ECM下基于相控阵雷达的目标跟踪算法研究
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摘要
目标跟踪在军用和民用方面都占有重要的地位。在现代高技术局部战争中，目标跟踪技术遇到的严峻挑战之一是电子对抗技术(ECM)。目前国内对电子对抗下的目标跟踪算法研究较少，一般都是常规算法。相控阵雷达是一种多功能、能跟踪多目标的先进雷达体制，研究ECM下相控阵雷达的机动目标跟踪技术具有十分重要的现实意义。
本文首先提出了常规条件下三种基于相控阵雷达的自适应跟踪算法。相控阵雷达可以在任何方向无惯性改变雷达照射方向，这使得它能进行变速率的采样。自适应采样是在一定的跟踪精度下，依据目标运动状态来判断下一次采样时间。自适应采样能最大程度的减少雷达更新次数，节约雷达资源。文中给出了一种根据预测误差方差的交互多模(IMM)的自适应采样算法，一种基于三个Singer模型的自适应采样算法。另外，还提出了一个自适应转弯速率模型的机动目标跟踪算法。
接着，研究了ECM下相控阵雷达观测的目标的点迹模型。ECM场景包括一个远距离支援干扰机(SOJ)和目标距离波门拖引(RGPO)。在常规算法中，对雷达的观测值通常是目标位置的真实值加上独立的高斯白噪声，在ECM下，这种观测模型是不符合实际情况的。通过建立相控阵雷达的仿真模型，给出了ECM存在时单脉冲测角的目标的测量角度和误差方差。观测模型的建立为目标算法的进行奠定了基础。
最后，给出了一个可以用于目标跟踪和雷达管理的IMMPDAF算法。交互多模(IMM)和概率数据关联(PDAF)相结合的IMMPDAF算法，适用于在ECM下对强机动目标进行跟踪。IMMPDAF算法中同样利用了自适应采样技术。对于SOJ产生的干扰，可通过选择高能量波形，提高检测门限来抑制。对于RGPO，利用PDAF来抑制。这样的整个过程，使得在跟踪目标的同时，也参与了雷达的管理，譬如自适应的选择采样时间、探测门限、探测波形。
The technology of target tracking plays an important role in both military and civilian areas. In modern high-tech part warfare, one of the severe challenges to target tracking is electronic counter measures. Most of the target tracking algorithms is normal ones without consideration of ECM in our research. Phased array radar is a multifucion and multitarget -tracking . It has very important realism significance to study the tracking algorithms for high maneuvering target with phased array radar in ECM.
First, three adaptive tracking algorithms based on phased array radar in normal condition are presented. Since a phased array radar can direct the radar beam in any direction without inertia, it can perform adaptive sampling of target trajectories. The technique of adaptive sampling is determining the next revisit time according to the target's motion. Using adaptive sampling can reduce the numbers of update, which leads to save radar energy. Two adaptive sampling algorithms are given: one is based on IMM, and another is based on three Singer models. In addition, a maneuvering target tracking algorithm using adaptive turn rate models are presented.
Secondly, the target trajectory recorded by phased array radar in ECM are studied . The ECM includes a standoff jammer (SOJ) broadcasting wideband noise and targets attempting range gate pull off (RGPO). In normal algorithms, the measurements are modeled as the true values plus independent Gaussian errors, which is not according with the ture condition in ECM. Estimates of bearing and elevation and the standard deviations of the measurements ,which are monopulse processing's results in ECM, are given .The measurements of simulation is the basis of processing tracking algorithm.
Finally, IMMPDAF for radar management and tracking in ECM is given. IMM estimator combined with PDA technique is suitable for target tracking in ECM. Adaptive sample scheduling are used in IMMPDAF. With a high energy waveform, an increased detection threshold, SOJ can be neutralized. PDAF can neutralize the false measurements of RGPO. During the same period of tracking target, the IMMPDAF can manage radar too, such as adaptively selecting revisit time, detection threshold and radar waveform.
本文首先提出了常规条件下三种基于相控阵雷达的自适应跟踪算法。相控阵雷达可以在任何方向无惯性改变雷达照射方向，这使得它能进行变速率的采样。自适应采样是在一定的跟踪精度下，依据目标运动状态来判断下一次采样时间。自适应采样能最大程度的减少雷达更新次数，节约雷达资源。文中给出了一种根据预测误差方差的交互多模(IMM)的自适应采样算法，一种基于三个Singer模型的自适应采样算法。另外，还提出了一个自适应转弯速率模型的机动目标跟踪算法。
接着，研究了ECM下相控阵雷达观测的目标的点迹模型。ECM场景包括一个远距离支援干扰机(SOJ)和目标距离波门拖引(RGPO)。在常规算法中，对雷达的观测值通常是目标位置的真实值加上独立的高斯白噪声，在ECM下，这种观测模型是不符合实际情况的。通过建立相控阵雷达的仿真模型，给出了ECM存在时单脉冲测角的目标的测量角度和误差方差。观测模型的建立为目标算法的进行奠定了基础。
最后，给出了一个可以用于目标跟踪和雷达管理的IMMPDAF算法。交互多模(IMM)和概率数据关联(PDAF)相结合的IMMPDAF算法，适用于在ECM下对强机动目标进行跟踪。IMMPDAF算法中同样利用了自适应采样技术。对于SOJ产生的干扰，可通过选择高能量波形，提高检测门限来抑制。对于RGPO，利用PDAF来抑制。这样的整个过程，使得在跟踪目标的同时，也参与了雷达的管理，譬如自适应的选择采样时间、探测门限、探测波形。
The technology of target tracking plays an important role in both military and civilian areas. In modern high-tech part warfare, one of the severe challenges to target tracking is electronic counter measures. Most of the target tracking algorithms is normal ones without consideration of ECM in our research. Phased array radar is a multifucion and multitarget -tracking . It has very important realism significance to study the tracking algorithms for high maneuvering target with phased array radar in ECM.
