中文摘要：

基于匹配滤波器组的最小方差谱估计方法，由一组匹配滤波器输出计算输入信号的谱估计值，其匹配滤波器的求解基于自相关矩阵逆矩阵，受到矩阵维数和奇异性的限制。提出一种迭代求解算法直接计算匹配滤波器，基于简化的复系数凸二次优化问题来实现，回避了矩阵求逆。算法具有二次终止性质，在有限次迭代内达到最优解。而限制迭代次数可以对频率分辨率和谱线不匹配现象折中，以得到更高谱峰幅度。实验采用新算法实现MVDR和CCA算法匹配滤波器，并对谱估计结果进行比较。

英文摘要：

The minimum variance spectral estimation based on matched filter bank is a non-parametric approach;it uses the output of a bank of band-pass matched filters to calculate the spectral estimation value of the input signal. Traditional solution method of the matched filter is based on autocorrelation matrix inversion, which is limited by the dimension and singularity of the matrix. An iterative algorithm is proposed to directly calculate the matched-filter, which is implemented based on the simplified complex coefficient convex quadratic optimization problem and avoids the matrix inversion. The proposed algorithm has quadratic termination property and is solved with conjugate gradient method;the optimal solution can be reached in finite number of iterations. Limiting the number of iterations can achieve a tradeoff between frequency resolution and spectral line unmatching, and higher spectral peak amplitudes are obtained. The proposed new algorithm was applied in experiment, （minimum variance distortionless response, MVDR） and （canonical correlation analysis, CCA） algorithm matched filters were implemented, and the spectral estimation results were compared.