Radar Task Scheduling Based on Stochastic Fractal Search

Task scheduling for radar resource management is an NP-hard problem due to the complexity of task parameter optimization. Approximate optimal solutions can be obtained by classical heuristic algorithms, but take a relatively long time. In this paper, a radar task scheduling method based on Stochastic Fractal Search (SFS) algorithm is proposed. The problem model is presented under the Quality of Service based resource allocation and management (Q-RAM) framework in order to ensure the overall mission effectiveness. We modified the SFS algorithm to fit the Q-RAM framework with a transformation strategy to unify the search space for different task parameters. The effectiveness of our method is verified by simulation experiments. Results show that, comparing to the other methods, our method can achieve approximately optimal scheduling performance while significantly reducing the calculation time.