Underwater sources location in non-Gaussian impulsive noise environments
Digital Signal Processing
Tracking Source azimuth Using a Single Vector Sensor
SENSORCOMM '10 Proceedings of the 2010 Fourth International Conference on Sensor Technologies and Applications
The acoustic vector-sensor's near-field array-manifold
IEEE Transactions on Signal Processing
Robust Gaussian and non-Gaussian matched subspace detection
IEEE Transactions on Signal Processing
Vector-sensor array processing for electromagnetic sourcelocalization
IEEE Transactions on Signal Processing
Subspace-based adaptive generalized likelihood ratio detection
IEEE Transactions on Signal Processing
Acoustic vector-sensor beamforming and Capon direction estimation
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Wideband source localization using a distributed acoustic vector-sensor array
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Near-field/far-field azimuth and elevation angle estimation using asingle vector hydrophone
IEEE Transactions on Signal Processing
Acoustic vector-sensor array processing
IEEE Transactions on Signal Processing
Signal detection in Gaussian noise of unknown level: An invariance application
IEEE Transactions on Information Theory
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This paper presents the formulation and performance analysis of four techniques for detection of a narrowband acoustic source in a shallow range-independent ocean using an acoustic vector sensor (AVS) array. The array signal vector is not known due to the unknown location of the source. Hence all detectors are based on a generalized likelihood ratio test (GLRT) which involves estimation of the array signal vector. One non-parametric and three parametric (model-based) signal estimators are presented. It is shown that there is a strong correlation between the detector performance and the mean-square signal estimation error. Theoretical expressions for probability of false alarm and probability of detection are derived for all the detectors, and the theoretical predictions are compared with simulation results. It is shown that the detection performance of an AVS array with a certain number of sensors is equal to or slightly better than that of a conventional acoustic pressure sensor array with thrice as many sensors.