Task Allocation Optimization for Multi-Target ISAR Imaging in Radar Sensor Network

Abstract

Inverse synthetic aperture radar imaging techniques, which can provide the fine structure of the targets for subsequent identification, have been a hot topic in recent years. When multiple targets appeared in the detection coverage of the radar sensor network, it is necessary to study the task allocation strategy of the multi-target inverse synthetic aperture radar (ISAR) imaging tasks to obtain high-quality ISAR images under the limited radar resources. Obviously, there are competitions among the targets for radar resources to obtain high-quality ISAR images. The purpose of the task allocation optimization game is to accomplish the multi-target ISAR imaging tasks with higher quality under limited radar resources. After analyzing the relationship of ISAR image quality and radar resource, the task allocation optimization problem can be constructed as a non-cooperative game problem, where the targets are the players. Then a genetic algorithm is applied to search the optimal solution of the game, where is also termed as Nash equilibrium solution. Simulation results verify the effectiveness of the proposed method.