基于概率假设密度滤波的多目标跟踪算法
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摘要
概率假设密度(PHD)滤波算法在雷达、红外以及可见光等传感器的多目标跟踪中研究越来越广泛。主要研究了基于PHD滤波的多目标跟踪算法的发展现状,简要介绍了PHD滤波算法的基本原理及其在目标运动模型、多检测情况、杂波分布规律假定等方面的研究进展,概述了PHD滤波的实现方法及研究进展,介绍了PHD滤波的主要应用领域,着眼提高目标跟踪精度和实时性的发展要求提出了PHD滤波的展望。
Probability Hypothesis Density(PHD)filter algorithm has been widely used in multiple target tracking research for radar, infrared and visible light sensors. This paper mainly studies the present development situation of mult-target tracking algorithm based on PHD filter. this paper briefly introduces the basic principle of PHD filter and research progress of the algorithm in target dynamic and multiple-detection and clutter distribution assumption. An overview of the implementation methods of PHD filter and the research progress is given. the main application fields of PHD filter are introduced. Aimed at the improvement the target tracking accuracy and real-time performance,expectation of PHD filter is proposed.
Probability Hypothesis Density(PHD)filter algorithm has been widely used in multiple target tracking research for radar, infrared and visible light sensors. This paper mainly studies the present development situation of mult-target tracking algorithm based on PHD filter. this paper briefly introduces the basic principle of PHD filter and research progress of the algorithm in target dynamic and multiple-detection and clutter distribution assumption. An overview of the implementation methods of PHD filter and the research progress is given. the main application fields of PHD filter are introduced. Aimed at the improvement the target tracking accuracy and real-time performance,expectation of PHD filter is proposed.
引文
[1]杨威,付耀文,龙建乾,等.基于有限集统计学理论的目标跟踪技术研究综述[J].电子学报,2012,7(40):1440-1448.
[2]吕学斌,周群彪,陈正茂,等.高斯混合概率假设密度滤波器在多目标跟踪中的应用[J].计算机学报,2012,35(2):397-404.
[3]徐洋.基于随机有限集理论的多目标跟踪技术研究[D].长沙:国防科技大学,2012.
[4]MAHLER R P S.Multitarget bayes filtering via first-order multitarget moments[J].IEEE Transactions on Aerospace and Electronic Systems,2003,39(4):1152-1178.
[5]孟凡彬.基于随机集理论的多目标跟踪技术研究[D].哈尔滨:哈尔滨工程大学,2010.
[6]杨峰,王永齐,梁彦,等.基于概率假设密度滤波方法的多目标跟踪技术综述[J].自动化学报,2013,39(11):1944-1956.
[7]MAHLER R.PHD filters of higher order in target number[J].IEEE Transactions on Aerospace and Electronic Systems,2007,43(4):1523-1543.
[8]B N,MA W K.The gaussian mixture probability hypothesis density filter[J].IEEE Transactions on Signal Processing,2006,54(11):4091-4104.
[9]ZHENG X T,SONG L P.Improved CPHD filtering with unknown clutter rate[C]//In:10th World Congress Conference on Intelligent Control and Automation,Beijing,2012:4326–4331.
[10]RISTIC B,CLARK D,VO B N,et al.Adaptive target birth intensity for PHD and CPHD filters[J].IEEE Trans.Aerosp.Electron.Syst.,2012,48(2):1656-1668.
[11]PIECZYNSKI W.Pairwise Markov chains[J].IEEE Trans.Pattern Anal.Mach.Intell.,2003,25(5):634-639.
[12]PIECZYNSKI W.Pairwise Markov chains and Bayesian unsupervised fusion[C]//Proc.3rd Int’l Conf.on Information Fusion,Paris,France,2000:10-13.
[13]PETETIN Y,DESBOUVRIES F.Bayesian multi-object filtering for pairwise Markov chains[J].IEEE Trans.Sign.Proc.,2013,61(18):4481-4490.
