Title :
A numerical Bayesian approach for DOA and frequency estimation of exponential signals in Gaussian and non-Gaussian noise
Author :
Kannan, B. ; Fitzgerald, W.J.
Author_Institution :
Dept. of Eng., Cambridge Univ., UK
Abstract :
We present a Bayesian approach for DOA and frequency estimation of narrowband signals in additive complex Gaussian and non-Gaussian noise. Using Bayesian techniques, the a posteriori probability densities for DOA and frequency parameters are derived from the signal and noise models. These posterior probabilities are then used in the self-targeting Metropolis-Hastings algorithm to derive the samples for the DOA and frequency parameters. The mean square errors (MSE) of the parameters are compared with the Cramer-Rao lower bound (CRLB) and with various subspace-based methods. Unlike the conventional subspace-based methods such as MUSIC, ESPRIT etc., this new algorithm can be used with a significantly lower number of samples to estimate the parameters with acceptable MSE
Keywords :
Bayes methods; Gaussian noise; array signal processing; direction-of-arrival estimation; frequency estimation; probability; signal sampling; Cramer-Rao lower bound; DOA estimation; MSE; a posteriori probability densities; additive complex Gaussian noise; exponential signals; frequency estimation; mean square error; narrowband signals; non-Gaussian noise; numerical Bayesian approach; samples; self-targeting Metropolis-Hastings algorithm; subspace-based methods; Array signal processing; Bayesian methods; Direction of arrival estimation; Frequency estimation; Gaussian noise; Microwave integrated circuits; Radar applications; Sensor arrays; Signal processing; Sonar applications;
Conference_Titel :
Statistical Signal and Array Processing, 1998. Proceedings., Ninth IEEE SP Workshop on
Conference_Location :
Portland, OR
Print_ISBN :
0-7803-5010-3
DOI :
10.1109/SSAP.1998.739385