A new method for array calibration of array gain and phase uncertainties, which severely degrade the performance of spatial spectrum estimation, is presented. The method is based on the idea of the instrumental sensor...A new method for array calibration of array gain and phase uncertainties, which severely degrade the performance of spatial spectrum estimation, is presented. The method is based on the idea of the instrumental sensors method （ISM）, two well-calibrated sensors are added into the original array. By applying the principle of estimation of signal parameters via rotational invariance techniques （ESPRIT）, the direction-of-arrivals （DOAs） and uncertainties can be estimated simultaneously through eigen-decomposition. Compared with the conventional ones, this new method has less computational complexity while has higher estimation precision, what＇s more, it can overcome the problem of ambiguity. Both theoretical analysis and computer simulations show the effectiveness of the proposed method.展开更多
在实际应用中多种类型阵列误差同时存在,针对这种情况下阵列误差方位依赖的特点,提出了一种基于流形分离技术(manifold separation technique,MST)的改进多重信号分类(multiple signal classification,MUSIC)算法,可以有效解决多种阵列...在实际应用中多种类型阵列误差同时存在,针对这种情况下阵列误差方位依赖的特点,提出了一种基于流形分离技术(manifold separation technique,MST)的改进多重信号分类(multiple signal classification,MUSIC)算法,可以有效解决多种阵列误差影响下的波达方向估计问题。利用MST获得包含阵列非理想特性的采样矩阵,从而进行精准测向;通过二维傅里叶变换求解二维空间谱,与现有MUSIC校正算法相比,减少了谱峰搜索的运算量。理论分析和仿真验证了该算法的有效性,可为实际问题的解决提供参考。展开更多
文摘A new method for array calibration of array gain and phase uncertainties, which severely degrade the performance of spatial spectrum estimation, is presented. The method is based on the idea of the instrumental sensors method （ISM）, two well-calibrated sensors are added into the original array. By applying the principle of estimation of signal parameters via rotational invariance techniques （ESPRIT）, the direction-of-arrivals （DOAs） and uncertainties can be estimated simultaneously through eigen-decomposition. Compared with the conventional ones, this new method has less computational complexity while has higher estimation precision, what＇s more, it can overcome the problem of ambiguity. Both theoretical analysis and computer simulations show the effectiveness of the proposed method.
文摘在实际应用中多种类型阵列误差同时存在,针对这种情况下阵列误差方位依赖的特点,提出了一种基于流形分离技术(manifold separation technique,MST)的改进多重信号分类(multiple signal classification,MUSIC)算法,可以有效解决多种阵列误差影响下的波达方向估计问题。利用MST获得包含阵列非理想特性的采样矩阵,从而进行精准测向;通过二维傅里叶变换求解二维空间谱,与现有MUSIC校正算法相比,减少了谱峰搜索的运算量。理论分析和仿真验证了该算法的有效性,可为实际问题的解决提供参考。
