【摘要】 为得到鲁棒性、高分辨波束形成,提出了一种高阶次Cross Sensor处理方法。该方法依据阵元间协方差矩阵同一斜对角线上不同元素具有相同相位差的特点,对协方差矩阵进行M阶次Cross Sensor处理后可虚拟出近(2~M-1)(N-1)个虚拟阵元(N为原始阵元数)。虚拟阵元的增加可扩大线阵有效孔径,降低波束形成主瓣宽度,提高方位分辨率。在Cross Sensor处理过程中,该方法对协方差矩阵同一斜对角线上不同元素进行了叠加运算,可进一步削弱噪声对波束形成的影响,提高了波束形成鲁棒性。数值仿真和海上试验结果表明,该方法既能有效降低波束形成主瓣宽度,提高方位分辨率,又可削弱方位历程图干扰背景。相比已有的逆波束形成,该方法具有较好的方位分辨率;相比已有的基于AR模型的高分辨逆波束形成,该方法对最低门限信噪比的要求较低,方位估计均方误差较小。更多还原

【Abstract】 In order to obtain robust high-resolution beamforming,a high order Cross Sensor processing( CSP)approach was developed. In the method,taking advantage of the characteristic that the elements on the same oblique diagnal of the covariance matrix of array elements have the same phase difference,approximate( 2~M- 1)( N- 1) virtual array elements( N is the number of original array elements) were invented by using M-order CSP. The increase of the number of virtual array elements can effectively expand the physical aperture of linear array and reduce beamforming mainlobe width,so the bearing resolution can be improved. In CSP,the different elements on the same sub-diagonal of the covariance matrix were superimposed in calculating operation,so that the influence of noise on beamforming was reduced,and the robustness was improved. The numerical simulation and sea trial results show that the method can effectively reduce the beamforming mainlobe width,improve the bearing resolution,and also decrease the interference background in bearing time recording( BTR). Compared with the inverse beamforming( IBF),the method has better bearing-resolution. Compared with the inverse beamforming based on auto-regression model( AR-IBF),the method can meet the requirement of lower signal-to-noise ratio( SNR) and has little mean square error for bearing estimation.更多还原