A Fast Electromagnetic Scattering Solution Restoration Method for Swarm Targets Based on Modified Empirical Interpolation Method

Noncooperative Uncrewed Aerial Vehicles (UAV) proposes high threats to public safety and require radar systems possess sufficient surveillance capabilities. The evolvement of swarm formulations further elevates the surveillance difficulty. Massive swarm target Radar Cross Section (RCS) data collection is fundamental to study radar signatures of swarm targets for UAVs and birds. Numerical simulation with fast solution restoration assistance is currently the optimum solution to conduct massive swarm target RCS data collection. This paper introduces a modified Empirical Interpolation Method (EIM) to optimize existing RCS restoration method using Equivalent Principle Analysis (EPA) and EIM. The modified EIM adds orthogonality maximization principle in basis function selection, and the Fruit Fly Optimization Algorithm (FOA) is embedded in interpolation point selections. Results reveal that basis functions and interpolation points from modified EIM could better span the solution space. RCS restoration accuracy reflects prominent elevation especially for swarm target with high complexity. Extra computation resource consumptions have minor impacts on offline training, and online RCS restoration performance is not influenced by the proposed method.