An efficient multi-objective pulse radar compression technique using RBF and NSGA-II

The task of radar pulse compression is formulated as a multi-objective optimization problem and has been effectively solved using radial basis function (RBF) network and multi-objective genetic algorithm (NSGA-II). The pulse compression performance of three different codes in terms of signal to peak side-lobe ratio (SSR) under noisy environment, range resolution and Doppler shift are evaluated through exhaustive simulation study and are compared with those obtained by radial basis function (RBF) and auto correlation (ACF) based methods. The results demonstrate excellent performance of the proposed multi-objective method compared to its counterparts. As the number of center increases, the performance compressor also progressively increases but its complexity correspondingly increases. The proposed multi-objective method helps to select appropriate structure that makes a judicious compromise between the complexity and performance.