Gain and Phase Calibration Algorithm of Near-field Source Based on Instrumental Sensors
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摘要: 针对近场源的定位及阵列幅相误差校正问题，该文提出一种基于均匀对称阵列利用辅助阵元矢量重构解耦合的幅相误差校正方法。通过重构虚拟阵列实现距离参数的分离，再通过对虚拟阵列导向矢量的变换实现方位和幅相误差之间的解耦合；最后通过对实阵列导向矢量的变换，实现距离与幅相误差的解耦合，从而实现对近场源的方位角、距离以及阵列的幅相误差系数的级联估计。仿真结果表明所提算法相比现有算法运算量小，方位及距离参数估计精确，幅相误差校正精度高。Abstract: In order to solve the problem of near-field source localization and array gain-phase error calibration, a method of gain-phase error calibration is proposed based on uniform array symmetry. The distance parameter is separated by reconstructing the virtual array, and then the decoupling between azimuth and error is realized by transforming the steering vector of the virtual array. Through the transformation of the real array steering vector, the decoupling between the distance and the gain-phase error is realized, and the cascade estimation of the azimuth and distance of the near-field source and the gain-phase error coefficient of the array is achieved. The simulation results show that compared with the exist algorithms, the proposed algorithm has less computational complexity, more accurate azimuth and distance parameters estimation, and higher accuracy of gain and phase error calibration.
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表 1 各个通道误差系数的真实值、估计值以及差值
误差系数 阵元2 阵元3 阵元4 阵元5 真实值 1.0000+0.0000i 0.9822–0.0181i 0.9909–0.0688i 0.9889+0.0162i 估计值 1.0000+0.0000i 0.9820–0.0183i 0.9908–0.0686i 0.9885+0.0142i 差值的绝对值 0.0000+0.0000i 0.0003+0.0000i 0.0002+0.0000i 0.0020+0.0000i 误差系数 阵元6 阵元7 阵元8 阵元9 真实值 1.0167+0.0121i 0.9820+0.0447i 1.0068+0.0062i 1.0077+0.0573i 估计值 1.0153+0.0103i 0.9817+0.0442i 1.0050+0.0060i 1.0081+0.0564i 差值的绝对值 0.0022+0.0000i 0.0005+0.0000i 0.0019+0.0000i 0.0010+0.0000i 误差系数 阵元10 阵元11 阵元12 真实值 1.0103–0.0410i 0.9976–0.0580i 1.0000+0.0000i 估计值 1.0105–0.0402i 0.9973–0.0575i 0.9999–0.0007i 差值的绝对值 0.0008+0.0000i 0.0006+0.0000i 0.0007+0.0000i 
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