西安电子科技大学学报（自然科学版）2024，Vol.51Issue(4)：29-38,10.DOI:10.19665/j.issn1001-2400.20240102
主被动协同定位空能资源优化配置方法
Algorithm for optimization of joint spatial and power resources for cooperative active and passive localization
摘要
Abstract
The rapid development of UAVs has brought great convenience to today′s society,but their potential misuse poses a risk to public safety.As a result,in recent years,surveillance and localization technologies for UAVs have been widely studied.In response to the application problem of difficulty in accurate localization of long-range low-flying UAVs,a cooperative localization framework is proposed,mainly for passive localization,and it is supplemented by active detection.Based on the passive localization using the time difference of arrival(TDOA),the active detection equipment supporting round-trip time of arrival(RT-TOA)measurement is introduced to locate the UAVs opportunistically and actively.These devices compensate for the missing target elevation information of passive localization,to improve the three-dimensional localization accuracy of UAVs.This paper delves into the spatial and power sources allocation methods for active localization nodes under the pre-deployment of passive localization nodes.Under the framework of cooperative localization,it derives the localization accuracy measurement indicator and formulates the joint optimization problem for spatial and power resources.A resource optimization algorithm for improved gray wolf optimization based on nonlinear convergence factors and memory guidance(CM-IGWO)is proposed.Simulation results show that the active and passive cooperative localization effect is better than the passive localization effect,and that the elevation localization accuracy in typical scenarios is significantly improved by 96.33% .In addition,the proposed CM-IGWO algorithm is superior to the gray wolf optimization(GWO)and IGWO when solving the joint optimization problem for spatial and power resources.关键词
协同定位/到达时间差/往返到达时间/改进灰狼优化/联合优化Key words
cooperative localization/time difference of arrival/round-trip time of arrival/improved gray wolf optimization/joint optimization algorithm分类
电子信息工程引用本文复制引用
吕佩霞,赵越,李赞,白豆,郝本建..主被动协同定位空能资源优化配置方法[J].西安电子科技大学学报（自然科学版）,2024,51(4):29-38,10.基金项目
国家重点研发计划(2022YFC3301300) （2022YFC3301300）
国家自然科学基金(62101403) （62101403）
国家杰出青年科学基金(61825104) （61825104）
