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Data Association Algorithm Based on Non-uniform Sampling


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Data Association Algorithm Based on Non-uniform Sampling
LIU Zhao-lei12XU Zhen-lai2ZHANG Guang-yi12GUO Yan-chang2
1.National Key Laboratory of Radar Signal Processing,Xidian University,Xi’an 710071,China;2.Nanjing Research Institute of Electronics Technology,Nanjing 210013,China
target tracking retrodicted probability probabilist ic data assoc iation mult-i d imensional associat ion
The procedure applying the backw ard recursive probabilist ic data associat ion filtering a-l gorithm based on mult-i scan is presented. The rules of track losing judgment are d iscussed. Simu lat ions aremade to compare the performance o f data assoc ia tion algorithm based onmu lt-i scan and sing le scan considering the non-uniform sampling prob lem that is common in practice for target tracking. On the cond ition o f the same samples, the resu lts show that non-un ifo rm samp ling can outperfo rm uniform samp ling in track m aintainability w hen association algorithm based on mu lt-i scan is used, and the more differences o f performance are shown tha t the process noise is h igher, the false alarm density is h igher and the probab ility o f detection is h igher.


[ 1] Steven T C, Kenneth B. Radar resource m anag em ent form echanically rota ted, e lectron ica lly scanned phased array radars [ A ]. IEEE Proceed ing s of the Radar Con ference [ C]. Los Ange les: IEEE, 1991. 88- 92.
[ 2] Thom asW J. Phased a rray radar track ing w ith non - uniform ly spaced m easurem ents [ A]. IEEE Proceedings of the Radar Confe rence [ C ] . Da llas: IEEE, 1998.
[ 3] A louaniA T, R iceT R. Asynchronous track fusion revisited [ A]. IEEE Proceed ings o f the Twenty- N inth Southeastern Symposium on System Theo ry [ C] . Tennessee: IEEE, 1997. 118- 122.
[ 4] Blackm an S, Popoli R. Design and ana lysis of mode rn tracking system s [M ]. Boston: Artech H ouse, 1999. 967- 1 065.
[ 5] N iu R X, Varshney P, M ehro traK, et a.l Temporal fusion in m ult-i sensor target tracking systems [ A ]. ISIF [ C]. Annapo lis: ISIF /IEEE, 2002. 1 030- 1 037.
[ 6] N iu R X, Va rshney P, M ehrotraK, et a.l Sensor stagge ring in mu lt-i senso r targe t track ing sy stem s [ A ]. 2003 IEEE Radar Conference [ C ]. H un tsv ille: IEEE, 2003.
[ 7] Drumm ond O E. M u ltiple-fram e best-hypothes is ta rget track ing w ith mu ltiple sensor [ A ]. Proceed ings o f SPIE, Vo l 5 204 [ C] . B ellingham: SPIE, 2003.
[ 8] Drumm ond O E. Targ et track ing w ith retrodicted discrete probab ilities [ A ]. SPIE Vol 3 163 [ C ]. San D iego: SPIE, 1997, 249- 268.
[ 9] Drumm ond O E. M ultip le targ et tracking w ith m ultip le fram e, probab ilistic data association [ A ]. SPIE Vo l 1954 [ C]. Orlando: SPIE, 1993. 394- 408.
[ 10] Li X R, Ba r-Sha lom Y. S tab ility evalua tion and track life o f the PDAF for tracking in c lutte r [ J]. IEEE T rans on AC, 1991, 36( 5): 588- 602.
[ 11] B ar-Sha lom Y, B lair W D, Mu ltitarg et- m ultisenso r track ing: applica tions and advances vo lum e III [M ]. Norw ood, MA: Artech H ouse. 2000.


Last Update: 2007-06-30