Wind Speed Estimation Method of Low-altitude Wind Shear Based on CL-KA-STAP in Complex Terrain Environment

Hai LI; Lingli XIE; Zhining ZHANG

doi:10.11999/JEIT200773

Volume 43 Issue 12

Dec. 2021

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Hai LI, Lingli XIE, Zhining ZHANG. Wind Speed Estimation Method of Low-altitude Wind Shear Based on CL-KA-STAP in Complex Terrain Environment[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3647-3655. doi: 10.11999/JEIT200773

Citation:

Hai LI, Lingli XIE, Zhining ZHANG. Wind Speed Estimation Method of Low-altitude Wind Shear Based on CL-KA-STAP in Complex Terrain Environment[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3647-3655. doi: 10.11999/JEIT200773

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Wind Speed Estimation Method of Low-altitude Wind Shear Based on CL-KA-STAP in Complex Terrain Environment

doi: 10.11999/JEIT200773

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

Funds: The Civil Aircraft Project (MJ-2018-S-28), The Key Projects of Tianjin Natural Fund(20JCZDJC00490), The Aviation Foundation of China (20182067008), The Basic Scientific Research Project of Universities of The CPC Central Committee (3122018D008), The Training Funds for Famous Blue Sky Teachers of Civil Aviation University of China

Received Date: 2020-08-31
Rev Recd Date: 2021-04-04

Available Online: 2021-07-13

Publish Date: 2021-12-21

Abstract

Abstract

When the airborne weather radar detects low-altitude wind shear in a complex terrain environment, the non-uniform characteristics of ground clutter make it difficult to accurately obtain clutter statistical characteristics, which in turn affects the clutter suppression effect, and makes the wind speed estimation of wind shear inaccurate. A Colored-Loading Knowledge-Aided STAP (CL-KA-STAP) wind speed estimation method of low-altitude wind shear is proposed. This method first constructs a dimensionality reduction joint space-time transformation matrix, and performs dimensionality reduction processing on the echo signal of the distance unit to be detected, and then integrates the prior knowledge obtained by the Digital Elevation Model (DEM) and the National Land Cover Database (NLCD) into the combined space. In the Combined space-time Main Channel Adaptive Processor (CMCAP), the color loading coefficient optimization function is constructed to solve the color loading coefficient, and finally the filter is constructed to realize the adaptive filtering of clutter and accurately estimate the wind speed. The subsequent simulation results prove the effectiveness of the proposed method.
- Airborne weather radar,
- Knowledge Aided (KA),
- Color loading,
- Low-altitude wind shear,
- Wind speed estimation

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References(24)

References

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