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A Downward-looking Three-dimensional Imaging Method for Airborne FMCW SAR Based on Array Antennas

Chinese Journal of Aeronautics 2011年第1期24卷 55-64页

作者： HOU Haiping QU Changwen ZHOU Qiang XIANG Yingchun Department of Electronic and Information Engineering Naval Aeronautical and Astronautical University Yantai 264001 China

With regard to problems in conventional synthetic aperture radar （SAR）, such as imaging distortion, beam limitation and failure in acquiring three-dimensional （3-D） information, a downward-looking 3-D imaging method based on frequency modulated continuous wave （FMCW） and digital beamforming （DBF） technology for airborne SAR is presented in this study. Downward-looking 3-D SAR signal model is established first, followed by introduction of virtual antenna optimization factor and discussion of equivalent-phase-center compensation. Then, compensation method is provided according to reside video phase （RVP） and slope term for FMCW SAR. As multiple receiving antennas are applied to downward-looking 3-D imaging SAR, range cell migration correction （RCMC） turns to be more complex, and corrective measures are proposed. In addition, DBF technology is applied in realizing cross-track resolution. Finally, to validate the proposed method, magnitude of slice, peak sidelobe ratio （PSLR）, integrated sidelobe ratio （ISLR） and two-dimensional （2-D） contour plot of impulse response function （IRF） of point target in three dimensions are demonstrated. Satisfactory performances are shown by simulation results.

关键词： synthetic aperture radar radar imaging frequency modulated continuous wave downward-looking three-dimensional array antenna digital beamforming

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Convolution neural network and 77 GHz millimeter wave radar based intelligent liquid classification system

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Journal of Information and Intelligence 2023年第4期1卷 352-363页

作者： Jiayu Chen Xinhuai Wang Yin Xu Ye Peng Wen Wang Junyan Xiang Qihang Xu Xidian University and National Key Laboratory of Antennas and Microwave Technology Xidian UniversityXi'an 710071China

An intelligent liquid classification system based on 77 GHz millimeter wave radar and convolution neural network are proposed in this *** data are collected by the AWR1843 radar platform and processed by the neural network on the host PC in *** doppler heatmap generated by radar signal processing is tried for the first time as the input of the *** information carried by the heatmap in 2 dimensions is analyzed and the reason why the doppler heatmap could be used for classification is *** feasible experiment proved that the proposed method can successfully classify 8 kinds of common liquid with high *** result of the experiment is explained and the limitations of the experiment are *** can be drawn that the combination of FMCW millimeter wave radar and convolution neural network is a method with great potential for liquid *** advantages of real time,non-invasive and unilateral measurement can also be used for the detection of dangerous liquids.

关键词： Convolution neural network Doppler heatmap frequency modulated continuous wave Liquid classification 77 GHz millimeter wave radar

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