of judging the measurement vector, the present invention uses the Doppler measurement information to construct the distance constraint condition, and uses the position information to construct the space constraint condition at the same time, and associates the measurement vector that meets both the distance constraint condition and the space constraint condition, effectively The false measurement vector is eliminated, the false track is suppressed, and the probability of track initiation is increased. Compared with the existing track initiation technology, the efficiency of track initiation is effectively improved.
附图说明Description of drawings
图1是本发明的实现流程框图；Fig. 1 is the realization flow diagram of the present invention;
图2是本发明与逻辑法虚假航迹概率仿真对比图；Fig. 2 is the simulation contrast figure of false track probability of the present invention and logical method;
图3是本发明与逻辑法虚假航迹平均数量仿真对比图；Fig. 3 is the simulation contrast figure of the average number of false track of the present invention and logic method;
图4是本发明与逻辑法航迹起始概率仿真对比图。Fig. 4 is a comparison diagram of the present invention and the trajectory initial probability simulation of the logic method.
具体实施方式Detailed ways
以下参照附图和实施例，对本发明作进一步详细说明：Below with reference to accompanying drawing and embodiment, the present invention is described in further detail:
参照图1，本发明的实现步骤如下：With reference to Fig. 1, the realization steps of the present invention are as follows:
步骤1，计算雷达最大不模糊速度Vf。Step 1, calculate the radar maximum unambiguous velocity Vf .
计算雷达最大不模糊速度Vf：Calculate the radar maximum unambiguous velocity Vf :
其中，λ表示雷达发射信号波长，fr表示脉冲重复频率。Among them, λ represents the wavelength of the radar emission signal, fr represents the pulse repetition frequency.
步骤2，计算径向速度集合vk-N,i。Step 2, calculate the radial velocity set vkN,i .
根据航迹头zk-N,i中的多普勒频率测量值fk-N,i和最大不模糊速度Vf，计算量测向量zk-N,i对应的径向速度集合vk-N,i，以下所述量测向量均表示未被已有稳定航迹关联的量测向量，且量测向量包含距离测量值、方位角测量值和多普勒测量值：According to the Doppler frequency measurement value fkN,i and the maximum unambiguous velocity Vf in the track head zkN,i , calculate the radial velocity set vkN,i corresponding to the measurement vector z kN, i, as follows The measurement vectors all represent measurement vectors that are not associated with an existing stable track, and the measurement vectors include range measurements, azimuth measurements, and Doppler measurements:
(2.1)计算zk-N,i中多普勒频率测量值fk-N,i对应的径向速度v⊥：(2.1) Calculate the radial velocity v⊥ corresponding to the Doppler frequency measurement value fkN, i in zkN,i :
其中，量测向量zk-N,i表示雷达第k-N次扫描中得到的未被已有稳定航迹关联的量测向量集合中第i个量测向量；Among them, the measurement vector zkN,i represents the i-th measurement vector in the measurement vector set not associated with the existing stable track obtained in the kNth scan of the radar;
(2.2)模糊次数的不同，构建计算径向速度集合vk-N,i：(2.2) Different fuzzy times, build and calculate radial velocity set vkN ,i:
vk-N,i＝{v⊥+2wVf|abs(v⊥+2wVf)≤Vmax,w＝0,±1,±2,...}，vkN,i ＝{v⊥ +2wVf |abs(v⊥ +2wVf )≤Vmax ,w＝0,±1,±2,...}，
其中，|表示条件符号，符号左边是集合元素，右边是元素满足的条件，w表示模糊次数，abs(·)表示取绝对值。Among them, | represents a conditional symbol, the left side of the symbol is the set element, the right side is the condition that the element satisfies, w represents the fuzzy number, and abs(·) represents the absolute value.
步骤3，对当前径向速度初始化，并设置计数器对循环次数进行记录。Step 3, initialize the current radial velocity, and set a counter to record the number of cycles.
(3.1)从航迹头对应的径向速度集合vk-N,i中选取模糊次数为m的径向速度vk-N,i,m(3.1) From the set of radial velocities vkN,i corresponding to the track head, select the radial velocities vkN,i,m with fuzzy times m
(3.2)设当前径向速度为v＝vk-N,i,m；(3.2) Let the current radial velocity be v=vkN, i, m ;
(3.3)设置计数器：令l＝k-N，n＝1。(3.3) Set the counter: let l=k-N, n=1.
步骤4，构建距离约束条件。Step 4, build distance constraints.