[14]MAHLER R.Tracking targets with pairwise-markov dynamics[C]//Proc.18th Int’l Conf.on Information Fusion,Washington,D.C.,2015:6-9.
[15]RONALD M,CONSULTANT E MN.On multitarget pairwise-Markov models[J].SPIE,2015:9474.
[16]VO B T,VO B N,CANTONI A.Bayesian ltering with random nite set observations[J].IEEE Trans.Signal Process.,2008,56(4):1313-1326.
[17]TANG X,CHEN X,MICHAEL M,et al.A multiple-detection probability hypothesis density filter[J].IEEE Trans Signal Process,2015,63(8):2007-2019.
[18]MAHLER R.CPHD and PHD filters for unknown backgrounds,II:Multitarget filtering in dynamic clutter[C]//Proc.SPIE 7330,2009.
[19]CHEN X,KIRUBARAJAN T,THARMARASA R,et al.Integrated clutter estimation and targettracking using spatial,amplitude,and Doppler information[C]//Proc.SPIE7697,2010.
[20]CHEN X,THARMARASA R,PELLETIER M,et al.Integrated clutter estimation and target tracking using Poisson point processes[J].IEEE Trans.AES,2012,48(2):1210-1234.
[21]MAHLER R.Advances in statistical multisource-multitarget information fusion[M].Norwood,MA:Artech House,2014.
[22]MAHLER R,El-Fallah,A.ìCPHD and PHD filters for unknown backgrounds,III:Tractable multitarget filtering in dynamic clutter[C]//Proc.SPIE 7698,2010.
[23]MAHLER R,VO B T,VO B N,CPHD filtering with unknown clutter rate and detection profile[J].IEEE Trans.Sign.Proc.,2011,59(6):3497-3513.
[24]MAHLER R,VO B T.An improved CPHD filter for unknown clutter backgrounds[C]//Proc.SPIE 9091,2014.
[25]MAHLER R.CPHD filters for unknown clutter and target-birth processes[C]//Proc.SPIE 9091,2014.
[26]VO B T,VO B N,HOSEINNEZHAD R,et al.Multi-bernoulli filtering with unknown clutter intensity and sensor field-of-view,Proc[C]//45th Conf.on Information Sciences and Systems(CISS2011),Baltimore,MD,2011:23-25.
[27]RONALD M,CONSULTANT,EAGAN,et al.Multi-bernoulli filtering with unknown clutter intensity and sensor field-of-view[C]//Proc.of SPIE,2011.
[28]VO B N,SINGH S,BOUCET A.Sequential monte carlo methods for multi-target filtering with random finite sets[J].IEEE Transactions on Aerospace and Electronic Systems.2005,41(4):1224-1245.
[29]VO M R.A theory of PHD filters of higher order in target number[C]//Proceedings of the 2006 Signal and Data Processing of Small Targets.Orlando,FL:SPIE,2006:62350K-62350K-12.
[30]LI T C,SUN S D,BOLI M,et al.Algorithm design for parallel implementation of the SMC-PHD filter[J].Signal Processing,2016,119:115-127.
[31]YOON J H,DU Y K,YOON K J.Efficient importance sampling function design for sequential Monte Carlo PHD filter[J].Signal Processing,2012,92:2315-2321.
[32]YOON K J,KIM D Y,YOON K J.Gaussian mixture importance sampling function for unscented SMC-PHD filter,Signal Processing,2013,93:2664-2670.
[33]LI T C,SUN S D,Tariq Pervez Sattar.High-speed sigma-gating SMC-PHD filter[J].Signal Processing,2013,93:2586-2593.
[34]ZHANG H Q,GE H W,YANG J L,et al.A GM-PHD algorithm for multiple target tracking based on false alarm detection with irregular window[J].Signal Processing,2016,120:537-552.
[35]MAHDI Y D,ZOHREH A.Refined GM-PHD tracker for tracking targets in possible subsequent missed detections[J].Signal Processing,2015,116:112-126.
[36]WANG X,HAN C Z.An improved multiple model GM-PHD filter for maneuvering target tracking[J].Chinese Journal of Aeronautics,2013,26(1):179-185.
