NDLI: Enhanced passive acoustic localization with an array of non-identical sensors using blind Gauss-Markov estimate

Content Provider	IEEE Xplore Digital Library
Author	Choudhary, H. Kumar, A. Bahl, R.
Copyright Year	2013
Description	Author affiliation: Center for Appl. Res. in Electron., Indian Inst. of Technol. Delhi, New Delhi, India (Choudhary, H.; Kumar, A.; Bahl, R.)
Abstract	For a stationary radiating source, the optimum time-delay vector estimation at a receiving sensor array is realized using the Generalized Cross Correlation (GCC) function. The estimates are combined with the correlator error matrix, expressed in terms of the sensor signal spectra and background noise spectra, to obtain a linear minimum variance unbiased estimate of the time delay vector, known as the Gauss-Markov estimate. In this estimation procedure, the signal power spectral density (PSD) is assumed to be the same at the different sensors which will be approximately true for distant sources. This PSD is replaced in practice by the a priori known source PSD. In the absence of a priori information, the PSD is required to be estimated at the sensors of the receiver array. This modified algorithm has been called the “blind” Gauss-Markov estimation algorithm. It provides better estimates of inter-sensor time delay, source range and bearing compared to the respective estimates obtained with the classical correlator system in terms of mean square error (MSE) measure. For a wide-aperture array, the use of PSD estimation based Gauss-Markov algorithm has been proposed earlier by the authors through two algorithms. In the first algorithm, the signal spectrum estimate at the closest sensor is used, while in the second algorithm, the signal spectra estimates at individual sensors are used. These proposed algorithms improve the estimates obtained from the correlator system in MSE terms. For a wide aperture array, the individual sensor PSD based Gauss-Markov estimate is more accurate than the closest sensor PSD based Gauss-Markov estimate as it utilizes the signal amplitude gradient information across the sensors of the array. This paper investigates the use of arrays with non-identical sensors along with the second algorithm in which the signal spectrum estimation is done at the individual sensors. Analytic explanation of the same shall be presented. The algorithm has been implemented and studied for an underwater acoustic experiment based on a three-element, non-uniform, perturbed linear array. It is found to give enhanced parameter estimation compared to the classical Gauss-Markov algorithm that uses constant PSD across the sensors. The proposed algorithm can be useful in providing more accurate localization of radiating underwater sources in applications like underwater robotics, diver guidance system, underwater object handling, and tracking of maneuvering vessels.
Sponsorship	Japan Council OE Chapt.
Starting Page	1
Ending Page	6
File Size	150211
Page Count	6
File Format	PDF
ISBN	9781467359481
e-ISBN	9781467359498
DOI	10.1109/UT.2013.6519849
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-03-05
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Delay effects Sensor arrays Signal to noise ratio Vectors Estimation Gauss-Markov Estimate and Time delay vector Acoustic Localization Correlator System
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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