(4.1)根据径向速度v，按照下式计算径向速度对应的距离预测值和距离预测标准差(4.1) According to the radial velocity v, calculate the distance prediction value corresponding to the radial velocity according to the following formula and distance prediction standard deviation
其中，表示第l次扫描的有效量测向量集合中第il个有效量测向量包含的距离测量值，表示有效量测向量对应的测距精度，表示有效量测向量对应的测速精度，Ts表示对当前波位的下次扫描所需的时间间隔；in, Indicates the ith effective measurement vector in the effective measurement vector set of thelth scan Included distance measurements, Represents the effective measurement vector The corresponding ranging accuracy, Represents the effective measurement vector Corresponding speed measurement accuracy, Ts represents the time interval required for the next scan of the current wave position;
(4.2)根据步骤(4.1)中得到的距离预测值和距离预测标准差构建距离约束条件：(4.2) According to the distance prediction value obtained in step (4.1) and distance prediction standard deviation Build distance constraints:
其中，g表示约束系数，ρl+n,j表示第l+n次扫描位于第L个多普勒通道的量测向量集合z(l+n)∩L中第j个量测向量z(l+n)∩L,j包含的距离测量值，σρ,l+n,j表示量测向量z(l+n)∩L,j对应的测距精度；Among them, g represents the constraint coefficient, ρ l+n,j represents the jth measurement vector z( l+n)∩L,j contains the distance measurement value, σρ,l+n,j represents the ranging accuracy corresponding to the measurement vector z(l+n)∩L,j ;
步骤5，构建空间位置约束条件。Step 5, constructing spatial location constraints.
设定目标的最大空间速度Vmax，构建空间位置约束条件：选取量测向量集合z(l+n)∩L中与有效量测向量的笛卡尔空间距离小于等于nVmaxTs的量测向量；Set the maximum space velocity Vmax of the target, and construct the space position constraints: select the measurement vector set z(l+n)∩L and the effective measurement vector The measurement vector whose Cartesian space distance is less than or equal to nVmax Ts ;
步骤6，判断是否满足上述约束条件，并分析判断结果。Step 6, judging whether the above constraints are met, and analyzing the judging result.
(6.1)根据步骤4和步骤5所述约束条件，判断量测向量集合z(l+n)∩L中是否存在同时满足距离约束条件和空间位置约束条件的量测向量；(6.1) According to the constraints described in step 4 and step 5, determine whether there is a measurement vector that satisfies both the distance constraint and the spatial position constraint in the measurement vector set z(l+n)∩L ;
(6.2)分析判断结果：(6.2) Analysis and judgment results:
若是，当l+n≠k-1时，将有效量测向量与同时满足两个约束条件的量测向量分别进行关联，并更新当前径向速度v，令n＝1，l＝l+n，并执行步骤4；当l+n＝k-1时，将有效量测向量与同时满足约束条件的量测向量分别进行关联，并执行步骤7；If so, when l+n≠k-1, the effective measurement vector Correlate with the measurement vectors that satisfy the two constraints at the same time, and update the current radial velocity v, set n=1, l=l+n, and perform step 4; when l+n=k-1, set effective measurement vector Associate with the measurement vectors that satisfy the constraints at the same time, and perform step 7;
若否，当l+n≠k-1时，令n＝n+1，并步骤4；当l+n＝k-1时，执行步骤7；If not, when l+n≠k-1, make n=n+1, and step 4; when l+n=k-1, execute step 7;
其中，更新径向速度v按如下步骤进行：Among them, update the radial velocity v according to the following steps:
(6.2a)计算有效量测向量中多普勒频率测量值对应的径向速度vN：(6.2a) Calculate the effective measurement vector Mid-Doppler frequency measurements Corresponding radial velocity vN :
(6.2b)按下式计算有效量测向量中模糊次数为m的径向速度并更新当前径向速度v：(6.2b) Calculate the effective measurement vector according to the following formula Radial velocity with fuzzy number m in and update the current radial velocity v:
步骤7，建立稳定起始航迹。Step 7, establish a stable initial track.
根据步骤6的关联结果，按照航迹起始准则建立稳定起始航迹，航迹起始准则要求当关联结果中被关联的量测向量个数大于等于起始航迹所需的最小量测向量个数时，则将该关联结果转变为稳定起始航迹，否则，删除该关联结果。所述设定航迹起始准则，包括2/2逻辑起始法、2/3逻辑起始法、3/3逻辑起始法和3/4逻辑起始法。According to the association result in step 6, establish a stable initial trajectory according to the trajectory initiation criterion. The trajectory initiation criterion requires that when the number of associated measurement vectors in the association result is greater than or equal to the minimum measurement required for the initial trajectory When the number of vectors is large, the association result is transformed into a stable initial track, otherwise, the association result is deleted. The starting criterion for setting the trajectory includes 2/2 logical starting method, 2/3 logical starting method, 3/3 logical starting method and 3/4 logical starting method.
步骤8，由于目标速度可能出现模糊，遍历径向速度集合。Step 8, traverse the collection of radial velocities due to possible ambiguity of the target velocity.
遍历径向速度集合vk-N,i中的所有径向速度，当径向速度集合vk-N,i中的所有径向速度均被遍历，则执行步骤9；Traversing all the radial velocities in the radial velocity set v kN,i , when all the radial velocities in the radial velocity set vkN,i are traversed, then perform step 9;
步骤9，由于航迹起始是对多目标的检测，可能存在多条航迹，遍历量测向量集合zk-N。In step 9, since the initial track is the detection of multiple targets, there may be multiple tracks, and the set of measurement vectors zkN is traversed.
