Detection of a real sinusoid in noise using differential evolution algorithm

Abstract

Detection of sinusoidal signals embedded in noise is a pertinent problem in applications such as radar and sonar, communication systems and defense, to name a few. This paper, describes the detection of a real sinusoid in additive white Gaussian noise (AWGN) using the Differential Evolution Algorithm (DE). The performance of DE is evaluated for different sampling rates and also for different signal-to-noise ratios (SNR). The proposed DE which combines two DE strategies enhances the detection performance compared to the original DE algorithm. We show that the detection performance of the proposed algorithm is superior to previously reported methods, especially at low SNR.