Task Scheduling for Multi-Target ISAR Imaging in Radar Network

Abstract

For radar imaging of multiple targets in radar network, it is necessary to schedule the imaging tasks among various radars at suitable time to achieve high performance under limited radar resources. In this paper, based on the image quality requirement, a task schedule method is proposed for multi-target inverse synthetic aperture radar (ISAR) imaging in radar network. Due to the image resolution is an important indicator of image quality and the imaging task is time sensitive, the relationship between the imaging resolution and task time is studied firstly. Thereafter, the task scheduling problem is converted into an optimization problem with time window constrains and an improved Quantum Genetic Algorithm (IQGA) is proposed to solve the problem. Then the task scheduling strategy which contains how to allocate the targets to the radars and when to observe the targets can be obtained. Finally, simulation results verify the effectiveness of the proposed method. With the help of the propose method, the multi-target ISAR task can be completed effectively and the resource utilization of the radar network can be improved. INDEX TERMS Radar network, multi-target imaging, task scheduling optimization, time window, improved quantum genetic algorithm (IQGA).

Phased-Array Radar Task Scheduling Method for Hypersonic-Glide Vehicles

“…The time utilization rate is the ratio of the sum of the dwell time of the successfully scheduled radar task to the length of the scheduling interval [23]. As shown in (13), i t R is the time utilization rate for the i-th scheduling interval.…”

Resource scheduling algorithm optimization for multitarget inverse synthetic aperture radar imaging in radar network

“…[12][13][14] The model established in Ref. 15 optimizes resource allocation for multiobjective imaging tasks in radar networks, but it uses the traditional Rang-Doppler (RD) imaging algorithm, which, although effective for traditional algorithm, is not as superior as CS. An allocation method of resource scheduling based on sparse observation ISAR imaging was proposed in Ref.…”