遍历第k-N次扫描中得到的所有未被已有稳定航迹关联的量测向量。All measurement vectors obtained in the k-N scans that are not associated with existing stable tracks are traversed.
以下结合仿真实验，对本发明的技术效果作进一步说明：Below in conjunction with simulation experiment, technical effect of the present invention is described further:
1.仿真场景：实验采用2D雷达，认为雷达坐落于坐标原点，设载频fc＝1GHz，光速c＝3×108m/s，发射信号带宽B＝2MHz，波束宽度θBeam＝3dB，脉冲宽度τ＝30us，脉冲重复周期Tr＝1ms，雷达发射信号波长λ＝0.3m，脉冲重复频率fr＝1MHz，当前波位的下次扫描所需的时间间隔Ts＝10s，约束系数g＝4，目标的最大空间速度Vmax＝400m/s，雷达量测参数为距离测量值、方位角测量值和多普勒测量值。1. Simulation scene: 2D radar is used in the experiment, and the radar is considered to be located at the origin of the coordinates. Set the carrier frequency fc = 1GHz, the speed of light c = 3×108 m/s, the transmitted signal bandwidth B = 2MHz, and the beam width θBeam = 3dB. Pulse width τ = 30us, pulse repetition period Tr = 1ms, radar emission signal wavelength λ = 0.3m, pulse repetition frequency fr = 1MHz, time interval required for the next scan of the current wave position Ts = 10s, constraint coefficient g=4, the target's maximum space velocity Vmax =400m/s, and the radar measurement parameters are distance measurement value, azimuth measurement value and Doppler measurement value.
2.仿真内容：2. Simulation content:
仿真1：采用以上实验场景，利用逻辑法和本发明的航迹起始方法，对航迹虚假概率进行仿真对比，结果如图2；Simulation 1: Using the above experimental scenario, using the logic method and the track initiation method of the present invention, the false probability of the track is simulated and compared, and the result is shown in Figure 2;
仿真2：采用以上实验场景，利用逻辑法和本发明的航迹起始方法，对虚假航迹平均数量进行仿真对比，结果如图3；Simulation 2: Using the above experimental scenario, using the logic method and the track initiation method of the present invention, the average number of false tracks is simulated and compared, and the results are shown in Figure 3;
仿真3：采用以上实验场景，利用逻辑法和本发明的航迹起始方法，对航迹起始概率仿真对比，结果如图4；Simulation 3: Using the above experimental scenario, using the logic method and the track initiation method of the present invention, the track initiation probability simulation is compared, and the results are shown in Figure 4;
3.实验结果分析：3. Analysis of experimental results:
参照图2，X轴表示虚警概率，Y轴表示虚假航迹概率。当虚警概率为10-4时，逻辑法的虚假航迹概率为0.6559，本发明的虚假航迹概率为0.00158，可以看出，本发明的虚假航迹概率约为逻辑法的大大降低了虚假航迹的概率。Referring to FIG. 2, the X axis represents the false alarm probability, and the Y axis represents the false track probability. When the false alarm probability is 10-4 , the false track probability of the logical method is 0.6559, and the false track probability of the present invention is 0.00158, as can be seen, the false track probability of the present invention is about that of the logical method The probability of false track is greatly reduced.
参照图3，X轴表示虚警概率，Y轴表示虚假航迹平均数量。当虚假航迹平均数量为0.4999时，逻辑法检测所需的虚警概率为10-6，本发明检测所需的虚警概率为2.684×10-5，可以看出，本发明的虚警概率为逻辑法的26.84倍。Referring to Fig. 3, the X-axis represents the false alarm probability, and the Y-axis represents the average number of false tracks. When the average number of false tracks is 0.4999, the false alarm probability required by the logic method detection is 10-6 , and the false alarm probability required by the detection of the present invention is 2.684×10-5 , it can be seen that the false alarm probability of the present invention It is 26.84 times that of the logic method.
参照图4，X轴表示信噪比，Y轴表示航迹起始概率当信噪比为15dB时，逻辑法航迹起始概率为0.4287，本发明航迹起始概率为0.514，可以看出，本发明的航迹起始概率为逻辑法的1.2倍。With reference to Fig. 4, X-axis represents signal-to-noise ratio, and Y-axis represents track initiation probability. The track initiation probability of the present invention is 1.2 times of the logic method.
综上所述，本发明有效的剔除虚假量测向量，抑制了虚假航迹的形成，进而提高了航迹起始的概率，提升了航迹起始效率。To sum up, the present invention effectively eliminates false measurement vectors, suppresses the formation of false tracks, further improves the probability of track initiation, and improves the efficiency of track initiation.
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| CN201610708469.XACN106405537B (en) | 2016-08-23 | 2016-08-23 | Radar track initial mode based on location information and doppler information |
| Application Number | Priority Date | Filing Date | Title |
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| CN201610708469.XACN106405537B (en) | 2016-08-23 | 2016-08-23 | Radar track initial mode based on location information and doppler information |
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| CN201610708469.XAActiveCN106405537B (en) | 2016-08-23 | 2016-08-23 | Radar track initial mode based on location information and doppler information |
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