被动时差测量下的多机动目标跟踪(英文)  

Passive multiple maneuvering targets tracking using TDOA measurements

作　　者：吴盘龙[1] 姬存慧[1] 张廉政 

机构地区：[1]南京理工大学自动化学院,南京210094

出　　处：《中国惯性技术学报》2013年第5期609-614,共6页Journal of Chinese Inertial Technology

基　　金：国家自然科学基金(61104196);江苏省自然科学基金(BK20131352);南京理工大学紫金之星基金资助(AB41381)

摘　　要：在时差被动跟踪系统中,由于目标加速度的不确定性和杂波干扰的存在使得多机动目标跟踪的难度增加。为了提高多机动目标的跟踪效果,提出一种被动时差测量条件下的多机动目标交互多模型联合概率数据关联(IMM-JPDA)跟踪算法。该算法将IMM和JPDA算法相结合,利用IMM模型集合间不同模型的相互切换来估计被跟踪目标的状态,利用JPDA算法处理被动时差测量系统的测量噪声和虚警。最后,通过对IMM-JPDA算法和单模型JPDA算法的跟踪性能进行了对比分析和验证。仿真结果表明在相同条件下,IMM-JPDA算法的跟踪精度优于JPDA算法,IMM-JPDA算法能减少89%的位置误差和90%的速度误差。It is difficult to track multiple maneuvering targets in time-difference-of-arrival (TDOA) passive tracking system due to the uncertain acceleration and the disturbance of the clutter. To solve this problem, a theoretical framework of passive multiple maneuvering target tracking using TDOA measurements by the IMM-JPDA algorithm is proposed, which combines the interacting multiple model (IMM) and joint probabilistic data association (JPDA) to improve the tracking performance. Under the architecture of the proposed algorithm, the IMM has the ability to estimate the state of a dynamic system with several models which can switch from one model to another. The JPDA method is used to process noisy measurements and false alarms. The tracking performance of IMM-JPDA algorithm is compared with single model based JPDA algorithm. The experiment results show that, under the same conditions, the IMM-JPDA algorithm can more effectively improve the tracking precision than the JPDA algorithm. The IMM-JPDA algorithm can reduce nearly 89% of the position error and nearly 90% of the velocity error than the JPDA algorithm.

关 键 词：IMM JPDA 机动目标 被动跟踪 时差测量 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]