A novel approach to improve merit factor values using Rudin-Shapiro and m-sequences

Abstract

LABS stand for low autocorrelation binary sequence. LABS detection is a classic problem in the literature. LABS are used in Radar pulse compression techniques to improve the visibility of the targets. As the autocorrelation value decreases, the ability of the radar to detect multiple targets increases. Since 1950's numerous methods were developed to solve LABS problem[13]. In the present case Rudin Shapiro and m-sequences were used to generate LABS. Research has been done previously on this topic by Jonathan Jedwab [1]. Jedwab considered Peak side lobe levels (PSL) to measure the quality of LABS [2]. We simultaneously introduced Merit Factors to analyze the sequences. We improvised his work by obtaining better merit factors for both of the sequences with the help of diverse sequence lengths (3m-1).