主被动协同定位空能资源优化配置方法

doi:10.19665/j.issn1001-2400.20240102

Abstract

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.

Key words: cooperative localization, time difference of arrival, round-trip time of arrival, improved gray wolf optimization, joint optimization algorithm

CLC Number:

TN92

LYU Peixia, ZHAO Yue, LI Zan, BAI Dou, HAO Benjian. Algorithm for optimization of joint spatial and power resources for cooperative active and passive localization[J].Journal of Xidian University, 2024, 51(4): 29-38.

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References 26

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算法名称	测距车位置/km	辐射功率分配/W	平均CRLB/m	平均定位精度增量/m
GWO	(1.72,1.96,0);(1.94,2.11,0);(2.04,1.83,0)	90.02;98.07;90.92	0.773	91.425
IGWO	(2.34,2.37,0);(2.60,2.52,0);(2.52,2.41,0)	89.69;91.11;89.20	0.756	91.537
CM-IGWO	(2.40,2.27,0);(2.37,2.58,0);(2.34,2.52,0)	89.94;89.96;90.10	0.534	91.539
UDO	(3.00,3.37,0);(1.50,2.50,0);(3.00,1.63,0)	90;90;90	16.094	89.427

Algorithm for optimization of joint spatial and power resources for cooperative active and passive localization

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