A multiple-target tracking filter using data association based on a MAP approach

作     者：Jeong, H Park, JH 

作者机构：POSTECH Dept EE Pohang 790784 Kyungbuk South Korea 

出 版 物：《IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES》 (电子信息通信学会汇刊：电子学、通信及计算机科学基础)

年 卷 期：2000年第E83A卷第6期

页      面：1203-1210页

核心收录：

学科分类：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）] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：multiple-target tracking data association Kalman filter 

摘      要：Tracking many targets simultaneously using a search radar has been one of the major research areas in radar signal processing. The primary difficulty in this problem arises from the noise characteristics of the incoming data. Hence it is crucial to obtain an accurate association between targets and noisy measurements in multi-target tracking. We introduce a new scheme for optimal data association, based on a MAP approach, and thereby derive an efficient energy function. Unlike the previous approaches, the new constraints between targets and measurements can manage the cases of target missing and false alarm. Presently, most algorithms need heuristic adjustments of the parameters. Instead, this paper suggests a mechanism that determines the parameters in an automated manner. Experimental results, including PDA and NNF, show that the proposed method reduces position errors in crossing trajectories: by 32.8% on the average compared to NNF.