A Multi-Node Cooperative Bearing-Only Target Passive Tracking Algorithm via UWSNs
A Multi-Node Cooperative Bearing-Only Target Passive Tracking Algorithm via UWSNs
复制标题
基于 UWSN 的多节点协作仅方位目标无源跟踪算法
DOI：
10.1109/jsen.2019.2931885
复制
发表时间：
2019-11-15
影响因子：
4.3
通讯作者：
Zhang, Qunfei
中科院分区：
文献类型：
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作者：
Han, Xueyan;Liu, Meiqin;Zhang, Qunfei
水下目标被动跟踪在海洋领域有着广泛的应用，无论是商业目的还是军事目的。水下无线传感器网络(UWSNs)引起了人们的极大兴趣，成为水下目标被动跟踪的重要工具。然而，电池为UWSN中的节点提供电力，当它们的能量耗尽时更换它们是不现实的。因此，研究高能量效率的水下目标被动跟踪算法是非常必要的。为了在跟踪精度和能量消耗之间进行权衡，提出了一种基于UWSNs动态分簇的多传感器协作纯方位被动跟踪算法。在分布式融合的框架下，利用线性最小方差融合准则最小化融合误差协方差的痕迹。在此基础上，将动态分簇过程引入被动目标跟踪中，从能量消耗的角度选择簇头节点，通过自适应节点选择方法选择簇内成员节点，将节点选择问题转化为背包问题。最后，仿真结果和分析表明，该算法可以在保证足够跟踪精度的前提下有效降低能耗。
Underwater target passive tracking has ubiquitous applications in oceanic fields for both commercial and military purposes. The underwater wireless sensor networks (UWSNs) draw great interest and become promising tools for underwater target passive tracking. However, batteries provide power for nodes in the UWSNs, and it is unrealistic to replace them when their energies are exhausted. Therefore, it is essential to study on energy-efficient underwater target passive tracking algorithm. To make a tradeoff between tracking accuracy and energy consumption, this paper proposes a multi-sensor cooperative bearing-only passive tracking algorithm based on dynamic clustering via UWSNs. Under the framework of distributed fusion, we utilize the linear minimum variance fusion criterion to minimize the trace of fusion error covariance. Furthermore, we introduce the dynamic clustering process into passive target tracking, select cluster head nodes from the perspective of energy consumption, and choose cluster member nodes through an adaptive node selection method, which formulates the nodes selection problem into a knapsack problem in mathematics. Finally, the simulation results and analysis demonstrate that this algorithm can effectively reduce energy consumption on the premise of sufficient tracking accuracy.