Experimental results of localization of moving underwater signal by adaptive beamforming

Gershman, A.B.; Turchin, V. I.; Зверев, В. А.

doi:10.1109/78.469863

Cited by 73 publications

(28 citation statements)

References 18 publications

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“…An array of hydro-acoustic sensors is often employed for source localization in underwater applications, which is a challenging problem primarily due to the difficulty of accurately modeling the propagation medium [52]. The background noise is often spatially correlated along the array due to, for example, surface noise and engine noise.…”

Section: Direction Estimation In Underwater Acousticsmentioning

confidence: 99%

Covariance Matching Estimation Techniques for Array Signal Processing Applications

Ottersten

Stoica

Roy

1998

Digital Signal Processing

360

265

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Section: Direction Estimation In Underwater Acousticsmentioning

confidence: 99%

Covariance Matching Estimation Techniques for Array Signal Processing Applications

Ottersten

Stoica

Roy

1998

Digital Signal Processing

360

265

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“…DOA estimation of an acoustic source in the underwater environment is an important topic and lies at the heart of many underwater signal processing applications such as sonar detection and localization [1]- [4], geoacoustic inversion [5], [6], underwater vehicle navigation [7], and ocean biological signal analysis [8]. It is a challenging problem since various uncertainties can arise from following aspects: 1) Source dynamics.…”

Section: Introductionmentioning

confidence: 99%

Direction of arrival tracking of an underwater acoustic source using particle filtering: Real data experiments

Zhong

Premkumar

Wang

2013

IEEE 2013 Tencon - Spring

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Abstract-In the past, both theoretical work and practical implementation of particle filtering (PF) method have been extensively studied. However, its application in underwater signal processing has received much less attention. This paper intends to introduce PF approach for underwater acoustic signal processing. Particularly, we are interested in direction of arrival (DOA) estimation using PF. A detailed introduction along with this perspective is presented in this paper. Since the noise usually spreads the mainlobe of likelihood function and causes problem in subsequent particle resampling step, an exponential weighted likelihood model is developed to emphasize particles at more relevant area. Hence, the the effect due to background noise can be reduced. Real underwater acoustic data collected in SWELLEx-96 experiment are employed to demonstrate the performance of the proposed PF approaches for underwater DOA tracking.Index Terms-Direction of arrival, localization and tracking, underwater acoustics, particle filtering, SWELLEx-96 experiment.

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“…9,10 When these projection operators subsequently are applied to the received data in the presence of a target, reduction of reverberation results in enhancing the target echo. This approach essentially is equivalent to the eigenvector-based projection method in radar [10][11][12][13] where strong interferences are suppressed by projecting the array data onto the subspace that is orthogonal to the interference subspace. In reverberationlimited active sonar conditions, 1 reverberation can be treated as a strong interference although it represents a collection of distributed sources at the interface rather than a single point source.…”

Section: Introductionmentioning

confidence: 99%

Passive reverberation nulling for target enhancement

Song

Hodgkiss

Kuperman

et al. 2007

The Journal of the Acoustical Society of America

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Echo-to-reverberation enhancement previously has been demonstrated using time reversal focusing when knowledge of the channel response between a target and the source array elements is available. In the absence of this knowledge, direct focusing is not possible. However, active reverberation nulling still is feasible given observations of reverberation from conventional source array transmissions. For a given range of interest, the response between the source array elements and the dominant sources of boundary reverberation is provided by the corresponding reverberation from this range. Thus, an active transmission can be projected from the source array which minimizes the energy interacting with the boundaries at a given range while still ensonifying the waveguide between the boundaries. As an alternative, here a passive reverberation nulling concept is proposed. In a similar fashion, the observed reverberation defines the response between the source array elements and the dominant sources of boundary reverberation at each range and this is used to drive a range-dependent sequence of projection operators. When these projection operators subsequently are applied to the received data vectors, reverberation can be diminished. The improvement in target detectability is demonstrated using experimental data with an echo repeater simulating the presence of a target.

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Experimental results of localization of moving underwater signal by adaptive beamforming

Cited by 73 publications

References 18 publications

Covariance Matching Estimation Techniques for Array Signal Processing Applications

Covariance Matching Estimation Techniques for Array Signal Processing Applications

Direction of arrival tracking of an underwater acoustic source using particle filtering: Real data experiments

Passive reverberation nulling for target enhancement

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