基于压缩感知的微波暗室稀疏阵列RMA成像
Thinned Array Antennas RMA Imaging in Microwave Anechoic Chamber Based on Compressed Sensing

稀疏阵列天线可有效降低微波成像系统规模和处理复杂度,但成像过程中,方位孔径数据采样率无法满足Nyquist采样定律要求时,将导致成像结果模糊或者混叠。对此,提出一种基于压缩感知理论的微波暗室稀疏阵列RMA成像算法。首先在微波暗室中搭建稀疏阵列天线成像模型,其次将方位向稀疏采样回波数据进行幅度校正和相位误差补偿,然后通过压缩感知理论进行回波信号的高精度重构,最终完成RMA成像。该算法实现以较大的空间采样间隔的稀疏阵列RMA高分辨成像,并利用微波暗室实测数据验证了所提算法的可行性和有效性。
The thinned array antennas can effectively reduce the scale and processing complexity of microwave imaging system, but it will lead to image blur or aliasing while the data sampling rate of azimuthal aperture can not meet the requirements of the Nyquist sampling theorem in the imaging process. Thus, thinned array antenna RMA imaging algorithm for the microwave anechoic chamber based on Compressed Sensing is proposed in the paper. Firstly, thinned array antenna imaging system model in the microwave anechoic chamber is established, secondly, amplitude correction and phase error compensation about the sparse sampling azimuthal echo data is accomplished, then echo signal is reconstructed precisely by Compressed Sensing theory, the final RMA imaging is obtained. The larger space sampling interval thinned array RMA high resolution imaging is achieved by the algorithm, and the data from microwave anechoic chamber is used to verify the validity and feasibility of the algorithm