Time and Aperture Resource Allocation Strategy for Multitarget ISAR Imaging in a Radar Network

In modern high-dynamic battlefield environments, the time and aperture resources of multifunction radar systems are often viewed as important system resources. In this paper, a time and aperture resource allocation strategy for multitarget inverse synthetic aperture radar (ISAR) imaging that incorporates requirements for distributed network radar multitarget imaging tasks is proposed to improve the efficiency of a radar system. First, the resolution requirement of the target is determined based on the feature recognition of the target, and an allocation model of the aperture resource for the distributed networking conditions is established by analyzing the relationship between the resolution and the aperture resource. Second, by analyzing the requirements of target sparse ISAR imaging, time resources are incorporated into the resource allocation model. Third, a multiobjective function model for the multitarget imaging of networked radars with the least resource consumption and the largest number of imaging tasks is established. Finally, the objective function is sorted according to the degree of importance by a lexicographic strategy, and a lexicographic genetic algorithm is proposed to solve the optimization problem. The simulation results show that the proposed algorithm outperforms the traditional algorithm in terms of the effective utilization of radar resources and the radar system performance.