High-Precision Time Delay Estimation Algorithm Based on Generalized Quadratic Cross-Correlation

Source abstract

In UAV target localization, the accuracy of time delay estimation is the key to high-precision positioning. However, under low signal-to-noise ratio (SNR), time delay estimation suffers from serious secondary peak interference and low accuracy, which degrades the positioning accuracy. This paper proposes an improved time delay estimation algorithm based on generalized quadratic cross-correlation. By introducing exponential operations and Hilbert difference operation, suppressing noise interference, and sharpening the peaks of the signal correlation function, the algorithm improves the estimation accuracy. Through simulation experiments comparing with the generalized cross-correlation and quadratic correlation algorithms, the results show that the improved algorithm enhances the peak of the cross-correlation function, improves the accuracy of estimation, and exhibits better anti-noise performance in low SNR environments, providing a new approach for high-precision time delay estimation in complex signal environments.