Narrow-band comb interference suppression algorithm in spaceborne synthetic aperture radar

The Spaceborne Synthetic Aperture Radar (SAR) uses electromagnetic waves to acquire remote sensing data. However, owing to the complex electromagnetic environment encountered on the Earth’s surface, it is necessary to address the challenge of anti-interference. This work focuses on the suppression of narrow-band comb interference (NCI) in practical applications. NCI manifests as a comb-like pattern in the frequency domain, and it overlaps with SAR echoes across multiple domains. Severe NCI can compromise the quality of SAR images. Conventional suppression algorithms are ineffective against NCI owing to its unique characteristics, resulting in unsatisfactory suppression performance. This paper introduces a new NCI suppression algorithm based on independent component analysis (ICA). The algorithm uses an eigen-beam to identify NCI components, which are subsequently extracted using ICA. A novel function is constructed to approximate negentropy, aligning with the characteristics of NCI. Finally, an orthogonal projection matrix is constructed using the extracted NCI samples, which effectively suppresses NCI in the raw echo data. Simulation experiments demonstrate the effectiveness and superiority of the proposed algorithm for NCI suppression.

Authors

Institutions

Publication Details

Journal
EURASIP Journal on Advances in Signal Processing
Published
2025-10-14
DOI
https://doi.org/10.1186/s13634-025-01257-0
Primary Topic
Advanced SAR Imaging Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Narrow-band comb interference suppression algorithm in spaceborne synthetic aperture radar

X. S. Jiang, Enyu Gao, Jia Zhi-hui, W. L. Chang et al.
EURASIP Journal on Advances in Signal Processing
Advanced SAR Imaging Techniques
article

Narrow-band comb interference suppression algorithm in spaceborne synthetic aperture radar

X. S. Jiang, Enyu Gao, Jia Zhi-hui, W. L. Chang, Jiang Wu, Shuai Guo, Wei Yan
article en

Abstract

The Spaceborne Synthetic Aperture Radar (SAR) uses electromagnetic waves to acquire remote sensing data. However, owing to the complex electromagnetic environment encountered on the Earth’s surface, it is necessary to address the challenge of anti-interference. This work focuses on the suppression of narrow-band comb interference (NCI) in practical applications. NCI manifests as a comb-like pattern in the frequency domain, and it overlaps with SAR echoes across multiple domains. Severe NCI can compromise the quality of SAR images. Conventional suppression algorithms are ineffective against NCI owing to its unique characteristics, resulting in unsatisfactory suppression performance. This paper introduces a new NCI suppression algorithm based on independent component analysis (ICA). The algorithm uses an eigen-beam to identify NCI components, which are subsequently extracted using ICA. A novel function is constructed to approximate negentropy, aligning with the characteristics of NCI. Finally, an orthogonal projection matrix is constructed using the extracted NCI samples, which effectively suppresses NCI in the raw echo data. Simulation experiments demonstrate the effectiveness and superiority of the proposed algorithm for NCI suppression.

EURASIP Journal on Advances in Signal ProcessingVol. 2025(1)
China Academy of Space Technology (CN), DigitalSpace (United States) (US)
National Natural Science Foundation of China
Openalex Percentile: Top 61%
Advanced SAR Imaging Techniques
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.