[1] [1] MAHLER R P S.Statistical multisource-multitarget information fusion［M］.Norwood:Artech House,2007:185-195.

[2] [2] MAHLER R P S.Multi-target Bayes filtering via first-order multi-target moments［J］.IEEE Transactions on Aerospace and Electronic Systems,2003,39(4):1152-1178.

[3] [3] MAHLER R P S.PHD filters of higher order in target number［J］.IEEE Transactions on Aerospace and Electronic Systems,2007,43(4):1523-1543.

[4] [4] VO B T,VO B N,CANTONI A.The cardinality balanced multi-target multi-Bernoulli filter and its implementations［J］.IEEE Transactions on Signal Processing,2009,57(2): 409-423.

[5] [5] VO B N,SINGH S,DOUCET A.Sequential Monte Carlo implementation of the PHD filter for multi-target tracking［C］//The 6th International Conference on Information Fusion,2003:792-799.

[6] [6] VO B N,MA W K.The Gaussian mixture probability hypothesis density filter［J］.IEEE Transactions on Signal Processing,2006,4(11):4091-4104.

[7] [7] REUTER S,VO B T,VO B N,et al.The labeled multi-Bernoulli filter［J］.IEEE Transactions on Signal Processing, 2014,62(12):3246-3260.

[8] [8] VO B N,VO B T,PHUNG D.Labeled random finite sets and Bayes multi-target tracking filter［J］.IEEE Transactions on Signal Processing,2014,62(24):6554-6567.

[9] [9] PAPI F,VO B N,VO B T,et al.Generalized labeled multi-Bernoulli approximation of multi-object densities［J］.IEEE Transactions on Signal Processing,2015,63(20):5487-5497.

[10] [10] TANG X,CHEN X,MCDONALD M,et al.A multiple-detection probability hypothesis density filter［J］.IEEE Transactions on Signal Processing,2015,63(8):2007-2019.

[11] [11] ZHANG H Q,GE H W,YANG J L.Adaptive Gaussian mixture probability hypothesis density for tracking multiple targets［J］.Optik-International Journal for Light and Electron Optics,2016,127(8):3918-3924.

[12] [12] ZHOU X L,LI Y F,HE B W,et al.GM-PHD-based multi-target visual tracking using entropy distribution and game theory［J］.IEEE Transactions on Industrial Informatics, 2014,10(2):1064-1076.

[13] [13] SHI C M,ZHAO L L,WANG J J,et al.Micro-object motion tracking based on the probability hypothesis density particle tracker［J］.Journal of Mathematical Biology, 2016,72 (5):1225-1254.

[14] [14] PAPI F,KIM D Y.A particle multi-target tracker for superpositional measurements using labeled random finite sets［J］.IEEE Transactions on Signal Processing, 2015, 63(16):4348-4358.

[15] [15] GOSTAR A K,HOSEINNEZHAD R,BAB-HADIASHAR A.Multi-Bernoulli sensor-selection for multi-target tracking with unknown clutter and detection profiles［J］.Signal Processing,2016,119(c):28-42.

[16] [16] YAZDIAN-DEHKORDI M,AZIMIFAR Z,MASNADI-SHI- RAZI M A.An improvement on GM-PHD filter for occluded target tracking［C］//The IEEE 36th International Conference on Acoustics,Speech and Signal Processing (ICASSP),2011:1773-1776.

[17] [17] YAZDIAN-DEHKORDI M,AZIMIFAR Z,MASNADI-SHI-RAZI M A.Penalized Gaussian mixture probability hypothesis density filter for multiple target tracking［J］.Signal Processing,2013,92 (5):1230-1242.

[18] [18] WANG Y,MENG H D,LIU Y M,et al.Collaborative penalized Gaussian mixture PHD tracker for close target tracking［J］.Signal Processing,2014,102(9):1-15.

[19] [19] 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(c):537-552.

[20] [20] SCHUHMACHER D,VO B T,VO B N.A consistent metric for performance evaluation of multi-object filters［J］.IEEE Transactions on Signal Processing,2008,56(8):3447-3457.