SEAD (suppression of enemy air defenses) is a typical application scenario of multi-UAV cooperation. Based on the characteristics of this scenario, the number of different types of UAV was also used as a decision variable in the task planning problem, fully characterizing the various constraints of the target, mission, and UAV, and establishing a heterogeneous UAV formation path problem model. A two-layer joint optimization method was designed to solve the model: the upper layer was designed with the task connection impact indicator to accurately assess the quantitative requirements of various types of UAVs and guide UAVs configuration adjustments; the lower layer improved the genetic algorithm, which can efficiently handle multiple coupling constraints and can accurately adjust the mission plan in conjunction with UAV quantity changes. The two layers coordinate with each other to obtain a UAV configuration and mission execution plan that meet the requirements. Simulation results show that the method can obtain a reasonable UAV configuration plan without traversing various UAV configurations, while obtaining an efficient and feasible mission execution plan.

The flexibility of UAV in structural style and material composition makes it have more space for stealth performance optimization than the manned aircraft, so it was urgent to carry out near-field imaging indoors or outdoors. Based on the imaging geometry model of aircraft turntable, a general signal model of near-field turntable imaging was established, and a near-field frequency-domain imaging algorithm for aircraft electromagnetic scattering feature diagnosis was proposed. Under the constraint of sub aperture imaging setting, the slant plane spectrum was approximately processed as the horizontal plane spectrum; the applicable conditions of the algorithm was analyzed, and simulation data around typical near-field imaging geometry and aircraft size was generated. The completes near-field imaging in the range of 0.6~35 GHz was performed. Good imaging results confirm the correctness of the theoretical analysis and the proposed algorithm.