[37]CLARK D,VO B T,VO B N.Gaussian particle implementations of probability hypothesis density filters[C]//Proceedings of the 2007 IEEE Aerospace Conference,2007:1-11.
[38]周承兴,刘贵喜,侯连勇,等.改进的高斯粒子概率假设密度滤波算法[J].控制理论与应用,2011,28(7):1005-1008.
[39]LEHMANN F.Recursive bayesian filtering for multitarget track-before-detect in passive radars[J].IEEE Transactions on Aerospace and Electronic Systems,2012,48(3):2458-2480.
[40]TONG H S,ZHANG H,MENG H D,et al.A shrinkage probability hypothesis density filter for multitarget tracking[J].EURASIP Journal on Advances in Signal Processing2011,116:1-13.
[41]HABTEMARIAM B K,THARMARASA R,KIRUBARAJAN T.PHD filter based track-before-detect for MIMO radars[J].Signal Processing,2012,92:667-678.
[42]PUNITHAKUMAR K,KIRUBARAJAN T,SINHA A.A sequential monte carlo probability hypothesis density algorithm for multitarget track-before-detect[C]//Proceedings of SPIE.San Diego,2005:1-8.
[43]ZHAN R H,GAO Y Z,HU J M,et al.SMC-PHD based multi-target track-before-detect with nonstandard point observations model[J].J.Cent.South Univ,2015(22):232-240.
[44]GRANSTRM K,LUNDQUIST C,ORGUNER U.Extended target tracking using a gaussian-mixture PHD filter[J].IEEE Trans.Aerosp.Electron.Syst.,2012,48(4):3268-3286.
[45]MAHLER R.PHD filters for nonstandard targets,I:extended targets[C]//Proceedings of the 12th International Conference on Inf.Fusion,Seattle,WA,USA,2009:915-921.
[46]GRANSTRM K,ORGUNER U.On spawning and combination of extended/group targets modeled with random matrices[J].IEEE Trans.Signal Process,2013,61(3):678-692.
[47]LUNDQUIST C,GRANSTRM K,ORGUNER U.An extended target CPHD filter and a gamma Gaussian inverse Wishart implementation[J].IEEE J.Select.Topics Signal Process,2013,7(3):472-483.
[48]ORGUNER U,LUNDQUIST C,GRANSTRM K.Extended target tracking with a cardinalized probability hypothesis density filter[C]//Proceedings of the 14th International Conference on Information Fusion,Chicago,Illinois,USA,2011:1-8.
[49]ZHANG Y Q,JI H B.A robust and fast partitioning algorithm for extended target tracking using a Gaussian inverse Wishart PHD filter[J].Knowledge-Based Systems,2016(118):1-17.
[50]CARPENTER G A,GROSSBERG S,ROSEN D B.Fuzzy ART:fast stable learning and categorization of analog patterns by an adaptive resonance system[J].Neural Netw,1991,4(1):759-771.
[51]GRANSTRM K,ORGUNER U.A PHD filter for tracking multiple extended targets using random matrices[J].IEEE Trans.Signal Process,2012,60(11):5657-5671.
[52]MAHLER R.Approximate multisensor CPHD and PHD filters[C]//Proceedings of the 13th International Conference on Information Fusion,Edinburgh,Scotland,2010:1-8.
[53]MAHLER R.The multisensor PHD filter,I:general solution via multitarget calculus[C]//Proceedings of the SPIE Conference on Signal Processing,Sensor Fusion and Target Recognition,2009:1-12.
[54]MAHLER R,EL-FALLAH A.Bayesian unified registration and tracking[C]//Proceedings of the SPIE Conference on Signal Processing,Sensor Fusion and Target Recognition,2011:1-11.
[55]LI W,JIA Y,DU J,et al.Gaussian mixture PHD filter for multi-sensor multi-target tracking with registration errors[J].Signal Process,2013,93(1):86-99.
