雷达微弱目标检测和跟踪方法研究
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摘要
如何提高对低可观测目标的检测能力、延长对它们的预警时间是现代雷达面临的重要挑战之一。雷达目标回波信号的长时间处理技术是提高雷达目标检测性能的一种有效途径，也是雷达信号处理领域的关键技术和研究热点之一，一直得到各国学者的高度关注和广泛研究。本文主要从长时间雷达目标回波信号处理方面展开对雷达微弱目标检测和跟踪方法的研究。一方面研究基于粒子滤波的雷达微弱目标检测前跟踪方法，另一方面探索和实践适合工程实现的雷达信号长时间积累方法。具体工作概括如下：
1.提出了一种基于粒子滤波的雷达扩展目标检测和跟踪方法。该方法首先在雷达的距离-多普勒频率二维数据上建立雷达扩展目标模型，然后推导了该模型的似然比函数，最后采用粒子滤波算法实现对雷达扩展目标的检测和跟踪。实验结果表明该方法能实现对低信噪比下的雷达扩展目标的检测和跟踪。
2.提出了一种基于粒子群滤波的雷达多目标检测和跟踪方法，将多目标检测和跟踪问题转化为对多个单目标的检测和跟踪问题。所提方法采用两种粒子群实现递归的贝叶斯滤波：一类为新生粒子群，用来引入新出现的目标；另一类为跟踪粒子群，用来跟踪上一时刻存在的目标。每个粒子群仅检测和跟踪一个目标并独立地处理自己对应的目标。所提方法通过粒子群以及它们对应的目标存在概率来估计多目标的个数和状态。另外，还提出一种基于距离信息的概率数据关联方法以实现对临近目标的航迹关联。该方法化繁为简，降低了多目标检测和跟踪的复杂度。实验表明该方法能较好地实现对多目标个数和状态的估计，并且具有较高的数据关联正确率。
3.提出一种基于PHD滤波的多目标检测和跟踪方法。所提方法首先根据系统的动态方程和PHD算法中当前时刻的粒子，产生代表连续多帧观测数据中的目标轨迹的粒子，然后根据该粒子和目标估计轨迹的相关系数来实现粒子和目标的关联，最后通过与目标关联的粒子来估计目标状态并同时实现数据关联。由于充分利用了连续多帧观测数据中的目标轨迹信息，所提方法显著地提高了数据关联的正确率和目标状态的估计精度，且能实现对交叉目标或相距较近的目标的跟踪。仿真实验结果证明了其有效性。
4. Radon-Fourier变换（RFT）是一种根据目标的运动参数对位于距离-慢时间平面中的目标轨迹进行积分来积累雷达目标能量的方法，其有效地增加了对雷达信号的相参积累时间。针对RFT算法的运算量大和未插值时会由量化误差引起能量积累损失这两个问题，提出一种基于Chirp-Z变换（CZT）的快速RFT方法。该方法在频域实现，并将其实现过程和CZT算法结合在一起，成功地解决了以上问题。另外，在不增加运算量的前提下，该方法还能通过补偿目标的多普勒频率来消除匹配滤波损失。针对近似径向匀加速运动的平稳目标，所提方法采用Dechirping方法对由目标运动引起的二次相位进行补偿，进一步延长了雷达信号的有效相参积累时间。实验结果表明在理想情况下该方法的目标能量积累性能接近理论最优值。
5.探索和实践适合工程应用的雷达信号长时间积累方法，提出了一种基于帧间移位运算的雷达信号长时间积累方法，并将其应用到实际工程中，外场实验结果证明了其有效性。通过对雷达实测数据的分析，在所提方法的基础上，提出了一种改进方法。新方法首先通过帧间移位运算将距离-多普勒-时间三维数据空间中的目标轨迹校正到垂直于多普勒频率轴的平面中，然后通过矩阵重组将校正后的数据分解为并列的距离-时间二维矩阵，最后通过积累重组的二维矩阵中的近似直线的目标轨迹来实现目标能量的长时间积累。该方法采用简单的移位和累加运算完成，运算量小，可在工程应用中实现。基于实测数据的实验结果表明该方法能增加雷达目标回波信号的积累时间，从而有效提高雷达的目标检测性能。
How to improve the detection performance of low observable targets and promotetheir early warning time is one of the great challenges that modern radar are facing. Thetechnique of long time processing of radar target echo signal is an effective approach topromote the detection performance of radar. As one of the key techniques and researchfocuses of radar signal processing, it has been obtained great concern and extensiveresearch by scholars in various countries. In this paper, the study of radar dim targetdetection and tracking is mainly implemented in the aspect of long time processing ofradar target echos. On the one hand, the algorithms of particle filter basedtrack-before-detect of radar dim target are studied and on the other hand, the algorithmsof radar signal long time integration which are suitable for practical applications arestudied and practised. The specific work is summarized as follows:
1. A particle filter based radar extended target detection and tracking algorithm isproposed. In the proposed algorithm, firstly, extended target model of radar isestablished according to the2-D data in radar range and Doppler map. Then, thelikelihood ratio function of the proposed model is deduced. At last, the detection andtracking algorithm of radar extended target is implemented based on particle filter.Simulation results manifest that the algorithm can effectively detect and track radarextended target with low signal to noise ratio (SNR).
2. An algorithm based on particle swarm filter for radar multi-target detection andtracking (MTDT) is proposed, which turns the problem of MTDT into the problem ofmultiple independent detection and tracking of a single target. Two kinds of particleswarms, the birth and tracking particle swarms, which are designed to introduce newtargets and track existing targets, respectively, are employed to implement a recursiveBayesian filter in the proposed algorithm. Each particle swarm only detects and tracksone target and deals with its corresponding target independently. In the proposedalgorithm, target number and states are estimated by the particle swarms and theircorresponding probabilities of target existence (PTE). Besides, a probabilistic dataassociation method based on range information is proposed to realize track associationof close distributed target. The proposed method simplifies the complicated problemand reduces the computational complexity of the MTDT. Simulation results show thatthe proposed method can well estimate the target number and states and have highcorrect ratio of data asscociation.
