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.
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.
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Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Contributions
Yong WU designed the research, processed the data, and drafted the paper. Luo ZUO offered data and helped organize the paper. Dongliang PENG and Zhikun CHEN revised and finalized the paper.
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All the authors declare that they have no conflict of interest.
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Project supported by the Zhejiang Provincial Natural Science Foundation of China (No. LZ23F030002), the Science and Technology Program of Zhejiang Provincial Department of Transportation (No. 2024012), and the Talent Funding Project of Zhejiang Institute of Communications (Nos. 822321KY0127 and 2024JK05)
List of supplementary materials
1 Performance analysis
2 Applicability and limitation analysis
Table S1 Computational complexity comparisons of ECA, ECA-B, and ECA-L
Table S2 Space complexity comparisons of ECA, ECA-B, and ECA-L
Fig. S1 Computational complexity variations of ECA, ECA-B, and ECA-L over the CPI and clutter suppression order K
Fig. S2 Space complexity variations of ECA, ECA-B, and ECA-L over the CPI and clutter suppression order K
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Wu, Y., Zuo, L., Peng, D. et al. A lightweight clutter suppression algorithm for passive bistatic radar. Front Inform Technol Electron Eng 25, 1536–1551 (2024). https://doi.org/10.1631/FITEE.2300859
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DOI: https://doi.org/10.1631/FITEE.2300859
Key words
- Passive bistatic radar
- Clutter suppression
- Extensive cancellation algorithm
- Computational complexity
- Space complexity