Separation of Signals with Same Frequency Based on Improved Bird Swarm Algorithm

In view of the problem that the same frequency interference accrued to shipborne radar frequently in complex battlefield environment, a separation method of the same frequency signals based on improved bird swarm algorithm (IBSA) is proposed. The algorithm optimizes the initial value of the bird swarm algorithm (BSA) by using a "reverse learning" mechanism, and calculates the reverse population in the process of optimization dynamically, and increases the global search capability of the algorithm. The dynamic weight is introduced into the foraging formula of BSA to increase the search efficiency of the algorithm. And the improved bird swarm algorithm combined with independent component analysis of non-Gauss maximization is applied to the same frequency interference resistance for shipborne radar, and achieved good results. According to two criteria of signal separation and evaluation, giving a new evaluation criterion based on the set pair analysis, and the effectiveness of the improved bird swarm optimization model is proved to be effective in the solving problem of radar signal separation with same frequency. It provides a solution for problem that anti same frequency interference of ship-borne radar.