RSS测距模式下无线传感器网络凸松驰定位算法

Convex Relaxation Location Algorithm for Wireless Sensor Network Under Received Signal Strength Ranging Mode

针对最大似然估计算法对目标函数的非凸性要求,在应用无线传感器网络定位时,会产生多个局部极值的问题,提出一种无线传感器网络凸松驰定位算法。基于二阶锥凸松驰策略和最小二乘算法对最大似然估计的非凸性进行改进,给出其均方根误差的Cramer-Rao下界表达式。针对3种不同情形下的无线传感器网络,分别给出不同的凸松驰定位方案,以提高算法的鲁棒性。通过与现有方案的仿真对比显示,在不显著增加计算复杂度的前提下,可有效减少该方案的均方根误差。

According to the non convexity demand for the objective function of Maximum Likelihood（ML）estimation,which results in more than one local extremum,a kind of convex relaxation location algorithm for Wireless Sensor Network（WSN）is proposed.The Second Order Cone Programming（SOCP）and Semi-Definite Programming（SDP）are used to improve the non convexity of the maximum likelihood estimation,and the Cramer-Rao lower bound expressions of the Root Mean Square Error（RMSE）is proposed.According to the three different circumstances of the WSN,the positioning schemes with different convex relaxation are respectively proposed,which improve the robustness of the algorithm.Through simulation and comparison with the existing scheme display,the proposed scheme improve the performance of RMSE in the evaluation index,and not too much increase the computational complexity of the algorithm.