Linear Prediction Approach for Accurate Dual - Channel Sine - Wave Parameter Estimation in White Gaussian Noise Hing - Cheung So and Zhenhua Zhou
نویسنده
چکیده
channels with common frequency in white Gaussian noise is addressed. By making use of the linear prediction property, an iterative linear least squares (LLS) algorithm for accurate frequency estimation is devised. The remaining parameters are then determined according to the LLS fit with the use of the frequency estimate. It is proven that the variance of the frequency estimate achieves Cramér-Rao lower bound at sufficiently small noise conditions.
منابع مشابه
Two accurate phase-difference estimators for dual-channel sine-wave model
Two algorithms for estimating the phase-difference between two real sinusoids with common frequency in the presence of white noise are proposed. The first estimator utilizes the maximum likelihood criterion to find the phase of each channel output in a separable manner, and the phase-shift estimate is then given by their difference. The algorithm extension to unknown frequency and/or noise powe...
متن کاملAccurate estimation of common sinusoidal parameters in multiple channels
Parameter estimation for exponentially damped complex sinusoids in the presence of white noise using multiple channel measurements is addressed. More precisely, we are interested in the damping factor and frequency parameters which are common among all channels. By exploiting linear prediction and weighted least squares technique, an iterative algorithm is devised to extract the common dynamics...
متن کاملSubspace approach for two-dimensional parameter estimation of multiple damped sinusoids
In this paper, we tackle the two-dimensional (2-D) parameter estimation problem for a sum of K ≥ 2 real/complex damped sinusoids in additive white Gaussian noise. According to the rank-K property of the 2-D noise-free data matrix, the damping factor and frequency information is contained in the K dominant left and right singular vectors. Using the sinusoidal linear prediction property of these ...
متن کاملCorrelation-based algorithm for multi-dimensional single-tone frequency estimation
In this paper, parameter estimation for a R-dimensional (R-D) single cisoid with R ≥ 2 in additive white Gaussian noise is addressed. By exploiting the correlation of the data samples, we construct R single-tone sequences which contain the R-D frequency parameters. Based on linear prediction and weighted linear squares techniques, two proposals are developed for fast and accurate frequency esti...
متن کاملIterative quadratic maximum likelihood based estimator for a biased sinusoid
The problem of parameter estimation of a single sinusoid with unknown offset in additive Gaussian noise is addressed. After deriving the linear prediction property of the noise-free signal, the maximum likelihood estimator for the frequency parameter is developed. The optimum estimator is relaxed according to the iterative quadratic maximum likelihood technique. The remaining parameters are the...
متن کامل