Performance analysis for direction finding in non-Gaussian noise
نویسندگان
چکیده
We consider narrowband angle of arrival estimation in nonGaussian (NG) noise channels, such as arises in some indoor and outdoor mobile communications channels. We develop a general expression for the Cramer-Rao bound (CRB) for direction nding using arrays for deterministic signals plus iid non-Gaussian noise, generalizing the Gaussian CRB. The CRBs for the noise and direction parameters decouple. The CRB for direction nding is expressed as a product of two terms that depend on the noise distribution, and the signal, respectively. We illustrate the results for a Gaussian mixture pdf, and present simulation results comparing ve direction nding algorithms. An approach based on the expectation-maximization (EM) algorithm, that simultaneously estimates the noise parameters, the signal directions, and the signal waveforms, is shown to achieve the CRB over a wide SNR range.
منابع مشابه
A Novel DOA Estimation Approach for Unknown Coherent Source Groups with Coherent Signals
In this paper, a new combination of Minimum Description Length (MDL) or Eigenvalue Gradient Method (EGM), Joint Approximate Diagonalization of Eigenmatrices (JADE) and Modified Forward-Backward Linear Prediction (MFBLP) algorithms is proposed which determines the number of non-coherent source groups and estimates the Direction Of Arrivals (DOAs) of coherent signals in each group. First, the MDL...
متن کاملPerformance analysis for time-frequency MUSIC algorithm in presence of both additive noise and array calibration errors
This article deals with the application of Spatial Time-Frequency Distribution (STFD) to the direction finding problem using the Multiple Signal Classification (MUSIC)algorithm. A comparative performance analysis is performed for the method under consideration with respect to that using data covariance matrix when the received array signals are subject to calibration errors in a non-stationary ...
متن کاملUnderwater Noise Modeling and Direction-Finding Based on Heteroscedastic Time Series
We propose a new method for practical non-Gaussian and nonstationary underwater noise modeling. This model is very useful for passive sonar in shallow waters. In this application, measurement of additive noise in natural environment and exhibits shows that noise can sometimes be significantly non-Gaussian and a time-varying feature especially in the variance. Therefore, signal processing algori...
متن کاملAsymptotic performance analysis of DOA finding algorithms with temporally correlated narrowband signals
This correspondence focuses on the asymptotic performance analysis of general direction-of-arrival (DOA) finding algorithms under the stochastic model assumption in which source and noise signals are possibly non-Gaussian and possibly temporally correlated. We prove, in particular, that all the covariance-based DOA estimators are sensitive to the temporal correlation of the sources when the noi...
متن کاملUnderwater Direction-of-Arrival Finding: Maximum Likelihood Estimation and Performance Analysis
OF THE DISSERTATION Underwater Direction-of-Arrival Finding: Maximum Likelihood Estimation and Performance Analysis by Tao Li Doctor of Philosophy in Electrical Engineering Washington University in St. Louis, May 2012 Research Advisor: Dr. Arye Nehorai In this dissertation, we consider the problems of direction-of-arrival (DOA) finding using acoustic sensor arrays in underwater scenarios, and d...
متن کامل