Joint spatial registration and multi-target tracking using an extended PM-CPHD filter

作     者：LIAN Feng1 , HAN ChongZhao1, LIU WeiFeng2, LIU Jing1 & YUAN XiangHui1 1SKLMSE Lab, MOE KLINNS Lab, School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China 2School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China 

作者机构：SKLMSE Lab MOE KLINNS Lab School of Electronics and Information Engineering Xi’an Jiaotong University Xi’an China School of Automation Hangzhou Dianzi University Hangzhou China 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2012年第55卷第3期

页      面：501-511页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 080902[工学-电路与系统] 08[工学] 080202[工学-机械电子工程] 0802[工学-机械工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Natural Science Foundation of China (Grant Nos. 61004087, 61104214,91016020, 61104051) China Postdoctoral Science Foundation (Grant Nos. 20100481338, 2011M501443) Fundamental Research Funds for the Central University and Doctoral Fund of Ministry of Education of China (Grant No. 20100201120036) Gansu Provincial Science and Technology Planning for China (Grant No. 0916RFZA017) 

主　　题：multi-sensor spatial registration multi-target tracking (MTT) cardinalized probability hypothesis density (PHD) filter random finite set (RFS) 

摘      要：An extended product multi-sensor cardinalized probability hypothesis density (PM-CPHD) filter for spatial registration and multi-target tracking (MTT) is proposed. The number and states of targets and the biases of sensors are jointly estimated by this method without the data association. Monte Carlo (MC) simulation results show that the proposed method (i) outperforms, although computationally more expensive than, the extended multi-sensor PHD filter which has been proposed for joint spatial registration and MTT; (ii) outperforms the multi-sensor joint probabilistic data association (MSJPDA) filter which is also extended in this study for joint spatial registration and MTT when the clutter is relatively dense.