在水声传感器网络中,利用多个传感器节点探测到的方位信息进行目标跟踪是水下目标跟踪领域的一种新思路。由于水中声速的限制,信号到达各个节点的时间不是同步的,提出了一种修正时间延迟的方法,并将其与粒子滤波(PF)、扩展卡尔曼粒子滤波(EKPF)结合来解决该非线性跟踪问题。仿真分析表明修正时延后,算法的跟踪性能有较大提高;并且在相同条件下,EKPF的跟踪性能比PF好。
In underwater acoustic sensor networks,using the angle information estimated by multiple sensors to track target provides a new approach to underwater target tracking.As the underwater sound velocity is limited,the time it takes the signal to reach each node is significantly different.This paper presents a method to modify the time delay,and combines it with the particle filter(PF) and the extend Kalman particle filter(EKPF) to solve this nonlinear tracking problem.Simulation analysis shows that the tracking performance of the modified time delay PF and EKPF is better than the general PF and EKPF,and under the same conditions,the tracking performance of EKPF is better than PF.