Improved Sine Cosine Algorithm for Estimating Parameters of Sine Signals

When the sampling time is limited, it becomes challenging to determine the parameters of overlapping sinusoidal signals with similar frequencies using traditional Fast Fourier Transform (FFT) algorithms. In this paper, we propose a step-by-step solution method. Firstly, we employ the modified covariance method to estimate the frequencies of the signals. Next, we introduce the concept of Simulated Annealing (SA) into the Sine Cosine Algorithm (SCA). Consequently, we propose a fusion algorithm, called the Simulated Annealing Sine Cosine Algorithm (SASCA), to determine parameters such as amplitude and initial phase. Simulation results demonstrate that the step-by-step solution method proposed in this paper effectively estimates each parameter of the sinusoidal signal while exhibiting notable noise immunity. Furthermore, SASCA performs better than SCA.