Time Delay Estimation Algorithm Based on Cross-Correlation Analysis

This paper presents a time delay estimation algorithm based on cross-correlation analysis. The core methodology involves estimating signal delays by comparing the cross-correlation function between a signal and its time-shifted version. This technique is widely applied in signal processing domains, particularly in acoustic and image processing applications. The algorithm implementation typically involves computing the cross-correlation function using Fast Fourier Transform (FFT) for computational efficiency, where the peak position in the correlation result indicates the time delay. Key functions include signal preprocessing, zero-padding for accurate frequency domain conversion, and peak detection algorithms for precise delay identification. By implementing this approach, we can achieve more accurate delay estimations, thereby enhancing the precision and efficiency of data analysis and processing tasks. The MATLAB implementation commonly utilizes xcorr() function for cross-correlation computation and findpeaks() for delay extraction.