Implementation of Multi-Objective Grey Wolf Optimizer to Minimize The Sidelobes And Reduce Mainlobe Width

Abstract

Range resolution in radar can be achieved by splitting the long pulse of high energy into the high bandwidth of short pulses using pulse compression technique. Frequency modulation (Linear frequency modulation (LFM)) signal is used to improve range resolution. To get better range resolution, frequency step is introduced between a train of LFM pulses known as stepped frequency pulse train (the SFPT). The SFPT suffers from grating lobes when the product of sub-pulse duration and frequency step becomes more than one. The grating lobes and sidelobes present in the vicinity of the mainlobe. It can cause the false alarm detection and hide the small targets. In this work, Multi-Objective Grey Wolf Algorithm (MOGWO) is used to set the parameters of SFPT to mitigate the grating lobes and minimize the sidelobes at the matched filter output. Trade-off solutions between sidelobes versus grating lobes and mainlobe width versus sidelobes are obtained using the Pareto front for different ranges of SFPT parameters.