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本发明公开了一种基于水下无线传感器网络的目标跟踪方法。该方法首先根据最强信号原则选择簇节点,然后根据单跳距离准则组成簇网络对目标进行观测,如果观测信号强度超过阈值,则发送观测数据给簇头节点。簇头节点接收到粗内节点传送的数据,采用改进重采样的粒子滤波算法对当前时刻的目标位置和方差进行估计。根据目标的运动不断地更新簇头节点,将上一簇头节点状态估计值和方差估计值传送给当前簇头节点,再由当前簇头节点采用改进的重采样粒子滤波算法估计运动目标位置,直到运动目标超出了水下无线传感器网络的跟踪范围;本发明使用改进重采样算法的粒子滤波跟踪方法估计水下目标的位置和方差,提高水下无线传感器网络的目标跟踪性能。
The invention discloses a target tracking method based on an underwater wireless sensor network. Firstly, the cluster nodes are selected according to the strongest signal principle. Then the cluster network is constructed according to the single-hop distance criterion to observe the target. If the observed signal strength exceeds the threshold, the observation data is sent to the cluster head node. The cluster head node receives the data transmitted by the coarse inner nodes, and uses the improved resampling particle filter algorithm to estimate the target position and variance at the current moment. According to the motion of the target, the cluster head node is continuously updated, the state estimation value and the variance estimation value of the previous cluster head node are transmitted to the current cluster head node, and the current cluster head node uses the improved resampling particle filter algorithm to estimate the moving target position, Until the moving target is beyond the tracking range of the underwater wireless sensor network; the present invention uses the particle filtering tracking method of the improved resampling algorithm to estimate the position and variance of the underwater target and improve the target tracking performance of the underwater wireless sensor network.