Scholarlink

<p>Time Delay Estimation (TDE) between signals can be addressed within the general framework of statistical signal processing, particularly through the use of the cross-correlation function of the signals involved. This paper is divided into two main parts. The first one highlights the existing solutions for TDE methods. In the second part, a straightforward example of TDE from a sonar application is considered and analyzed under imposed and simplified conditions of the processed signals. Recognizing that the estimations of TDE in sonar applications are biased when the processed signals have different durations, this paper proposes a solution to reduce this bias. The principle of the proposed method involves compressing the received signal’s envelope. This method consists of three steps: estimating the start point, estimating the endpoint, and compressing the received signal. Experiments based on computer simulations under various Signal-to-Noise Ratios (SNRs) and signal widths demonstrate the feasibility of the method by reducing bias in estimations and expanding the range of SNR for valid estimations, with a lower limit reaching down to 0 dB. This method is considered as an example solution to the problem of bias in estimating TDE of signals with different widths.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Some Aspects of Time Delay Estimation Based on Cross-Correlation

  • 期刊论文

  • 发表日期：

    2025年9月4日

查看全文
  • Dorel Aiordachioaie

摘要

Time Delay Estimation (TDE) between signals can be addressed within the general framework of statistical signal processing, particularly through the use of the cross-correlation function of the signals involved. This paper is divided into two main parts. The first one highlights the existing solutions for TDE methods. In the second part, a straightforward example of TDE from a sonar application is considered and analyzed under imposed and simplified conditions of the processed signals. Recognizing that the estimations of TDE in sonar applications are biased when the processed signals have different durations, this paper proposes a solution to reduce this bias. The principle of the proposed method involves compressing the received signal’s envelope. This method consists of three steps: estimating the start point, estimating the endpoint, and compressing the received signal. Experiments based on computer simulations under various Signal-to-Noise Ratios (SNRs) and signal widths demonstrate the feasibility of the method by reducing bias in estimations and expanding the range of SNR for valid estimations, with a lower limit reaching down to 0 dB. This method is considered as an example solution to the problem of bias in estimating TDE of signals with different widths.