Full Text:   <477>

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Suppl. Mater.: 

CLC number: TN95

On-line Access: 2024-12-26

Received: 2023-12-22

Revision Accepted: 2024-04-07

Crosschecked: 2024-12-26

Cited: 0

Clicked: 935

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Jun Wang

https://orcid.org/0000-0002-3434-6312

Yong WU

https://orcid.org/0009-0008-8580-5196

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Frontiers of Information Technology & Electronic Engineering  2024 Vol.25 No.11 P.1536-1551

http://doi.org/10.1631/FITEE.2300859


A lightweight clutter suppression algorithm for passive bistatic radar


Author(s):  Yong WU, Luo ZUO, Dongliang PENG, Zhikun CHEN

Affiliation(s):  Intelligent Transportation School, Zhejiang Institute of Communications, Hangzhou 311112, China; more

Corresponding email(s):   wuyong@zjvtit.edu.cn, zuoluo@xidian.edu.cn, dlpeng@hdu.edu.cn, czk@hdu.edu.cn

Key Words:  Passive bistatic radar, Clutter suppression, Extensive cancellation algorithm, Computational complexity, Space complexity


Yong WU, Luo ZUO, Dongliang PENG, Zhikun CHEN. A lightweight clutter suppression algorithm for passive bistatic radar[J]. Frontiers of Information Technology & Electronic Engineering, 2024, 25(11): 1536-1551.

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journal="Frontiers of Information Technology & Electronic Engineering",
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publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2300859"
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Abstract: 
In passive bistatic radar, the computational efficiency of clutter suppression algorithms remains low, due to continuous increases in bandwidth for potential illuminators of opportunity and the use of multi-source detection frameworks. Accordingly, we propose a lightweight version of the extensive cancellation algorithm (ECA), which achieves clutter suppression performance comparable to that of ECA while reducing the computational and space complexities by at least one order of magnitude. This is achieved through innovative adjustments to the reference signal subspace matrix within the ECA framework, resulting in a redefined approach to the computation of the autocorrelation matrix and cross-correlation vector. This novel modification significantly simplifies the computational aspects. Furthermore, we introduce a dimension-expanding technique that streamlines clutter estimation. Overall, the proposed method replaces the computation-intensive aspects of the original ECA with fast Fourier transform (FFT) and inverse FFT operations, and eliminates the construction of the memory-intensive signal subspace. Comparing the proposed method with ECA and its batched version (ECA-B), the central advantages are more streamlined implementation and minimal storage requirements, all without compromising performance. The efficacy of this approach is demonstrated through both simulations and field experimental results.

一种轻量化的外辐射源杂波抑制算法

武勇1,左罗2,彭冬亮3,陈志坤3
1浙江交通职业技术学院智慧交通学院,中国杭州市,311112
2西安电子科技大学广州研究院,中国广州市,510555
3杭州电子科技大学自动化学院,中国杭州市,310018
摘要:由于潜在机会照射源信号带宽不断增大及普遍使用的多源探测框架,外辐射源雷达杂波抑制的计算效率非常受限。本文提出一种经典扩展相消算法(ECA)的轻量化版本,能够实现和ECA相当的杂波抑制性能,但计算复杂度和空间复杂度能降低至少一个数量级。首先,通过改进ECA中参考信号子空间的构建方式,重新定义自相关和互相关矩阵的计算方法。然后,通过一种扩维方法来简化杂波估计过程。总体上,所提方法利用计算复杂度更低的快速傅里叶变换及其反变换来替代传统ECA中的高密度计算部分,并省去了高存储量的参考信号子空间的构建。仿真和外场数据处理结果验证了本文所提方法相比于ECA及其他批处理版本的优越性。

关键词:外辐射源双基地雷达;杂波抑制;扩展相消算法;计算复杂度;空间复杂度

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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