Enhancing multi-target detection in low SNR conditions

Electronic Warfare is a type of military operation that uses electromagnetic radiation to identify, exploit, limit, or prohibit the use of the electromagnetic spectrum. The main objective of this paper is to improve the range resolution of multiple targets in Electronic Warfare systems under noisy conditions. Multiple Signal Classification (MUSIC), a high-resolution algorithm is used with denoising techniques to enhance the ability of digital receivers to detect multiple targets. The Savitzky Golay filter is used in the first stage as a pre-processing filter, and the novel noise removal technique is used in the second stage to achieve better target detection and discrimination. This modification to the MUSIC algorithm aims to address its limitations in the presence of noise and when targets are in proximity, resulting in improved performance in Electronic Warfare scenarios. Using the proposed method, we are able to detect three (3) target frequencies up to SNR of − 12 dB and four (4) target frequencies up to SNR of − 19 dB, with the percentage of error in the estimation of frequency is 0.58%. The optimized computation complexity is highlighted as a strength, making the proposed method more efficient compared to alternative approaches.