一种水声传感器网络容错定位算法

Corruption Tolerant Localization for Underwater Acoustic Sensor Networks

针对由于分组冲突和信号噪声造成测距数据包损坏,导致节点间距离测量缺失从而定位性能下降的问题,提出了一种能够容忍测距包损坏的定位算法。首先,设计了一种高效的节点间距离测量值收集机制,并构造具有部分观测值的平方距离矩阵;然后,利用平方距离矩阵固有的低秩结构,将矩阵的恢复补全转化为一个正则化的低秩矩阵分解问题,并设计了一种改进的Newton-Raphson方法进行优化求解;最后,基于恢复矩阵内的距离测量值,应用多维标度技术对所有节点进行定位。仿真结果表明,该算法在定位精度、定位覆盖率和稳定性等方面均优于其他对比算法。

Packet collisions and signal noises may corrupt ranging packets, resulting in distance measurements data missing and degrading localization performance. A packet corruption tolerant localization algorithm is proposed to address this challenge. First, an energy-efficient mechanism is designed to gather inter-node distance measurements and form partially observed square distance matrix(SDM). Then, leveraging the intrinsic low-rank structure of SDM,the reconstruction of true SDM is formulated as a regularized low-rank matrix factorization problem and an improved Newton-Raphson method is designed to optimize the problem. Finally, a multi-dimension scaling technique is applied to localize all the nodes based on the reconstructed SDM. Simulation results demonstrate that the proposed algorithm outperforms the benchmark approaches in terms of localization accuracy, coverage and stability.