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| Citation: | Tian He, Li Daojing, Qi Chunchao. Millimeter-wave Human Security Imaging Based on Frequency-domain Sparsity and Rapid Imaging Sparse Array Architecture[J]. Journal of Radars, 2018, 7(3): 376-386. doi: 10.12000/JR17082
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Millimeter-wave Human Security Imaging Based on Frequency-domain Sparsity and Rapid Imaging Sparse Array Architecture
doi: 10.12000/JR17082
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Abstract
This paper examines the processing of millimeter-wave imaging data based on sparse sampling and sparse array design for the rapid imaging of human security data. First, based on the cylindrical scanning imaging model, the Barker code-based randomly sparse sampling method is employed to reduce the scanning time. Then, a three-dimensional imaging algorithm based on interferometry and compressed sensing in the frequency domain is proposed, with sparse representation of the image in the frequency domain after interferometry and Compressed Sensing measurement model, to recover the image frequency spectrum, thereby implementing human security image reconstruction via sparse sampling. Real data processing results indicated that the proposed method could obtain image resolution and performance similar to those of complete samples and that the image correlation coefficients before and after sparse sampling were better than 0.9, with 50% time/data reduction. Furthermore, based on the Barker codes and multistatic work mode, a sparse array architecture for rapid imaging was designed with a sparse rate of 94.6% and the guarantee of imaging quality. The proposed method was found to considerably increase the passage rate and reduce the amount of radiation unit and system complexity, marking its application significance and market prospect in security clearance. -
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References
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- Figure 1. The cylindrical scanning 3-D imaging model of a millimeter wave human security system
- Figure 2. The Autocorrelation and Beam pattern diagrams for Barker code of [1110010]
- Figure 3. The cylindrical scanning imaging system and testing objectives
- Figure 4. The sparse sampling method of cylindrical echo
- Figure 5. The direct imaging result under complete sampling
- Figure 6. The direct imaging result under uniformly spaced sparse sampling
- Figure 7. The direct imaging result under Barker code sparse sampling
- Figure 8. The 3-D frequency spectrum before and after interferometry
- Figure 9. The reconstruction of 3-D imaging algorithm based on interferometry and CS in frequency domain
- Figure 10. The structure of minimum unit in 2-D sparse array
- Figure 11. The 2-D sparse array structure for millimeter wave fast imaging