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Receiver Deployment Optimization for Satellite Illuminator-Based Forward Scatter Radar
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DOI：10.1109/taes.2026.3713118.png)
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Abstract
En 中文
This article addresses receiver deployment optimization for passive forward scatter radar (FSR) using satellite illuminators. To quantify boundary crossing surveillance, we introduce the fence detection area, a physically derived metric obtained from satellite, target, and receiver geometry and the FSR signal-to-noise ratio threshold, and use it to characterize the effective detection region on the surveillance boundary. Based on this metric, static and dynamic deployment models are formulated to jointly account for receiver locations, transmitter and receiver pairing, coverage ratio constraints, deployment cost, and, in the dynamic case, switching cost over satellite motion. To solve the resulting nonconvex mixed discrete and continuous problems, an Improved Artificial Lemming Algorithm (Imp-ALA) is used as a problem-specific solver with redundancy elimination, feasibility repair, and greedy output correction. Numerical simulations show that the proposed metric captures fence type coverage more faithfully than geometric simplifications, and that Imp-ALA achieves a better balance among receiver number, coverage robustness, switching behavior, and normalized computational cost than the baseline artificial lemming algorithm, genetic algorithm, and particle swarm optimization. A small-scale exact solver validation further confirms the solution quality, and the formulation can accommodate target-dependent radar cross section models, signal-to-interference-plus-noise-ratio (SINR)-based interference constraints, and cooperative detection rules across multiple stations.
Keywords:
Deployment optimization
forward scatter radar (FSR)
radar coverage
receiver (Rx) deployment
satellite illuminator
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5.7
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651
Citations:
2.4W
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