Estimation of location and motion parameters of a moving source observed from a linear array

Hassab, Joseph C.; Guimond, B.; Nardone, S.

doi:10.1121/1.386956

Cited by 43 publications

(9 citation statements)

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“…The range R and bearing are the polar coordinates of the source with the position of the middle sensor of the array coinciding with the origin. If d and c denote the intersensor spacing and the iso-speed of sound travel ͑respectively͒, then the range to the source from the middle sensor is given by 10 Rϭ…”

Section: A Range and Bearing Estimationmentioning

confidence: 99%

In situ source level and source position estimates of biological transient signals produced by snapping shrimp in an underwater environment

Ferguson

Cleary

2001

The Journal of the Acoustical Society of America

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Biological transient signals produced by snapping shrimp are sensed underwater by a wide aperture array. The instantaneous range and bearing of the source position of each snap is estimated along with a source level equal to the peak-to-peak amplitude of the pressure impulse generated by the snap at a standard distance of 1 m from its point of origin. For a sample of 1000 snaps recorded in Sydney Harbour, the distribution of peak-to-peak sound pressure levels has a mean value of 187 dB (re 1 microPa) and an interquartile range of 185-189 dB (re 1 microPa). Plotting the Cartesian coordinates of the source positions of the biological transient signals over a period of time maps the two-dimensional spatial distribution of the local snapping shrimp population. The principal habitat is found to be geocoincident with a 120-m-long wharf, the closest point of which is 60 m from the middle of the receiving array. The passive ranging performance of the wide aperture array is evaluated by generating mechanical transient signals at selected positions along the wharf. Precise estimates of the relative times-of-arrival of the acoustic wavefronts lead to source range and bearing estimates with standard deviations of only 0.1 m and 0.005 degrees (respectively), in agreement with theoretical predictions.

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Section: A Range and Bearing Estimationmentioning

confidence: 99%

In situ source level and source position estimates of biological transient signals produced by snapping shrimp in an underwater environment

Ferguson

Cleary

2001

The Journal of the Acoustical Society of America

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“…Even when time delays are estimated with unbiased Gaussian errors as would occur with high signal-to-noise spectra and long observation times (or as may occur following stabilization through windowing, gating, and filtering) direct mapping of the time delays into the contact's state can lead to biases in the estimation process. Reduction of this bias (and variance in contact state estimates) can be accomplished by judicious use of statistical estimation techniques over sequential and finite observations of the contact signal [13]. The contact state estimator is an expanding memory filter that maps imperfect time delay estimates into the invariant contact trajectory parameters (i.e., constant velocity, initial range) over which smoothing is performed.…”

Section: Statistical Smoothingmentioning

confidence: 99%

“…CLMA from a linear array, a class D problem, deals with the location and motion of a contact in the plane containing a linear array and contact [13,[54][55][56][57][58]. For the sake of simplicity, consider an array having three spatially separated elements (figure 2c).…”

Section: Clma From a Linear Arraymentioning

confidence: 99%

Contact Localization and Motion Analysis in the Ocean Environment: A Perspective

Hassab¹

1983

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UNCLASSIFIED 15«. DECLASSIFICATION / DOWNGRADING SCHEDULE ie. DISTRIBUTION STATEMENT lof IhU ReponI 17. DISTRIBUTION STATEMENT lof the abttract enumd in Block 20, if differttU from Reponi Approved for public release; distribution unlimited. 19. SUPPLEMENTARY NOTES 19. KEY WORDS fContmua on rewne iide if neemsMry and idmntify by block number/ Contact Location and Motion Analysis 20. ABSTRACT {Continue on mvene aide if neceaaary and identify by block numbert This document provides an overview of Contact Localization and Motion Analysis (CLMA) in the ocean environment. Such well-studied cases as passive bearings-only contact motion analysis, multipath ranging, and localization/tracking via arrays are used to illustrate the concept. The performance of current CLMA systems is shown to depend on the type and characteristics of the basic measurements developed by their time delay estimators, the acoustic channels linking contact and observer, and the DD, 'r"147 3 20. Abstract (Cont'd) type and description of relative motion between contact and observer. General classes of CLMA schemes are presented. Complexity is shown to depend on the linearity/nonlinearity of their solution equations, the degree to which a contact is observable at each sample time, and the relative motion or degree of stationarity between contact and observer. Contributions to total system gain, biasing issues, and candidate solutions are discussed. Comprehensive references are provided.

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“…There has been a growing interest in passive acoustic-based systems for vehicle monitoring since the mid 1990s, comprising vehicle detection [4][5][6][7], vehicle classification [8], traffic density estimation [9][10][11][12][13][14], speed estimation [15][16][17][18][19][20] and also energy consumption estimation using sound [21]. In this paper, we investigate a particle filtering-based technique for jointly estimating speed and wheelbase length of two-axle vehicles as they pass by.…”

Section: Introductionmentioning

confidence: 99%

An acoustic based method for jointly estimating speed and wheelbase length of two-axle road vehicles as they pass by

Marmaroli

Falourd

Lissek

2013

The Journal of the Acoustical Society of America

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This paper focuses on acoustic road traffic monitoring and looks, more specifically, into the problem of joint speed and wheelbase length estimation of two-axle vehicles as they pass by. It is known that both front and rear axle trajectories may be observed using a cross-correlation based processing in conjunction with a well designed two-element microphone array placed on the roadside. This is mainly due to the broadband nature of the tyre/road noise which makes two peaks appear in, one per axle, in the correlation function. In a former work, we proposed to conduct this double-peak-tracking problem using a specific particle filter that model road vehicles as bimodal sound sources (bimodal particle filter). After a brief theoretical recall of the method, this paper stresses on the recent preliminary results we obtained from simulation and in-situ experiments.

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Estimation of location and motion parameters of a moving source observed from a linear array

Cited by 43 publications

References 0 publications

In situ source level and source position estimates of biological transient signals produced by snapping shrimp in an underwater environment

In situ source level and source position estimates of biological transient signals produced by snapping shrimp in an underwater environment

Contact Localization and Motion Analysis in the Ocean Environment: A Perspective

An acoustic based method for jointly estimating speed and wheelbase length of two-axle road vehicles as they pass by

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