Title :
Multitarget tracking algorithm based on clutter model estimation
Author :
Lv Ning ; Lian Feng ; Han ChongZhao
Author_Institution :
MOE KLINNS Lab., Xi´an Jiaotong Univ., Xi´an, China
Abstract :
Aiming at severe bias caused by unknown and complex clutter, A multitarget tracking algorithm based on clutter model estimation is put forward in this paper. In this algorithm, multitarget likelihood function is established with the finite mixture model (FMM), the parameters of which can be estimated by the algorithm of expectation maximum (EM). Furthermore, target number and multitarget states can be estimated precisely after the clutter model fitted. Association between target and measurement can be avoided. Simulation proved that the proposed algorithm has a good performance in dealing with unknown and complex clutter.
Keywords :
expectation-maximisation algorithm; target tracking; EM algorithm; FMM; clutter model estimation; expectation maximum algorithm; finite mixture model; multitarget likelihood function; multitarget tracking algorithm; Clutter; Estimation; Merging; Noise; Noise measurement; Target tracking; Time measurement; clutter model estimation; expectation maximum component; finite mixture model; multitarget tracking;
Conference_Titel :
Information Fusion (FUSION), 2013 16th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-605-86311-1-3