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Article

11 Citations

3,318 Views

29 Pages

An Off-Grid Compressive Sensing Algorithm Based on Sparse Bayesian Learning for RFPA Radar

Ju Wang,
Bingqi Shan,
Song Duan,
Yi Zhao and
Yi Zhong

Remote Sens.2024, 16(2), 403;https://doi.org/10.3390/rs16020403

20 January 2024

In the application of Compressive Sensing (CS) theory for sidelobe suppression in Random Frequency and Pulse Repetition Interval Agile (RFPA) radar, the off−grid issues affect the performance of target parameter estimation in RFPA radar. Theref...

(This article belongs to the Special Issue Advanced Radar Signal Processing and Applications)

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Article

2 Citations

2,328 Views

30 Pages

A Highly Efficient Compressive Sensing Algorithm Based on Root-Sparse Bayesian Learning for RFPA Radar

Ju Wang,
Bingqi Shan,
Song Duan and
Qin Zhang

Remote Sens.2024, 16(19), 3564;https://doi.org/10.3390/rs16193564

25 September 2024

Off-grid issues and high computational complexity are two major challenges faced by sparse Bayesian learning (SBL)-based compressive sensing (CS) algorithms used for random frequency pulse interval agile (RFPA) radar. Therefore, this paper proposes a...

(This article belongs to the Topic Radar Signal and Data Processing with Applications)

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