Evidence map›Paper›PMID 41258125›Full record

ArticleScientific reports2025

Experimental analysis of time difference of arrival estimates based on inexactly reconstructed signals.

Shanhe Wang, Changjiang Huang, Yu Xiang, Yuanyuan Gao, Xian Zhao, Yu Hua

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Shanhe WangNational Time Service Center, Chinese Academy of Sciences, Xi'an, 710600, Shaanxi, China.
Changjiang HuangNational Time Service Center, Chinese Academy of Sciences, Xi'an, 710600, Shaanxi, China. huangcj@ntsc.ac.cn.
Yu XiangNational Time Service Center, Chinese Academy of Sciences, Xi'an, 710600, Shaanxi, China.
Yuanyuan GaoNational Time Service Center, Chinese Academy of Sciences, Xi'an, 710600, Shaanxi, China.
Xian ZhaoNational Time Service Center, Chinese Academy of Sciences, Xi'an, 710600, Shaanxi, China.
Yu HuaNational Time Service Center, Chinese Academy of Sciences, Xi'an, 710600, Shaanxi, China.

Funding

Basic Research Program of Natural Sciences of Shaanxi Province 2024JC-DXWT-01
6 · The paper itself

Abstract

Time Difference of Arrival (TDOA) estimation is a pivotal technique with extensive applications across various domains, including passive detection and indoor positioning. For signals characterized by unknown modulation types and originating from non-cooperative sources, achieving high-precision TDOA estimation traditionally necessitates a substantial volume of sampling data. Conventional approaches, such as cross-correlation, require high sampling rates and extended durations, posing significant challenges in terms of data acquisition, transmission, and storage. To surmount these obstacles, this paper delves into an enhanced inexact reconstruction-based compressed sensing method for TDOA estimation (EIRCS), presents an optimized algorithmic procedure that further reduces the computational complexity of the EIRCS method. Experimental results substantiate that the EIRCS method is an unbiased estimation technique. It accomplishes high-precision TDOA estimation concurrent with efficient data compression. These insights suggest that the EIRCS method can yield dependable TDOA estimates with minimal error, even at elevated compression ratios. Its capacity to sustain high accuracy across a range of compression ratios renders it particularly apt for applications demanding efficient data processing and reliable TDOA estimation.

Indexed as

Compressed sensingCross-correlationTime difference of arrival

Identifiers

PMID41258125
PMCPMC12630815

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.