First, three adaptive tracking algorithms based on phased array radar in normal condition are presented. Since a phased array radar can direct the radar beam in any direction without inertia, it can perform adaptive sampling of target trajectories. The technique of adaptive sampling is determining the next revisit time according to the target's motion. Using adaptive sampling can reduce the numbers of update, which leads to save radar energy. Two adaptive sampling algorithms are given: one is based on IMM, and another is based on three Singer models. In addition, a maneuvering target tracking algorithm using adaptive turn rate models are presented.
Secondly, the target trajectory recorded by phased array radar in ECM are studied . The ECM includes a standoff jammer (SOJ) broadcasting wideband noise and targets attempting range gate pull off (RGPO). In normal algorithms, the measurements are modeled as the true values plus independent Gaussian errors, which is not according with the ture condition in ECM. Estimates of bearing and elevation and the standard deviations of the measurements ,which are monopulse processing's results in ECM, are given .The measurements of simulation is the basis of processing tracking algorithm.
Finally, IMMPDAF for radar management and tracking in ECM is given. IMM estimator combined with PDA technique is suitable for target tracking in ECM. Adaptive sample scheduling are used in IMMPDAF. With a high energy waveform, an increased detection threshold, SOJ can be neutralized. PDAF can neutralize the false measurements of RGPO. During the same period of tracking target, the IMMPDAF can manage radar too, such as adaptively selecting revisit time, detection threshold and radar waveform.
引文
[1] 刘福声，罗鹏飞。统计信号处理。国防科技大学出版社，1999
[2] Samul Blackman, Robert Popoli. Design and analysis of Modern Tracking Systems. Artech House ,Bostom London. 1999．
[3] G.A.Watson and W.D.Blair. Tracking performance of phased array radar with revisit time controlled using the IMM algorithm. IEEE Conference.on Dec. 1994
[4] Blackman,S.S. Multiple-Target Tracking with Radar Applications.Dedham,MA,june, 1995
[5] W.D.Blair,and G.A.Watson, IMM Algorithm and A periodic Data, Proc.of SPIE Acquisiton,Tracking,and Pointing VI Orlando,FL,Apr. 1992
[6] Van Keuk,G. Software structure and sampling strategy for automatic target tracking with a phased array radar. Proceedings of AGARD conference, Monterey, CA,1978,no.252,pp.11-1,11-13
[7] H.-J.Shin,S.-M.Hong,D.-H,Hong. Adaptive-update-rate target tracking for phased-array radar. IEE Proc.-Radar, Sonar Naving.,Vol. 142,No.3, June 1995
[8] Samuel Blackman, Robert Popil. Design and Analysis of Modern Tracking Systems[M].Artech House, 1999, pp 200-210
[9] Watson,G.A. and Blair,W.D., IMM Algorithm for Tracking Target That Manoeuver Through Coordinated Turns. Proceedings of SPIE Signal and Data Processing of Small Targets, 1992,pp 236-247
[10] Munir,A.and Atherton,D.P. Manouvering Target tracking Using different Turn Rate Models in the Interacting Multiple Model Algorithm. Proceding Conference on Decision and Control,New Orleans, Lousiana, USA, Decemer 13-15,1995
[11] Cook,C.E.,and Bernfeld,M. Radar Signal:An Introdution to Theory and Applications.Norwood,MA:Artech House, 1993
[12] Edd,B. Radar:principles,technology,Applications.Norwood,MA:Artech house, 1993
[13] W.Blair,G.Watson and S. Hoffman. Benchmark problem foe beam Pointing control of phased array radar against maneuvering targets.Proc.of the 1994 American Control Conference, 1994
[14] X.R.Li,C.He.2M-PDAF: An integrated two model probabilistic data association fliter.SPIE Conference on Signal and Data processing of Small Targets,USA, 1999