[56]LIAN F,HAN C,LIU W,et al.Joint spatial registration an multitarget tracking using an extended probability hypothesis density filter[J].IET Radar Sonar Navig,2011,5(4):441-448.
[57]DELANDE E,DUFLOS E,VANHEEGHE P,et al.Multi-sensor PHD by space partitioning:computation of a true reference density within the PHD framework[C]//Proceedings of the IEEE International Conference on Statistical Signal Processing Workshop,Nice,2011:333-336.
[58]LIU L,JI H B,FAN Z H.Improved Iterated-corrector PHD with Gaussian mixture implementation[J].Signal Processing,2015,114:89-99.
[59]LI W L,JIA Y M,DU J P,et al.Gaussian mixture PHD filter for multi-sensor multi-target tracking with registration errors[J].Signal Processing,2013,93:86-99.
[60]WU W H,JIANG J,LIU W J,et al.Augmented state GM-PHD filter with registration errors for multi-target tracking by Doppler radars[J].Signal Processing,2016,120:117-128.
[2]吕学斌,周群彪,陈正茂,等.高斯混合概率假设密度滤波器在多目标跟踪中的应用[J].计算机学报,2012,35(2):397-404.
[3]徐洋.基于随机有限集理论的多目标跟踪技术研究[D].长沙:国防科技大学,2012.
[4]MAHLER R P S.Multitarget bayes filtering via first-order multitarget moments[J].IEEE Transactions on Aerospace and Electronic Systems,2003,39(4):1152-1178.
[5]孟凡彬.基于随机集理论的多目标跟踪技术研究[D].哈尔滨:哈尔滨工程大学,2010.
[6]杨峰,王永齐,梁彦,等.基于概率假设密度滤波方法的多目标跟踪技术综述[J].自动化学报,2013,39(11):1944-1956.
[7]MAHLER R.PHD filters of higher order in target number[J].IEEE Transactions on Aerospace and Electronic Systems,2007,43(4):1523-1543.
[8]B N,MA W K.The gaussian mixture probability hypothesis density filter[J].IEEE Transactions on Signal Processing,2006,54(11):4091-4104.
[9]ZHENG X T,SONG L P.Improved CPHD filtering with unknown clutter rate[C]//In:10th World Congress Conference on Intelligent Control and Automation,Beijing,2012:4326–4331.
[10]RISTIC B,CLARK D,VO B N,et al.Adaptive target birth intensity for PHD and CPHD filters[J].IEEE Trans.Aerosp.Electron.Syst.,2012,48(2):1656-1668.
[11]PIECZYNSKI W.Pairwise Markov chains[J].IEEE Trans.Pattern Anal.Mach.Intell.,2003,25(5):634-639.
[12]PIECZYNSKI W.Pairwise Markov chains and Bayesian unsupervised fusion[C]//Proc.3rd Int’l Conf.on Information Fusion,Paris,France,2000:10-13.
[13]PETETIN Y,DESBOUVRIES F.Bayesian multi-object filtering for pairwise Markov chains[J].IEEE Trans.Sign.Proc.,2013,61(18):4481-4490.
[14]MAHLER R.Tracking targets with pairwise-markov dynamics[C]//Proc.18th Int’l Conf.on Information Fusion,Washington,D.C.,2015:6-9.
[15]RONALD M,CONSULTANT E MN.On multitarget pairwise-Markov models[J].SPIE,2015:9474.
[16]VO B T,VO B N,CANTONI A.Bayesian ltering with random nite set observations[J].IEEE Trans.Signal Process.,2008,56(4):1313-1326.
[17]TANG X,CHEN X,MICHAEL M,et al.A multiple-detection probability hypothesis density filter[J].IEEE Trans Signal Process,2015,63(8):2007-2019.
[18]MAHLER R.CPHD and PHD filters for unknown backgrounds,II:Multitarget filtering in dynamic clutter[C]//Proc.SPIE 7330,2009.
[19]CHEN X,KIRUBARAJAN T,THARMARASA R,et al.Integrated clutter estimation and targettracking using spatial,amplitude,and Doppler information[C]//Proc.SPIE7697,2010.
