摘要
Abstract
In order to address the drawbacks of slow convergence and high computational complexity caused by the non-convex nature in traditional received signal strength indicator(RSSI)-based maximum likelihood esti-mation(ML-RSSI)for military scenarios,this paper proposes a high-accuracy,low-complexity RSSI-based maxi-mum likelihood node localization(MLNL-RSSI)method.First,the objective function is established based on RS-SI ranging.To tackle its non-convex and non-continuous characteristics,it is transformed into an optimizable form through convex relaxation and continuity processing.Finally,the gradient descent method is employed to efficient-ly solve the position of the target node,thus significantly reducing computational complexity.Simulation results demonstrate that,compared with existing similar methods,the MLNL-RSSI method,while ensuring positioning accuracy,can significantly enhance the convergence speed,has higher computational efficiency,and is more adapt-able to the strict requirements of military tasks for real-time performance and resource constraints.关键词
无线传感网络/节点定位/接收信号强度指示/最大似然/凸松驰Key words
wireless sensor networks/node localization/received signal strength indicator/maximum likeli-hood/convex relaxation分类
信息技术与安全科学
