An Adaptive ISAR-Imaging-Considered Task Scheduling Algorithm for Multi-Function Phased Array Radars

In multi-function phased array radar (MFPAR) systems, time and energy resources are allocated for different tasks so that the radar can perform various missions simultaneously. An effective scheduling algorithm is crucial to optimizing the overall performance of the MFPAR. There are various existing adaptive resource scheduling methods for the allocation of radar resources, but none of them consider the mission of imaging, a very important task. In this paper, an adaptive ISAR-imaging-considered task scheduling algorithm is proposed. Based on the sparse-aperture ISAR Compressive Sensing (CS) cognitive imaging techniques, the required resources for target imaging can be calculated from the online cognition of the target characteristics. Then the imaging mission is considered in the resource scheduling optimization model to realize adaptive allocation of radar resources and high-resolution imaging of multi targets. With the proposed algorithm, different tasks, such as tracking, searching and imaging, etc. can be implemented simultaneously, thus the radar efficiency is significantly improved. The effectiveness of the proposed method will be demonstrated by simulation experiments.