一种分散化多站联合目标跟踪算法

 本文基于分散估计理论的基本原理,考虑各子站基于不同坐标系这个一般情形,给出了一种新的分散化多站联合目标跟踪算法。并针对子站间四种不同的通讯方式,对算法进行了仿真。结果表明,本文的最优合成算法即使在各个子站由于缺少足够的信息而得到错误估计的情况下,也能快速地给出正确的估计。

A DISTRIBUTED TARGET TRACKING ALGORITHM FOR MULTIPLE STATIONS

In recent years, there has been a great deal of interest in the problem of multi-station multi-target tracking. The recent published paper of S. Mori proposed a new kind of theory of multi-target tracking for distributed sensor networks; K. C. Chang generalized Bar-Shalom's famous joint probabilistic data association algorithm to multi-station case. In the present paper, we propose a new distributed target tracking algorithm for multiple stations based on the basic principles of distributed estimation theory. Without loss of generality,we consider the case where two substations and a main station (this wain station may be the same as one of the two sub-stations) coordinate to track a moving target,and the two sub-stations use different coordinate systern. The two sub-stations measure and estimate the states of the targets and send the sub-estimates to the main station according to some communication strategies. The main station combines the two-estimates optimally and obtains better estimates. We start from the basic formula of the problem and obtain the optimal equations for combining the sub-estimates of the sub-stations just using simple algebra. After the final algorithm has been proposed, we simulate it through an example for four different communication strategies. The simulation results show that our algorithm is effective, and giycs the correct estimates quickly even if the sub-estimates of the sub-stations are all wrong.