A KIND OF MAXIMUM ENTROPY SPECTRAL ESTIMATION ALGORITHM WITH HIGH RESOLUTION
一种高分辨率的最大嫡谱估计算法

Based on the Yule-Walker equations, a traditional Maximum Entropy Method (MEM) is the Levinson-Durbin recursion algorithm. The algorithm omits errors that are pro-duced when estimated values of autocorrelation sequence take the place of their ideai values. A new algorithm is presented in order to decrease the errors as much as possible. The algorithm improves its performance of spectral estimation and reduces computational complexity by means of the clues of some existing algorithms. The results of simulation demonstrate that the new algorithm has much more excellent performance of spectral estimation than that of the Levinson-Durbin algorithm. Compared with the LUD (Lower and Upper triangular matrix Decomposition) algorithm which also has high estimation performance, the new algorithm has higher resolution under low Signal-to-Noise Ratio(SNR) condition, or same resolution under high SNR.