[20]CHEN X,THARMARASA R,PELLETIER M,et al.Integrated clutter estimation and target tracking using Poisson point processes[J].IEEE Trans.AES,2012,48(2):1210-1234.
[21]MAHLER R.Advances in statistical multisource-multitarget information fusion[M].Norwood,MA:Artech House,2014.
[22]MAHLER R,El-Fallah,A.ìCPHD and PHD filters for unknown backgrounds,III:Tractable multitarget filtering in dynamic clutter[C]//Proc.SPIE 7698,2010.
[23]MAHLER R,VO B T,VO B N,CPHD filtering with unknown clutter rate and detection profile[J].IEEE Trans.Sign.Proc.,2011,59(6):3497-3513.
[24]MAHLER R,VO B T.An improved CPHD filter for unknown clutter backgrounds[C]//Proc.SPIE 9091,2014.
[25]MAHLER R.CPHD filters for unknown clutter and target-birth processes[C]//Proc.SPIE 9091,2014.
[26]VO B T,VO B N,HOSEINNEZHAD R,et al.Multi-bernoulli filtering with unknown clutter intensity and sensor field-of-view,Proc[C]//45th Conf.on Information Sciences and Systems(CISS2011),Baltimore,MD,2011:23-25.
[27]RONALD M,CONSULTANT,EAGAN,et al.Multi-bernoulli filtering with unknown clutter intensity and sensor field-of-view[C]//Proc.of SPIE,2011.
[28]VO B N,SINGH S,BOUCET A.Sequential monte carlo methods for multi-target filtering with random finite sets[J].IEEE Transactions on Aerospace and Electronic Systems.2005,41(4):1224-1245.
[29]VO M R.A theory of PHD filters of higher order in target number[C]//Proceedings of the 2006 Signal and Data Processing of Small Targets.Orlando,FL:SPIE,2006:62350K-62350K-12.
[30]LI T C,SUN S D,BOLI M,et al.Algorithm design for parallel implementation of the SMC-PHD filter[J].Signal Processing,2016,119:115-127.
[31]YOON J H,DU Y K,YOON K J.Efficient importance sampling function design for sequential Monte Carlo PHD filter[J].Signal Processing,2012,92:2315-2321.
[32]YOON K J,KIM D Y,YOON K J.Gaussian mixture importance sampling function for unscented SMC-PHD filter,Signal Processing,2013,93:2664-2670.
[33]LI T C,SUN S D,Tariq Pervez Sattar.High-speed sigma-gating SMC-PHD filter[J].Signal Processing,2013,93:2586-2593.
[34]ZHANG H Q,GE H W,YANG J L,et al.A GM-PHD algorithm for multiple target tracking based on false alarm detection with irregular window[J].Signal Processing,2016,120:537-552.
[35]MAHDI Y D,ZOHREH A.Refined GM-PHD tracker for tracking targets in possible subsequent missed detections[J].Signal Processing,2015,116:112-126.
[36]WANG X,HAN C Z.An improved multiple model GM-PHD filter for maneuvering target tracking[J].Chinese Journal of Aeronautics,2013,26(1):179-185.
[37]CLARK D,VO B T,VO B N.Gaussian particle implementations of probability hypothesis density filters[C]//Proceedings of the 2007 IEEE Aerospace Conference,2007:1-11.
[38]周承兴,刘贵喜,侯连勇,等.改进的高斯粒子概率假设密度滤波算法[J].控制理论与应用,2011,28(7):1005-1008.
[39]LEHMANN F.Recursive bayesian filtering for multitarget track-before-detect in passive radars[J].IEEE Transactions on Aerospace and Electronic Systems,2012,48(3):2458-2480.
[40]TONG H S,ZHANG H,MENG H D,et al.A shrinkage probability hypothesis density filter for multitarget tracking[J].EURASIP Journal on Advances in Signal Processing2011,116:1-13.
[41]HABTEMARIAM B K,THARMARASA R,KIRUBARAJAN T.PHD filter based track-before-detect for MIMO radars[J].Signal Processing,2012,92:667-678.
