Clutter Suppression of Wind Farm Based on Sparse Reconstruction and Morphological Component Analysis for ATC Radar under Short Coherent Processing Interval Condition

Weikun HE; Fenghua BI; Xiaoliang WANG; Ying ZHANG

doi:10.11999/JEIT200474

Volume 43 Issue 7

Jul. 2021

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Weikun HE, Fenghua BI, Xiaoliang WANG, Ying ZHANG. Clutter Suppression of Wind Farm Based on Sparse Reconstruction and Morphological Component Analysis for ATC Radar under Short Coherent Processing Interval Condition[J]. Journal of Electronics & Information Technology, 2021, 43(7): 1954-1961. doi: 10.11999/JEIT200474

Citation:

Weikun HE, Fenghua BI, Xiaoliang WANG, Ying ZHANG. Clutter Suppression of Wind Farm Based on Sparse Reconstruction and Morphological Component Analysis for ATC Radar under Short Coherent Processing Interval Condition[J]. Journal of Electronics & Information Technology, 2021, 43(7): 1954-1961. doi: 10.11999/JEIT200474

Citation:

Weikun HE, Fenghua BI, Xiaoliang WANG, Ying ZHANG. Clutter Suppression of Wind Farm Based on Sparse Reconstruction and Morphological Component Analysis for ATC Radar under Short Coherent Processing Interval Condition[J]. Journal of Electronics & Information Technology, 2021, 43(7): 1954-1961. doi: 10.11999/JEIT200474

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Clutter Suppression of Wind Farm Based on Sparse Reconstruction and Morphological Component Analysis for ATC Radar under Short Coherent Processing Interval Condition

doi: 10.11999/JEIT200474 cstr: 32379.14.JEIT200474

Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China

Funds: The National Natural Science Foundation of China and the Civil Aviation Administration of China (U1533110), The Special Funding from the Civil Aviation University of China for the Basic Research Business Fee Project of Central Universities (3122018D011), The Natural Science Foundation of Tianjin (19JCQNJC01000)

Received Date: 2020-06-12
Rev Recd Date: 2020-12-06

Available Online: 2020-12-14

Publish Date: 2021-07-10

Abstract

Abstract

In recent years, countries around the world have paid more and more attention to the development of wind power. The existence of wind farms may have a negative impact on the performance of air traffic control surveillance radars. Therefore, the research on the clutter suppression technology of wind farms is of great significance to improve the work performance of air traffic control surveillance radars and ensure the safety of air traffic. When the Morphological Component Analysis(MCA)algorithm is applied to the wind farm clutter suppression based on the difference of sparse characteristics for the signals, the calculation burden is lower and the performance is better. However, the clutter suppression performance of the MCA algorithm is affected when the spectral resolution is reduced due to the short Coherent Processing Interval(CPI)and the signal characteristics are not obvious. Therefore, the sparse reconstruction algorithm and the MCA algorithm are combined to suppress the clutter in the wind farm with a small number of coherent pulses. It is considered that the short CPI received echo data is the default of tail data on the basis of the longer CPI radar echo data, and then the sparse reconstruction algorithm is used to recover the default data, and the MCA algorithm is used to suppress wind farm clutter. The experimental results verify the effectiveness of the proposed method.
- Wind farm,
- Morphological Component Analysis(MCA),
- Sparse reconstruction,
- Clutter suppression

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References(19)

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