Baghel V.Panda G.Srihari P.Rajarajeswari K.Majhi B.2025-02-112009http://dx.doi.org/10.1109/NABIC.2009.5393761https://idr.iitbbs.ac.in/handle/2008/21The 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 multiobjective genetic algorithm (NSGA-II). The pulse compression performance of three different codes in terms of signal to peak side-lobe ratio (SSR) under noisy environmentrange 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 multiobjective method compared to its counterparts. As the number of center increasesthe 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. �2009 IEEE.enGenetic algorithmMultiobjective optimizationPulse compressionRange resolutionRBF networksConference Paper