Extended-aperture underwater acoustic multisource azimuth/elevation direction-finding using uniformly but sparsely spaced vector hydrophones

Abstract

Abstract-Aperture extension is achieved in this novel ESPRITbased two-dimensional angle estimation scheme using a uniform rectangular array of vector hydrophones spaced much farther apart than a half-wavelength. A vector hydrophone comprises two or three spatially co-located, orthogonally oriented identical velocity hydrophones (each of which measures one Cartesian component of the underwater acoustical particle velocity vector-field) plus an optional pressure hydrophone. Each incident source's directions-of-arrival are determined from the source's acoustical particle velocity components, which are extracted by decoupling the data covariance matrix's signal-subspace eigenvectors using the lower dimensional eigenvectors obtainable by ESPRIT. These direction-cosine estimates are unambiguous but have high variance; they are used as coarse references to disambiguate the cyclic phase ambiguities in ESPRIT's eigenvalues when the intervector-hydrophone spacing exceeds a halfwavelength. In one simulation scenario, the estimation standard deviation decreases with increasing intervector-hydrophone spacing up to 12 wavelengths, effecting a 97% reduction in the estimation standard deviation relative to the half-wavelength case. This proposed scheme and the attendant vector-hydrophone array outperform a uniform half-wavelength spaced pressurehydrophone array with the same aperture and slightly greater number of component hydrophones by an order of magnitude in estimation standard deviation. Other simulations demonstrate how this proposed method improves underwater acoustic communications link performance. The virtual array interpolation technique would allow this proposed algorithm to be used with irregular array geometries.

Azimuth-elevation direction finding using a microphone and three orthogonal velocity sensors as a non-collocated subarray

“…12. The only change in the data-model of (30) is that now a k ¼ a gen (h k , / k ) of (13). Then, Sec.…”

An efficient joint estimation of wideband polynomial-phase signal parameters and direction-of-arrival in sensor array

“…Time-frequency analysis can be successfully used for underwater dispersive channel estimation [3]. An algorithm for azimuth/elevation direction-finding that enlarges the array aperture without introducing additional sensors and nonuniform interelement spacing, and that avoids the directioncosine ambiguity is proposed in [4].…”

“…An important application of polynomial-phase signal (PPS) estimation is related to the underwater monitoring of vessels and marine fauna [1][2][3], where large hydrophone arrays, containing tens or hundreds of sensors, are a common tool [4][5][6]. Numerous publications address the problem of estimating the PPS parameters along with the direction-of-arrival (DOA) [7][8][9][10][11][12].…”

Noncircular-PARAFAC for 2D-DOA estimation of noncircular signals in arbitrarily spaced acoustic vector-sensor array subjected to unknown locations

“…Since the measurement model of acoustic vectorsensor array had been developed in [2], researchers mainly turned to the study on direction of arrival (DOA) estimation of incoming signals and proposed many DOA estimation algorithms, which contain Capon technique [4], propagator method (PM) [5,13], estimation of signal parameters via rotational invariance technique (ESPRIT) algorithms [7][8][9], root-multiple signal classification (MUSIC) algorithm [10], self-initiating multiple signal classification MUSIC algorithm [11], hypercomplex MUSIC algorithm [12], parallel factor (PARAFAC) algorithm [15], successive MUSIC [14], as well as others [16][17][18][19][20][21].…”

“…Compared with traditional acoustic pressure sensor arrays, the acoustic vector sensors can measure the acoustic pressure as well as all three orthogonal components of the acoustic particle velocity at a single point in space, which brings about certain significant advantages in collecting more information on acoustics, better exploitation of beam forming, and enhancing the system performance [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15]. Since the measurement model of acoustic vectorsensor array had been developed in [2], researchers mainly turned to the study on direction of arrival (DOA) estimation of incoming signals and proposed many DOA estimation algorithms, which contain Capon technique [4], propagator method (PM) [5,13], estimation of signal parameters via rotational invariance technique (ESPRIT) algorithms [7][8][9], root-multiple signal classification (MUSIC) algorithm [10], self-initiating multiple signal classification MUSIC algorithm [11], hypercomplex MUSIC algorithm [12], parallel factor (PARAFAC) algorithm [15], successive MUSIC [14], as well as others [16][17][18][19][20][21].…”