Chang Shengming, Li Youming, He Yucheng, Wu Yongqing
Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China.
School of Electronic and Information Engineering, Ningbo University of Technology, Ningbo 315211, China.
Sensors (Basel). 2019 May 20;19(10):2323. doi: 10.3390/s19102323.
The received signal strength (RSS) based target localization problem in underwater acoustic wireless sensor networks (UWSNs) is considered. Two cases with respect to target transmit power are considered. For the first case, under the assumption that the reference of the target transmit power is known, we derive a novel weighted least squares (WLS) estimator by using an approximation to the RSS expressions, and then transform the originally non-convex problem into a mixed semi-definite programming/second-order cone programming (SD/SOCP) problem for reaching an efficient solution. For the second case, there is no knowledge on the target transmit power, and we treat the reference power as an additional unknown parameter. In this case, we formulate a WLS estimator by using a further approximation, and present an iterative ML and mixed SD/SOCP algorithm for solving the derived WLS problem. For both cases, we also derive the closed form expressions of the Cramer-Rao Lower Bounds (CRLBs) on root mean square error (RMSE). Computer simulation results show the superior performance of the proposed methods over the existing ones in the underwater acoustic environment.
考虑水下声学无线传感器网络（UWSN）中基于接收信号强度（RSS）的目标定位问题。针对目标发射功率考虑两种情况。对于第一种情况，在目标发射功率参考已知的假设下，我们通过对RSS表达式进行近似推导了一种新颖的加权最小二乘（WLS）估计器，然后将原本的非凸问题转化为混合半定规划/二阶锥规划（SD/SOCP）问题以获得高效解。对于第二种情况，目标发射功率未知，我们将参考功率视为一个额外的未知参数。在这种情况下，我们通过进一步近似制定了一个WLS估计器，并提出了一种迭代极大似然和混合SD/SOCP算法来求解推导的WLS问题。对于这两种情况，我们还推导了均方根误差（RMSE）的克拉美 - 罗下界（CRLB）的闭式表达式。计算机仿真结果表明，在水下声学环境中，所提方法比现有方法具有更优的性能。
