Local Low Range Sidelobes Waveform Design with Cognitive Levels Using Particles Swarm Projection Optimization

In modern electronic warfare, radar with knowledge-aided waveforms has shown significant flexibility. In this paper, the method named Particles Swarm Projection Optimization (PSPO), is introduced to design local low range sidelobes waveform under non-convex constraint and randomized initialization. Firstly, the mathematical problem corresponding to multiple non-cooperative targets or interference is formulated considering different threat levels. Furthermore, using the alternating direction decomposition idea, the original problem is divided into triple-variable ones, which could be solved via particles projection. Here, PSPO assisted by swarm intelligence and learning factor, would enhance the global optimization convergence under unimodular non-convex constraint. Finally, simulations and numerical results show comparisons with several other methods.