Maneuvering Target Parameter Estimation Based on Sparse Bayesian Dictionary Learning in Space-Time Adaptive Processing

ZHANG Tao; ZHANG Yajuan; SUN Gang; LUO Qijun

doi:10.11999/JEIT210567

Volume 44 Issue 8

Aug. 2022

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ZHANG Tao, ZHANG Yajuan, SUN Gang, LUO Qijun. Maneuvering Target Parameter Estimation Based on Sparse Bayesian Dictionary Learning in Space-Time Adaptive Processing[J]. Journal of Electronics & Information Technology, 2022, 44(8): 2884-2892. doi: 10.11999/JEIT210567

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ZHANG Tao, ZHANG Yajuan, SUN Gang, LUO Qijun. Maneuvering Target Parameter Estimation Based on Sparse Bayesian Dictionary Learning in Space-Time Adaptive Processing[J]. Journal of Electronics & Information Technology, 2022, 44(8): 2884-2892. doi: 10.11999/JEIT210567

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Maneuvering Target Parameter Estimation Based on Sparse Bayesian Dictionary Learning in Space-Time Adaptive Processing

doi: 10.11999/JEIT210567

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

Funds: The Scientific Research Plan of Tianjin Education Commission (2019KJ117)

Received Date: 2021-06-11
Rev Recd Date: 2022-04-20

Available Online: 2022-04-26

Publish Date: 2022-08-17

Abstract

Abstract

A sparse Bayesian dictionary learning-based parameter estimation method is proposed to overcome the performance degradation in presence of dictionary mismatch in Space-Time Adaptive Processing (STAP). First, multiple measurements are constructed by using direction compensated space samples. Second, the bilinear transformation is utilized to separate the velocity and acceleration of the maneuvering target. Finally, the dynamic dictionaries of velocity and acceleration are established by the Taylor’s series, and then the maneuvering target parameters are estimated by sparse Bayesian dictionary learning. Numerical results show that the proposed method can obtain better accuracy in parameter estimation, and can provide an improved performance to the sparse recovery methods with pre-discretized dictionary in STAP parameter estimation.
- Space-Time Adaptive Processing(STAP),
- Parameter estimation,
- Dictionary mismatch,
- Sparse Bayesian dictionary learning

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References(20)

References

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