Medium PRF radar PRF selection using evolutionary algorithms

Evolutionary algorithms are applied to the optimization of pulse repetition frequency (PRF), for both eight-and nine PRFs, in medium PRF radar while considering the detailed effects of sidelobe clutter and many other technical factors. The algorithm presented also ensures that all the solutions produced are fully decodable and have no blind velocities. The evolutionary algorithm was able to identify near-optimum PRF sets for a realistic radar system with only a modest computational effort.     

Performance comparison of PRF schedules for medium PRF radar

Previous work has shown how evolutionary algorithms (EAs) are an effective tool in optimising the selection of pulse repetition frequency (PRF) values of medium PRF schedules in an airborne fire control radar (FCR) application requiring target data in three PRFs. The optimisation is driven by the requirement to minimise range/Doppler blindness whilst maintaining full decodability. In this paper we detail work in which the optimisation process is applied to design novel short medium PRF schedules requiring target data in just two PRFs. The paper reports on the testing of a variety of near-optimum schedules to compare their blindness, decoding, and ghosting performances. The results show that in many situations, the 2 of N schedules are a practical alternative to conventional 3 of N processing.