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 数值计算与计算机应用  2018, Vol. 39 Issue (2): 81-90    DOI:
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IMPROVED PISARENKO ALGORITHM BASED ON SELF CORRELATION
Zhang Xiaowei, Lü Qianqian, Yan Huimin, Wan Xu
Science School of Harbin Engineering University, Harbin 150001, China
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Abstract： Pisarenko is an algorithm to estimate the parameters of a stationary random signal through N sampling data. Improved Pisarenko algorithm can accurately estimate the signal frequency in the noise environment. In this algorithm, a new self correlation matrix is obtained by choosing proper a time domain accumulation quantity relations. Finally, the estimated value of the frequency is obtained by using the least square method. The algorithm estimate the signal frequency which is extracted from the frequency domain in the time domain solution. Due to the classic Pisarenko algorithm is reduce the self correlation matrix dimensionality using sample autocorrelation function less, it avoided this weakness which affected the accuracy of frequency estimation. The simulation results show that the proposed algorithm can effectively improve the accuracy of the frequency estimation, and the frequency estimation performance is stable.

 引用本文: . 一种自相关矩阵改进的Pisarenko算法[J]. 数值计算与计算机应用, 2018, 39(2): 81-90. . IMPROVED PISARENKO ALGORITHM BASED ON SELF CORRELATION[J]. Journal of Numerical Methods and Computer Applicat, 2018, 39(2): 81-90.

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