Distributed UAV Swarm Placement Optimization for Compressive Sensing based Target Localization

被引:0
作者
Wang, Yen-Chin [1 ]
Cabric, Danijela [1 ]
机构
[1] Univ Calif Los Angeles, Elect Engn Dept, Los Angeles, CA 90024 USA
来源
2023 INTERNATIONAL CONFERENCE ON COMPUTING, NETWORKING AND COMMUNICATIONS, ICNC | 2023年
关键词
Unmanned aerial vehicle (UAV); compressive sensing; MIMO radar; localization; MEASUREMENT MATRIX DESIGN; MIMO RADAR; POWER ALLOCATION;
D O I
10.1109/ICNC57223.2023.10074263
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Cooperative target localization using unmanned aerial vehicles (UAVs) swarm is gaining popularity in many applications such as disaster detection, crowd surveillance, and rescue operation. In this paper, a UAV swarm, featuring a single antenna RF transceiver per UAV, is considered and regarded as a distributed MIMO radar system for a problem of target localization. To reduce the number of measurements and computational complexity, the compressive sensing based (CS-based) algorithm is applied. In most of the existing works in radar community, the assumption of fixed radar positions is adopted. Here, by exploiting the mobility of the UAV swarm, we propose two UAV placement optimization algorithms to improve the performance of CS-based target localization. Simulation results show that compared to the random UAV placement, the mutual coherence of the measurement matrix is reduced and the localization root mean square error (RMSE) is significantly improved under the proposed UAV placement. Moreover, the RMSE performance can be further improved by increasing the number of UAVs.
引用
收藏
页码:547 / 551
页数:5
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