Fast antenna deployment method for multistatic radar with multiple dynamic surveillance regions

In this paper, we consider an optimal antenna deployment problem for distributed multistatic radar under the situation of multiple surveillance regions in a dynamic environment. The problem is solved by proposing a dynamic multi-objective particle swarm optimization (DMOPSO) with the assistance of the proposed Kalman filtering prediction strategy. Firstly, we construct a dynamic multi-objective optimization problem for antenna deployment by choosing the effective coverage rates of different non-fixed surveillance regions as objective functions. Then, to avoid the unnecessary computational load for solving optimization problem and improve the real-time property of antenna deployment, a DMOPSO algorithm based on the Kalman filtering prediction strategy is proposed by extracting the relationships among adjacent optimization time segments. Finally, numerical results are provided to verify the validity of the proposed DMOPSO algorithm.