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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chaoyu Wang Hongtao Li Xiaohua Zhu Yapeng He |
| Copyright Year | 2013 |
| Description | Author affiliation: Inst. of Microwave Remote Sensing & Data Transm., China Acad. of Space Technol. (CAST), Xi'an, China (Yapeng He) || Sch. of Electron. & Opt. Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China (Chaoyu Wang; Hongtao Li; Xiaohua Zhu) |
| Abstract | Compressive sensing (CS) is an emerging data acquisition method under the condition that the signal is sparse or compressible. However, applying CS in radar to reconstruct target scene always requires the sparsity of the echo signal is known priori with high Signal to Interference and Noise Ratio (SINR). Such an ideal assumption may not be met in practical situations. In this paper, a robustly blind sparsity recovery algorithm for compressive sensing radar (CSR) is presented. The proposed method could enhance the performance of targets detection and range-Doppler parameters estimation in low SINR without known the sparsity of the original signal with the idea of choosing supplements of the sparse signal adaptively and optimizing transmit waveform. The numerical simulations are carried out to verify the effectiveness of the proposed method. |
| Starting Page | 573 |
| Ending Page | 576 |
| File Size | 254734 |
| Page Count | 4 |
| File Format | |
| DOI | 10.1109/CECNet.2013.6703396 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-11-20 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Signal to Interference and Noise Ratio (SINR) Signal processing algorithms Interference Radar Sensors Compressive Sensing Radar (CSR) Blind sparisty Waveform Optimization Compressed sensing Signal to noise ratio |
| Content Type | Text |
| Resource Type | Article |
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