Transmit-Receive Assignment and Path Planning of Multistatic Radar-Enabled UAVs for Target Tracking in Stand-Forward Jamming

Target tracking in stand-forward swarm jamming for unmanned aerial vehicles (UAVs) is a promising topic but the relevant research is tepid. This article aims at exploring this problem for multistatic radar-enabled UAVs (RUAVs) via a multiagent cooperative sensing and control scheme, in which all RUA...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2024-10, Vol.60 (5), p.5702-5714
Main Authors: Xiong, Kui, Cui, Guolong, Liao, Maosen, Gan, Linchuan, Kong, Lingjiang
Format: Article
Language:English
Subjects:
Algorithms
Coalition game
Cooperative control
Cramer-Rao bounds
Jamming
Lower bounds
Multiagent systems
Multistatic radar
multistatic radar-enabled UAVs (RUAVs)
Optimization
Particle swarm optimization
Path planning
Radar
Radar equipment
Radar tracking
Receivers
stand-forward jamming
Target tracking
Task analysis
Transmitters
transmit–receive task assignment
Unmanned aerial vehicles
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Summary:Target tracking in stand-forward swarm jamming for unmanned aerial vehicles (UAVs) is a promising topic but the relevant research is tepid. This article aims at exploring this problem for multistatic radar-enabled UAVs (RUAVs) via a multiagent cooperative sensing and control scheme, in which all RUAVs constitute a multistatic radar system with variable and movable transmitting and receiving platforms, and each RUAV as an autonomous agent makes decision with other agents for transmit–receive task assignment and path planning to seek the optimal overall target tracking performance. The optimization problem of RUAVs is formulated as minimizing the Bayesian Cramér–Rao lower bound with some practical constraints. To solve this problem, an alternating iterative optimization scheme is presented, in which the coalition formation method is applied for transmit–receive task assignment and the improved particle swarm optimization (PSO) method is devised for path planning. The alternating coalition formation and PSO (ACFPSO) algorithm is, therefore, proposed for RUAVs for target tracking in stand-forward jamming. Numerical simulations in the typical scenario are conducted to verify the effectiveness and superiority of the ACFPSO algorithm from aspects of tracking accuracy and jamming elimination.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2024.3394794