Range and Bearing Estimation in Passive Sonar

Pasupathy, S.; Alford, W. J.

doi:10.1109/taes.1980.308961

Cited by 19 publications

(4 citation statements)

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“…a) In similar cases, we can prove that no unbiased estimator of θ exists since for such estimators the CRLB is the inverse of the FIM. This fact is met in array processing for the estimation of the end-fire bearing[5].b) The singularity of the FIM at some points of R d can cause some problems during the Gauss Newton routine for which the Hessian is approximated by the FIM evaluated at the point of the current iteration. The palliative is the augmentation of the FIM by some αId as suggested in the Levenberg-Marquardt method[6].…”

mentioning

confidence: 99%

Observability and fisher information matrix in nonlinear regression

Jauffret

2007

IEEE Trans. Aerosp. Electron. Syst.

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confidence: 99%

Observability and fisher information matrix in nonlinear regression

Jauffret

2007

IEEE Trans. Aerosp. Electron. Syst.

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“…Nevertheless, in many practical applications, such conditions are unlikely to be continuously guaranteed. This is the case of passive location systems, where the object of the location task could be an emitting source [11]- [13] or a target that backscatters a signal of opportunity, as in passive radar [14]- [16] or passive sonar [17] systems. The passive nature of such systems intrinsically limits the possibility to fully control the performance for any target of interest.…”

Section: A Overviewmentioning

confidence: 99%

Threshold Region Performance of Multicarrier Maximum Likelihood Direction of Arrival Estimator

Filippini

Colone

Maio

2019

IEEE Trans. Aerosp. Electron. Syst.

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This paper addresses performance characterization of a direction of arrival (DoA) estimator in the low signal-to-noise-ratio (SNR) region. The case of a sensor array simultaneously collecting signals emitted at multiple carrier frequencies by a single source is considered. A maximum likelihood (ML) approach is used as a reference method for DoA estimation and its accuracy is characterized in terms of mean square error (MSE). It is well known that, for SNR values included in the so-called threshold region, the DoA estimation accuracy decreases rapidly, due to the presence of outliers. This effect can be possibly mitigated when multiple frequency channels are jointly exploited. However, the capability to predict this performance degradation is fundamental either for assessing the robustness of an existing sensor or for supporting its design. Therefore, the scope of this paper is to introduce appropriate approximations to the MSE of a multi-frequency ML DoA estimator in order to provide a reliable characterization of its performance in the threshold region. Two models for the source signals are considered and separately discussed, namely the deterministic (or conditional) and stochastic (or unconditional). An extensive simulated analysis is reported to prove the tightness of the approximations and to characterize the benefits steming from the exploitation of signals emitted at multiple carriers.

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“…To effect this minimization, different windows are added to the basic time delays estimators with varying effectiveness [20,28,35,[59][60][61][62][63][64][65][66][67][68][69][70][71][72][73]• Such a ranging approach presumes stationary contact and sensor positions, as well as stationary signal and noise statistics.…”

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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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Range and Bearing Estimation in Passive Sonar

Cited by 19 publications

References 9 publications

Observability and fisher information matrix in nonlinear regression

Observability and fisher information matrix in nonlinear regression

Threshold Region Performance of Multicarrier Maximum Likelihood Direction of Arrival Estimator

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

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