Subspace approach for two-dimensional parameter estimation of multiple damped sinusoids
نویسندگان
چکیده
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 vectors, the frequencies and damping factors of the first dimension are first estimated. For each frequency of the first dimension, the corresponding parameter in the second dimension is then obtained to achieve autopairing. Computer simulations are included to compare the proposed approach with several conventional 2-D estimators in terms of mean square error performance and computational complexity. Index Terms dominant singular vector, linear prediction, weighted least squares, two-dimensional parameter estimation, spectral analysis
منابع مشابه
A New Windowing Method for the Parameter Estimation of Damped Sinusoids
This paper presents a preprocessing technique based on exponential windowing (EW) for parameter estimation of superimposed exponentially damped sinusoids. It is shown that the EW technique significantly improves the robustness to noise over two other commonly used preprocessing techniques: subspace decomposition and higher order statistics. An ad-hoc but efficient approach for the EW parameter ...
متن کاملUtilizing Principal Singular Vectors for Parameter Estimation of Multiple Damped Sinusoids
A new signal subspace approach for sinusoidal parameter estimation of multiple tones is proposed in this paper. Our main ideas are to stack the observed data into a matrix without reuse of elements and exploit the principal singular vectors of this matrix for parameter estimation. Comparing with the conventional subspace methods which employ Hankel-style matrices with redundant entries, the pro...
متن کاملA Super - Resolution Parameter Estimation Algorithmfor Multi - Dimensional NMR Spectroscopy 1
A super-resolution parameter estimation scheme for multi-dimensional nuclear magnetic resonance spectroscopy is presented in this paper. Multi-dimensional nuclear magnetic resonance signals can be modeled as the summation of multi-dimensional damped sinusoids. The frequencies and the damping factors of multi-dimensional damped sinusoids play important roles in protein structure determination us...
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 کاملA New Guideline for the Allocation of Multipoles in the Multiple Multipole Method for Two Dimensional Scattering from Dielectrics
A new guideline for proper allocation of multipoles in the multiple multipole method (MMP) is proposed. In an ‘a posteriori’ approach, subspace fitting (SSF) is used to find the best location of multipole expansions for the two dimensional dielectric scattering problem. It is shown that the best location of multipole expansions (regarding their global approximating power) coincides with the med...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Signal Processing
دوره 92 شماره
صفحات -
تاریخ انتشار 2012