3. A scheme for multi-target detection and tracking based on PHD filter is proposed.The proposed scheme firstly generates particles which represent the target tracks inseveral sequential frames of measurements according to the system dynamic equationand the current particles in PHD filter. Then, the correlation coefficients of the particlesand the estimated target tracks are used to implement the association of particles andtargets. At last, data association is accomplished in the process of estimating the state oftargets by the particles associated with them. Due to the sufficient usage of theinformation of target tracks in several sequential frames of the measurements, thecorrect ratio of data association and the precision of estimated target state areremarkably improved by the proposed methods, and the proposed algorithm can alsotrack the interacted or close spaced targets. Simulation results demonstrate itseffectiveness.
4. Radon-Fourier Transform (RFT) integrates radar target energy by integrating thetarget reflected energy in range-slow time domain according to the target motionparameters, which can effectively increase the coherent integration time of radar signal.A fast RFT method based on Chirp-Z Transform (CZT) is proposed to alleviate highcomputation cost often encountered by the RFT and the energy lose caused byquantization error without interpolation. In addition, the proposed method can alsoeliminate the loss of matched filter by compensating the Doppler frequency of targetwithout increasing the computation cost. For the stationary target with near constantacceleration, Dechirping method is adopted to compensate the quadratic phase causedby the acceleration of target, which further increase the effective coherent integrationtime of radar signals. The experimental data processing results show that the integrationperformance of the proposed method can almost achieve the optimal one under idealcondition.
5. Methods of radar signal long time processing which are suitable for practicalapplications are investigated. A radar signal long time integration algorithm based onshifting operation among frames is proposed and, its effectiveness is validated by theexperimental data processing results. Through the analysis of real radar data, a modifiedmethod is proposed. In the modified method, firstly, the target track in the3-D space(range-Doppler-time data) is corrected into a certain plane which is perpendicular to theaxes of Doppler frequency by shifting operation among frames. Then, the corrected3-Ddata is decomposed into parallel2-D matrices of range-time by matrices reconstruction.At last, long time integration is fulfilled by integrating the target track whichapproximates to a straight line in the recombined2-D matrices. The method can be implemented by shifting and accumulating operation with low computation cost and berealized in practical application. The experimental results show that the proposedmethod can increase the effective integration time of radar target echo signal andimprove target detection performance of radar systems.