[15] W.Blair,G.Watson,. Benchmark for radar resource allocation and tracking targets in the presence of ECM. IEEE Trans.on Aes,VOL.34,1998
[16] Bar-Shalom,Y.,and Li, X.R.(1993) .Estimation and Tracking : Principles, Techniques and Software. Dedham, MA:Artech House, 1993．
[17] Yeddanapudi,M., Bar-Shalom,Y., and Pattipati,K.R. IMM estimation for multitarget-multisensors air traffic surveillance. IEEE Proceedings,85,1,1997
[18]Kirubarajan,T., Bar-Shalom,Y., and Daeipour, E. Adaptive beam pointing control of a phased array radar in the presence of ECM and false alarms using IMMPDAF. In proceedings of the American Control Conference,Seattle,WA,Junc, 1995
[19]Li,X.R., and Bar-Shalom,Y. Tracking with debiased consistent and Electronic Systems,29,3,1993
[20]赵艳丽，刘剑，罗鹏飞。基于相控阵雷达的自适应采样目标跟踪算法。现代雷达(已录用待发)
[21]赵艳丽，刘剑，罗鹏飞。自适应转弯模型的机动目标跟踪算法。现代雷达。(已录用待发)
[22]罗鹏飞,赵艳丽。相控阵雷达多目标跟踪(MTT)技术综述。国防科技大学电子科学与工程学院学术年会论文集。2001．10。
[23]赵国庆。雷达对抗原理。西安电子科技大学出版社，1999
[2] Samul Blackman, Robert Popoli. Design and analysis of Modern Tracking Systems. Artech House ,Bostom London. 1999．
[3] G.A.Watson and W.D.Blair. Tracking performance of phased array radar with revisit time controlled using the IMM algorithm. IEEE Conference.on Dec. 1994
[4] Blackman,S.S. Multiple-Target Tracking with Radar Applications.Dedham,MA,june, 1995
[5] W.D.Blair,and G.A.Watson, IMM Algorithm and A periodic Data, Proc.of SPIE Acquisiton,Tracking,and Pointing VI Orlando,FL,Apr. 1992
[6] Van Keuk,G. Software structure and sampling strategy for automatic target tracking with a phased array radar. Proceedings of AGARD conference, Monterey, CA,1978,no.252,pp.11-1,11-13
[7] H.-J.Shin,S.-M.Hong,D.-H,Hong. Adaptive-update-rate target tracking for phased-array radar. IEE Proc.-Radar, Sonar Naving.,Vol. 142,No.3, June 1995
[8] Samuel Blackman, Robert Popil. Design and Analysis of Modern Tracking Systems[M].Artech House, 1999, pp 200-210
[9] Watson,G.A. and Blair,W.D., IMM Algorithm for Tracking Target That Manoeuver Through Coordinated Turns. Proceedings of SPIE Signal and Data Processing of Small Targets, 1992,pp 236-247
[10] Munir,A.and Atherton,D.P. Manouvering Target tracking Using different Turn Rate Models in the Interacting Multiple Model Algorithm. Proceding Conference on Decision and Control,New Orleans, Lousiana, USA, Decemer 13-15,1995
[11] Cook,C.E.,and Bernfeld,M. Radar Signal:An Introdution to Theory and Applications.Norwood,MA:Artech House, 1993
[12] Edd,B. Radar:principles,technology,Applications.Norwood,MA:Artech house, 1993
[13] W.Blair,G.Watson and S. Hoffman. Benchmark problem foe beam Pointing control of phased array radar against maneuvering targets.Proc.of the 1994 American Control Conference, 1994
[14] X.R.Li,C.He.2M-PDAF: An integrated two model probabilistic data association fliter.SPIE Conference on Signal and Data processing of Small Targets,USA, 1999
[15] W.Blair,G.Watson,. Benchmark for radar resource allocation and tracking targets in the presence of ECM. IEEE Trans.on Aes,VOL.34,1998
[16] Bar-Shalom,Y.,and Li, X.R.(1993) .Estimation and Tracking : Principles, Techniques and Software. Dedham, MA:Artech House, 1993．
[17] Yeddanapudi,M., Bar-Shalom,Y., and Pattipati,K.R. IMM estimation for multitarget-multisensors air traffic surveillance. IEEE Proceedings,85,1,1997
[18]Kirubarajan,T., Bar-Shalom,Y., and Daeipour, E. Adaptive beam pointing control of a phased array radar in the presence of ECM and false alarms using IMMPDAF. In proceedings of the American Control Conference,Seattle,WA,Junc, 1995
[19]Li,X.R., and Bar-Shalom,Y. Tracking with debiased consistent and Electronic Systems,29,3,1993
[20]赵艳丽，刘剑，罗鹏飞。基于相控阵雷达的自适应采样目标跟踪算法。现代雷达(已录用待发)
[21]赵艳丽，刘剑，罗鹏飞。自适应转弯模型的机动目标跟踪算法。现代雷达。(已录用待发)
[22]罗鹏飞,赵艳丽。相控阵雷达多目标跟踪(MTT)技术综述。国防科技大学电子科学与工程学院学术年会论文集。2001．10。
[23]赵国庆。雷达对抗原理。西安电子科技大学出版社，1999