On the Invariance of Cross-Correlation Peak Positions Under Monotonic Signal Transformations, with Application to Fast Time Difference Estimation

Fuente: arXiv
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Main Authors: Ueno, Natsuki, Sato, Ryotaro, Ono, Nobutaka
Format: Preprint
Published: 2025
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author Ueno, Natsuki
Sato, Ryotaro
Ono, Nobutaka
author_facet Ueno, Natsuki
Sato, Ryotaro
Ono, Nobutaka
contents We present a theorem concerning the invariance of cross-correlation peak positions, which provides a foundation for a new method for time difference estimation that is potentially faster than the conventional fast Fourier transform (FFT) approach for real/complex sequences. This theoretical result shows that the peak position of the cross-correlation function between two shifted discrete-time signals remains unchanged under arbitrary monotonic transformations of the input signals. By exploiting this property, we design an efficient estimation algorithm based on the cross-correlation function between signals quantized into low-bit integers. The proposed method requires only integer arithmetic instead of real-valued operations, and further computational efficiency can be achieved through number-theoretic algorithms. Numerical experiments demonstrate that the proposed method achieves a shorter processing time than conventional FFT-based approaches.
format Preprint
id arxiv_https___arxiv_org_abs_2509_19974
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle On the Invariance of Cross-Correlation Peak Positions Under Monotonic Signal Transformations, with Application to Fast Time Difference Estimation
Ueno, Natsuki
Sato, Ryotaro
Ono, Nobutaka
Signal Processing
Audio and Speech Processing
We present a theorem concerning the invariance of cross-correlation peak positions, which provides a foundation for a new method for time difference estimation that is potentially faster than the conventional fast Fourier transform (FFT) approach for real/complex sequences. This theoretical result shows that the peak position of the cross-correlation function between two shifted discrete-time signals remains unchanged under arbitrary monotonic transformations of the input signals. By exploiting this property, we design an efficient estimation algorithm based on the cross-correlation function between signals quantized into low-bit integers. The proposed method requires only integer arithmetic instead of real-valued operations, and further computational efficiency can be achieved through number-theoretic algorithms. Numerical experiments demonstrate that the proposed method achieves a shorter processing time than conventional FFT-based approaches.
title On the Invariance of Cross-Correlation Peak Positions Under Monotonic Signal Transformations, with Application to Fast Time Difference Estimation
topic Signal Processing
Audio and Speech Processing
url https://arxiv.org/abs/2509.19974