Random Chirp Frequency-stepped Signal ISAR Imaging Algorithm Based on Joint Block-sparse Model

Mingjiu LÜ; Wenfeng CHEN; Saiqiang XIA; Jun YANG; Xiaoyan MA

doi:10.11999/JEIT180054

Volume 40 Issue 11

Oct. 2018

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Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(11): 2614-2620

Mingjiu LÜ, Wenfeng CHEN, Saiqiang XIA, Jun YANG, Xiaoyan MA. Random Chirp Frequency-stepped Signal ISAR Imaging Algorithm Based on Joint Block-sparse Model[J]. Journal of Electronics & Information Technology, 2018, 40(11): 2614-2620. doi: 10.11999/JEIT180054

Citation:

Mingjiu LÜ, Wenfeng CHEN, Saiqiang XIA, Jun YANG, Xiaoyan MA. Random Chirp Frequency-stepped Signal ISAR Imaging Algorithm Based on Joint Block-sparse Model[J]. Journal of Electronics & Information Technology, 2018, 40(11): 2614-2620. doi: 10.11999/JEIT180054

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Random Chirp Frequency-stepped Signal ISAR Imaging Algorithm Based on Joint Block-sparse Model

doi: 10.11999/JEIT180054

Air Force Early Warning Academy, Wuhan 430019, China

Funds: The National Natural Science Foundation of China (61671469)

Received Date: 2018-01-16
Rev Recd Date: 2018-07-17

Available Online: 2018-08-01

Publish Date: 2018-11-01

Abstract

Abstract

Under the condition of lack of echo data and low SNR, the ISAR imaging performance is greatly reduced by using Random Chirp Frequency-Stepped (RCFS) signal. To solve the above problems, based on fully analyzing the echo characteristics of the random chirp frequency-stepped signal, a new method of obtaining high quality ISAR images is proposed using the joint sparse feature of the target range dimension. First, a joint block sparse imaging model of the target echo signal under the condition of random chirp frequency-stepped signal is derived and the characteristics of the model are analyzed. Secondly, a Joint Block sparse Orthogonal Matching Pursuit (JBOMP) algorithm is proposed for solving the model. The algorithm utilizes the sparse information and the joint sparse information of the ISAR echo. Therefore, the ISAR imaging performance is enhanced under the condition of low measurement and low SNR. The proposed algorithm also can achieve joint processing of multidimensional signals and has a faster operation speed. Both theoretical analysis and simulation experiments verify the effectiveness of the proposed method.
- ISAR imaging,
- Random Chirp Frequency-Stepped (RCFS) signal,
- Joint sparse model,
- Block sparse model

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References(11)

References

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