1.提出了一种基于粒子滤波的雷达扩展目标检测和跟踪方法。该方法首先在雷达的距离-多普勒频率二维数据上建立雷达扩展目标模型，然后推导了该模型的似然比函数，最后采用粒子滤波算法实现对雷达扩展目标的检测和跟踪。实验结果表明该方法能实现对低信噪比下的雷达扩展目标的检测和跟踪。
2.提出了一种基于粒子群滤波的雷达多目标检测和跟踪方法，将多目标检测和跟踪问题转化为对多个单目标的检测和跟踪问题。所提方法采用两种粒子群实现递归的贝叶斯滤波：一类为新生粒子群，用来引入新出现的目标；另一类为跟踪粒子群，用来跟踪上一时刻存在的目标。每个粒子群仅检测和跟踪一个目标并独立地处理自己对应的目标。所提方法通过粒子群以及它们对应的目标存在概率来估计多目标的个数和状态。另外，还提出一种基于距离信息的概率数据关联方法以实现对临近目标的航迹关联。该方法化繁为简，降低了多目标检测和跟踪的复杂度。实验表明该方法能较好地实现对多目标个数和状态的估计，并且具有较高的数据关联正确率。
3.提出一种基于PHD滤波的多目标检测和跟踪方法。所提方法首先根据系统的动态方程和PHD算法中当前时刻的粒子，产生代表连续多帧观测数据中的目标轨迹的粒子，然后根据该粒子和目标估计轨迹的相关系数来实现粒子和目标的关联，最后通过与目标关联的粒子来估计目标状态并同时实现数据关联。由于充分利用了连续多帧观测数据中的目标轨迹信息，所提方法显著地提高了数据关联的正确率和目标状态的估计精度，且能实现对交叉目标或相距较近的目标的跟踪。仿真实验结果证明了其有效性。
4. Radon-Fourier变换（RFT）是一种根据目标的运动参数对位于距离-慢时间平面中的目标轨迹进行积分来积累雷达目标能量的方法，其有效地增加了对雷达信号的相参积累时间。针对RFT算法的运算量大和未插值时会由量化误差引起能量积累损失这两个问题，提出一种基于Chirp-Z变换（CZT）的快速RFT方法。该方法在频域实现，并将其实现过程和CZT算法结合在一起，成功地解决了以上问题。另外，在不增加运算量的前提下，该方法还能通过补偿目标的多普勒频率来消除匹配滤波损失。针对近似径向匀加速运动的平稳目标，所提方法采用Dechirping方法对由目标运动引起的二次相位进行补偿，进一步延长了雷达信号的有效相参积累时间。实验结果表明在理想情况下该方法的目标能量积累性能接近理论最优值。
5.探索和实践适合工程应用的雷达信号长时间积累方法，提出了一种基于帧间移位运算的雷达信号长时间积累方法，并将其应用到实际工程中，外场实验结果证明了其有效性。通过对雷达实测数据的分析，在所提方法的基础上，提出了一种改进方法。新方法首先通过帧间移位运算将距离-多普勒-时间三维数据空间中的目标轨迹校正到垂直于多普勒频率轴的平面中，然后通过矩阵重组将校正后的数据分解为并列的距离-时间二维矩阵，最后通过积累重组的二维矩阵中的近似直线的目标轨迹来实现目标能量的长时间积累。该方法采用简单的移位和累加运算完成，运算量小，可在工程应用中实现。基于实测数据的实验结果表明该方法能增加雷达目标回波信号的积累时间，从而有效提高雷达的目标检测性能。
How to improve the detection performance of low observable targets and promotetheir early warning time is one of the great challenges that modern radar are facing. Thetechnique of long time processing of radar target echo signal is an effective approach topromote the detection performance of radar. As one of the key techniques and researchfocuses of radar signal processing, it has been obtained great concern and extensiveresearch by scholars in various countries. In this paper, the study of radar dim targetdetection and tracking is mainly implemented in the aspect of long time processing ofradar target echos. On the one hand, the algorithms of particle filter basedtrack-before-detect of radar dim target are studied and on the other hand, the algorithmsof radar signal long time integration which are suitable for practical applications arestudied and practised. The specific work is summarized as follows:
1. A particle filter based radar extended target detection and tracking algorithm isproposed. In the proposed algorithm, firstly, extended target model of radar isestablished according to the2-D data in radar range and Doppler map. Then, thelikelihood ratio function of the proposed model is deduced. At last, the detection andtracking algorithm of radar extended target is implemented based on particle filter.Simulation results manifest that the algorithm can effectively detect and track radarextended target with low signal to noise ratio (SNR).
