Open Access

ARTICLE

A Hybrid Modified Sine Cosine Algorithm Using Inverse Filtering and Clipping Methods for Low Autocorrelation Binary Sequences

by Siti Julia Rosli^1,2, Hasliza A Rahim^1,2,*, Khairul Najmy Abdul Rani^1,2, Ruzelita Ngadiran^2,3, Wan Azani Mustafa^3,4, Muzammil Jusoh^1,2, Mohd Najib Mohd Yasin^1,2, Thennarasan Sabapathy^1,2, Mohamedfareq Abdulmalek⁵, Wan Suryani Firuz Wan Ariffin², Ahmed Alkhayyat⁶

1 Advanced Communication Engineering, Centre of Excellence (ACE), Universiti Malaysia Perlis (UniMAP), 01000 Kangar, Perlis, Malaysia
2 Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis (UniMAP), 02600 Arau, Perlis, Malaysia
3 Advanced Computing (AdvCOMP), Centre of Excellence, Universiti Malaysia Perlis (UniMAP), 02600 Arau, Perlis, Malaysia
4 Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis (UniMAP), 02600 Arau, Perlis, Malaysia
5 Faculty of Engineering and Information Science, University of Wollongong in Dubai, Dubai 20183, United Arab Emirates
6 Department of Computer Technical Engineering, College of Technical Engineering, the Islamic University, 54001 Najaf, Iraq

* Corresponding Author: Hasliza A Rahim. Email:

Computers, Materials & Continua 2022, 71(2), 3533-3556. https://doi.org/10.32604/cmc.2022.021719

Received 12 July 2021; Accepted 19 October 2021; Issue published 07 December 2021 Retracted 30 August 2023

Abstract

The essential purpose of radar is to detect a target of interest and provide information concerning the target's location, motion, size, and other parameters. The knowledge about the pulse trains’ properties shows that a class of signals is mainly well suited to digital processing of increasing practical importance. A low autocorrelation binary sequence (LABS) is a complex combinatorial problem. The main problems of LABS are low Merit Factor (MF) and shorter length sequences. Besides, the maximum possible MF equals 12.3248 as infinity length is unable to be achieved. Therefore, this study implemented two techniques to propose a new metaheuristic algorithm based on Hybrid Modified Sine Cosine Algorithm with Cuckoo Search Algorithm (HMSCACSA) using Inverse Filtering (IF) and clipping method to achieve better results. The proposed algorithms, LABS-IF and HMSCACSA-IF, achieved better results with two large MFs equal to 12.12 and 12.6678 for lengths 231 and 237, respectively, where the optimal solutions belong to the skew-symmetric sequences. The MF outperformed up to 24.335% and 2.708% against the state-of-the-art LABS heuristic algorithm, xLastovka, and Golay, respectively. These results indicated that the proposed algorithm's simulation had quality solutions in terms of fast convergence curve with better optimal means, and standard deviation.

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Keywords

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