A Novel Blind SNR Estimator Based on the Modified PASTd Algorithm for IF Signals
一种新的基于改进PASTd的中频信号盲信噪比估计算法

A blind Signal-to-Noise Ratio (SNR) estimator based on the modified PASTd (Projection Approximation Subspace Tracking deflation) algorithm is proposed in this paper for Intermediate Frequency (IF) signals in the Additive White Gaussian Noise (AWGN) channel. The orthogonality of the estimated eigenvectors is guaranteed by the use of the modified Gram-Schmidt orthogonization process in the original PASTd method. Computer simulations are performed for the commonly used IF signals, such as MPSK (M=2,4,8) and MQAM (M=16,64,128,256) signals. The results show that the performance of the algorithm is robust and when the true SNR is in the range from 5dB to 25dB the estimation bias is under 1dB and the corresponding STD is within 0.3. Compared with the Eigenvalue Decomposition (ED)-based method, the proposed algorithm can achieve a more accurate estimation with a simple computational complexity.