[42]PUNITHAKUMAR K,KIRUBARAJAN T,SINHA A.A sequential monte carlo probability hypothesis density algorithm for multitarget track-before-detect[C]//Proceedings of SPIE.San Diego,2005:1-8.
[43]ZHAN R H,GAO Y Z,HU J M,et al.SMC-PHD based multi-target track-before-detect with nonstandard point observations model[J].J.Cent.South Univ,2015(22):232-240.
[44]GRANSTRM K,LUNDQUIST C,ORGUNER U.Extended target tracking using a gaussian-mixture PHD filter[J].IEEE Trans.Aerosp.Electron.Syst.,2012,48(4):3268-3286.
[45]MAHLER R.PHD filters for nonstandard targets,I:extended targets[C]//Proceedings of the 12th International Conference on Inf.Fusion,Seattle,WA,USA,2009:915-921.
[46]GRANSTRM K,ORGUNER U.On spawning and combination of extended/group targets modeled with random matrices[J].IEEE Trans.Signal Process,2013,61(3):678-692.
[47]LUNDQUIST C,GRANSTRM K,ORGUNER U.An extended target CPHD filter and a gamma Gaussian inverse Wishart implementation[J].IEEE J.Select.Topics Signal Process,2013,7(3):472-483.
[48]ORGUNER U,LUNDQUIST C,GRANSTRM K.Extended target tracking with a cardinalized probability hypothesis density filter[C]//Proceedings of the 14th International Conference on Information Fusion,Chicago,Illinois,USA,2011:1-8.
[49]ZHANG Y Q,JI H B.A robust and fast partitioning algorithm for extended target tracking using a Gaussian inverse Wishart PHD filter[J].Knowledge-Based Systems,2016(118):1-17.
[50]CARPENTER G A,GROSSBERG S,ROSEN D B.Fuzzy ART:fast stable learning and categorization of analog patterns by an adaptive resonance system[J].Neural Netw,1991,4(1):759-771.
[51]GRANSTRM K,ORGUNER U.A PHD filter for tracking multiple extended targets using random matrices[J].IEEE Trans.Signal Process,2012,60(11):5657-5671.
[52]MAHLER R.Approximate multisensor CPHD and PHD filters[C]//Proceedings of the 13th International Conference on Information Fusion,Edinburgh,Scotland,2010:1-8.
[53]MAHLER R.The multisensor PHD filter,I:general solution via multitarget calculus[C]//Proceedings of the SPIE Conference on Signal Processing,Sensor Fusion and Target Recognition,2009:1-12.
[54]MAHLER R,EL-FALLAH A.Bayesian unified registration and tracking[C]//Proceedings of the SPIE Conference on Signal Processing,Sensor Fusion and Target Recognition,2011:1-11.
[55]LI W,JIA Y,DU J,et al.Gaussian mixture PHD filter for multi-sensor multi-target tracking with registration errors[J].Signal Process,2013,93(1):86-99.
[56]LIAN F,HAN C,LIU W,et al.Joint spatial registration an multitarget tracking using an extended probability hypothesis density filter[J].IET Radar Sonar Navig,2011,5(4):441-448.
[57]DELANDE E,DUFLOS E,VANHEEGHE P,et al.Multi-sensor PHD by space partitioning:computation of a true reference density within the PHD framework[C]//Proceedings of the IEEE International Conference on Statistical Signal Processing Workshop,Nice,2011:333-336.
[58]LIU L,JI H B,FAN Z H.Improved Iterated-corrector PHD with Gaussian mixture implementation[J].Signal Processing,2015,114:89-99.
[59]LI W L,JIA Y M,DU J P,et al.Gaussian mixture PHD filter for multi-sensor multi-target tracking with registration errors[J].Signal Processing,2013,93:86-99.
[60]WU W H,JIANG J,LIU W J,et al.Augmented state GM-PHD filter with registration errors for multi-target tracking by Doppler radars[J].Signal Processing,2016,120:117-128.