TY - EJOU AU - Rosli, Siti Julia AU - Rahim, Hasliza A AU - Rani, Khairul Najmy Abdul AU - Ngadiran, Ruzelita AU - Mustafa, Wan Azani AU - Jusoh, Muzammil AU - Yasin, Mohd Najib Mohd AU - Sabapathy, Thennarasan AU - Abdulmalek, Mohamedfareq AU - Ariffin, Wan Suryani Firuz Wan AU - Alkhayyat, Ahmed TI - A Hybrid Modified Sine Cosine Algorithm Using Inverse Filtering and Clipping Methods for Low Autocorrelation Binary Sequences T2 - Computers, Materials \& Continua PY - 2022 VL - 71 IS - 2 SN - 1546-2226 AB - 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. KW - Merit factor; autocorrelation; skew-symmetric sequences; combinatorial optimization; sine cosine algorithm; cuckoo search algorithm; radar system; wearable antenna; antenna and propagation DO - 10.32604/cmc.2022.021719