2. An algorithm based on particle swarm filter for radar multi-target detection andtracking (MTDT) is proposed, which turns the problem of MTDT into the problem ofmultiple independent detection and tracking of a single target. Two kinds of particleswarms, the birth and tracking particle swarms, which are designed to introduce newtargets and track existing targets, respectively, are employed to implement a recursiveBayesian filter in the proposed algorithm. Each particle swarm only detects and tracksone target and deals with its corresponding target independently. In the proposedalgorithm, target number and states are estimated by the particle swarms and theircorresponding probabilities of target existence (PTE). Besides, a probabilistic dataassociation method based on range information is proposed to realize track associationof close distributed target. The proposed method simplifies the complicated problemand reduces the computational complexity of the MTDT. Simulation results show thatthe proposed method can well estimate the target number and states and have highcorrect ratio of data asscociation.
3. A scheme for multi-target detection and tracking based on PHD filter is proposed.The proposed scheme firstly generates particles which represent the target tracks inseveral sequential frames of measurements according to the system dynamic equationand the current particles in PHD filter. Then, the correlation coefficients of the particlesand the estimated target tracks are used to implement the association of particles andtargets. At last, data association is accomplished in the process of estimating the state oftargets by the particles associated with them. Due to the sufficient usage of theinformation of target tracks in several sequential frames of the measurements, thecorrect ratio of data association and the precision of estimated target state areremarkably improved by the proposed methods, and the proposed algorithm can alsotrack the interacted or close spaced targets. Simulation results demonstrate itseffectiveness.
4. Radon-Fourier Transform (RFT) integrates radar target energy by integrating thetarget reflected energy in range-slow time domain according to the target motionparameters, which can effectively increase the coherent integration time of radar signal.A fast RFT method based on Chirp-Z Transform (CZT) is proposed to alleviate highcomputation cost often encountered by the RFT and the energy lose caused byquantization error without interpolation. In addition, the proposed method can alsoeliminate the loss of matched filter by compensating the Doppler frequency of targetwithout increasing the computation cost. For the stationary target with near constantacceleration, Dechirping method is adopted to compensate the quadratic phase causedby the acceleration of target, which further increase the effective coherent integrationtime of radar signals. The experimental data processing results show that the integrationperformance of the proposed method can almost achieve the optimal one under idealcondition.
5. Methods of radar signal long time processing which are suitable for practicalapplications are investigated. A radar signal long time integration algorithm based onshifting operation among frames is proposed and, its effectiveness is validated by theexperimental data processing results. Through the analysis of real radar data, a modifiedmethod is proposed. In the modified method, firstly, the target track in the3-D space(range-Doppler-time data) is corrected into a certain plane which is perpendicular to theaxes of Doppler frequency by shifting operation among frames. Then, the corrected3-Ddata is decomposed into parallel2-D matrices of range-time by matrices reconstruction.At last, long time integration is fulfilled by integrating the target track whichapproximates to a straight line in the recombined2-D matrices. The method can be implemented by shifting and accumulating operation with low computation cost and berealized in practical application. The experimental results show that the proposedmethod can increase the effective integration time of radar target echo signal andimprove target detection performance of radar systems.
引文
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