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基于辅助阵元的无孔互质阵幅相误差校正方法

Gain and Phase Error Calibration for Hole-Free Coprime Arrays Using Auxiliary Sensors

  • 摘要: 为解决互质阵列存在幅相误差情况下波达方向估计精度下降的问题,本文提出了一种基于少量辅助阵元的无孔互质阵列幅相误差校正方法。首先在原始阵列中添加3个校正后的辅助阵元,利用子阵分解将阵列接收数据分解为两个子阵的接收数据,采用基于协方差矩阵的辅助阵元法(R-instrumental sensor method,R-ISM)分别估计两个子阵的幅相误差,通过排序重组得到阵列的幅相误差,然后对接收数据协方差矩阵进行误差校正,结合MUSIC算法实现DOA估计。理论分析和仿真实验结果表明,本文方法仅需3个辅助阵元即可有效校正互质阵列的幅相误差,相较于四个辅助阵元的传统方法,本文方法在信噪比为0 dB和快拍数为300时均方根误差均降低0.3°,且无需优化求解,计算复杂度较低。

     

    Abstract: To address the degradation of Direction of Arrival (DOA) estimation accuracy in coprime arrays due to gain and phase errors, this paper proposes a calibration method for hole-free coprime arrays using a minimal number of auxiliary sensors. First, three pre-calibrated auxiliary sensors are appended to the original array. By leveraging the concept of subarray decomposition, the received array data is decomposed into two subarray datasets. The covariance matrix-based R-instrumental sensor method (R-ISM) is then applied to independently estimate the gain and phase errors for each subarray. These error estimates are sorted and recombined to derive the full-array error vector, which is used to calibrate the received data covariance matrix. Finally, DOA estimation is performed via the MUSIC algorithm. Theoretical analysis and simulation results demonstrate that the proposed method effectively calibrates coprime array gain and phase errors using only three auxiliary sensors. Compared with the traditional method requiring four auxiliary sensors, the proposed approach reduces the Root Mean Square Error (RMSE) by 0.3° under conditions of 0 dB SNR and 300 snapshots. Additionally, it eliminates the need for optimization procedures, thereby reducing computational complexity.

     

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