太赫兹科学与电子信息学报2016，Vol.14Issue(5)：771-777,7.DOI:10.11805/TKYDA201605.0771
一种基于奇异值分解的改进信噪比盲估计算法
Improved blind SNR estimation algorithm based on singular value decomposition
许维伟 1叶江峰 1胡茂海1
作者信息
- 1. 中国工程物理研究院电子工程研究所，四川绵阳 621999
- 折叠
摘要
Abstract
Signal Noise Ratio(SNR) estimation algorithms adopting subspace decomposition exhibit some disadvantages such as high complexity of estimating dimension of subspace and large deviation under low SNR region. An improved algorithm to estimate the dimension of subspace is proposed. Firstly, autocorrelation matrix of receiving signals is constructed to decompose the singular values. Then the gradient array is obtained from singular values through backward deviation. The ratio of each element to the sum of next five elements in gradient array is searched to find the max ratio. The sequence number corresponding to the max ratio is the dimension of signal subspace. Finally, SNR estimation value is calculated. Simulations under appropriate length of data indicate that the mean bias of SNR estimation is below 0.5dB and the standard deviation is below 1dB for normal modulated signals with SNR from -5dB to 20dB. This algorithm improves estimated performance in low SNR region and reduces the amount of calculation without knowing the parameters such as modulation mode, carrier wave frequency and symbol frequency beforehand. It has better performance of SNR tracking estimation in low SNR region and is also suited to complex high order modulation signals.关键词
信噪比估计/奇异值分解/差分准则/维数估计/信噪比跟踪Key words
SNR estimation/singular value decomposition/deviation principle/dimension estimation/SNR tracking分类
信息技术与安全科学引用本文复制引用
许维伟,叶江峰,胡茂海..一种基于奇异值分解的改进信噪比盲估计算法[J].太赫兹科学与电子信息学报,2016,14(5):771-777,7.
