Resource Scheduling for Multitarget Imaging in a Distributed Netted Radar System Based on Maximum Scheduling Benefits.

As a new radar system with improved performance, distributed multiple-input multiple-output (MIMO) radar provides a new idea for the development of netted radar. Aiming at the limited resource allocation problem of netted radar, this paper extends the idea of distributed MIMO radar to netted radar and proposes a resource scheduling algorithm for multitarget imaging in distributed netted radar based on the maximum scheduling benefits. Under the condition of the cognition of the target characteristics, the algorithm comprehensively considers the angle and dwell time to complete the multiradar and multitarget matching. Then it uses the principle of compressed sensing to calculate the pulse resources required for sparse imaging of each target on the corresponding radar. In this paper, the scheduling benefit of a radar system is expressed by weighting the three factors of the scheduling success rate, the hit value rate and the pulse resource consumption rate. The resource scheduling model is established according to the maximum scheduling benefits and solved using a heuristic algorithm. The simulation results show that compared with the traditional algorithm, this method improves the scheduling benefits of the radar system.