Multipath Component Parameter Estimation Based on Fractional Fourier Transform

The distinctive modulation domain characteristics of the linear frequency modulation (LFM) signal render them widely adopted as detection reference signals in channel sensing tasks. This article proposes a channel parameter estimation scheme leveraging fractional Fourier transform (FrFT) and compressed sensing (CS) technology. In order to achieve better pulse compression effects in the FrFT domain, this article proposes an ant colony optimization algorithm to achieve the non-cooperative perception of the FrFT optimal transform order. In addition, by constructing a CS algorithm with a sparse matrix as its core component, the estimation accuracy of multipath component parameters is improved. Furthermore, an actual channel measurement system is constructed to collect measurement data in real-world scenarios. Finally, the experimental data analysis shows that the method proposed in this article is superior to traditional methods in terms of resolution and estimation accuracy. This progress not only helps improve channel measurement practices, but also provides a reference solution for LFM signal processing.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Instrumentation and Measurement
Published
2025-01-01
DOI
https://doi.org/10.1109/tim.2025.3556173
Citations
1
Primary Topic
Advanced Electrical Measurement Techniques
Type
article
Field-Weighted Citation Impact
0.73

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multipath Component Parameter Estimation Based on Fractional Fourier Transform

Jingbo Zhang, Chunli Zhu, Shuya Liu, Zhen Tang
1 citations
IEEE Transactions on Instrumentation and Measurement
Advanced Electrical Measurement Techniques
0.73
article

Multipath Component Parameter Estimation Based on Fractional Fourier Transform

Jingbo Zhang, Chunli Zhu, Shuya Liu, Zhen Tang
article en
1 citations

Abstract

The distinctive modulation domain characteristics of the linear frequency modulation (LFM) signal render them widely adopted as detection reference signals in channel sensing tasks. This article proposes a channel parameter estimation scheme leveraging fractional Fourier transform (FrFT) and compressed sensing (CS) technology. In order to achieve better pulse compression effects in the FrFT domain, this article proposes an ant colony optimization algorithm to achieve the non-cooperative perception of the FrFT optimal transform order. In addition, by constructing a CS algorithm with a sparse matrix as its core component, the estimation accuracy of multipath component parameters is improved. Furthermore, an actual channel measurement system is constructed to collect measurement data in real-world scenarios. Finally, the experimental data analysis shows that the method proposed in this article is superior to traditional methods in terms of resolution and estimation accuracy. This progress not only helps improve channel measurement practices, but also provides a reference solution for LFM signal processing.

IEEE Transactions on Instrumentation and MeasurementVol. 74
Dalian Maritime University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 30%
Advanced Electrical Measurement Techniques
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.