A Bayesian Method for Localization by Multistatic Active Sonar

Peters, Daniel J.

doi:10.1109/joe.2016.2540744

Cited by 30 publications

(11 citation statements)

References 5 publications

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“…Rui and Ho [23] proposed an algorithm to locate an object by an asynchronous relay network using time of arrival (TOA) measurements and Markov Chain Monte Carlo method, simulations showed that the proposed method has high accuracy for measurement association and yields a good localization accuracy. Peters [24] developed a localization method that can account for transmitter and receiver location errors, besides sound-speed, time and bearing errors. A Monte Carlo test was conducted to compare the accuracy of the proposed method to that of a more conventional method used as a baseline.…”

Section: Surveymentioning

confidence: 99%

A Modified Sampling Method for Localization Accuracy Improvement of Monte Carlo Localization

Awadallah¹,

Abdelaziz²,

Shahin³

et al. 2018

The International Conference on Applied Mechanics and Mechanica

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Unmanned vehicles are devices that can move around and perform tasks without an operator onboard. Such features are essential in many applications. Localization is a very important task in any autonomous mobile robot; in order to reliably navigate, the robot must keep accurate track of where it is. In the past few years Monte Carlo Localization (MCL) has been one of the most successful and popular approaches to solve the localization problem. MCL is a Bayesian algorithm based on particle filters. This paper is an attempt to increase the accuracy of localizing a mobile robot by modifying the way of generating samples from the proposal distribution of the MCL algorithm. Results show improvements in localization accuracy as compared to the basic MCL algorithm.

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Section: Surveymentioning

confidence: 99%

A Modified Sampling Method for Localization Accuracy Improvement of Monte Carlo Localization

Awadallah¹,

Abdelaziz²,

Shahin³

et al. 2018

The International Conference on Applied Mechanics and Mechanica

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“…Researchers are attempting to use methods such as matched filtering theory [53] or Bayesian localization [32] with simple sensors or sensor arrays in order to increase the performance of the sonar that is typically reliant on the size and number of sensors, not processing. A quick search of literature reveals that in the previous year, 2016, there were more than twice as many articles published relating to sonar software than sonar hardware.…”

Section: Trends In Sonar Researchmentioning

confidence: 99%

A comparison of the role of beamwidth in biological and engineered sonar

Todd

Müller²

2017

Bioinspir. Biomim.

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Sonar is an important sensory modality for engineers as well as in nature. In engineering, sonar is the dominating modality for underwater sensing. In biology, it is likely to have been a central factor behind the unprecedented evolutionary success of bats, a highly diverse group that accounts for over 20% of all mammal species. However, it remains unclear to what extent engineered and biosonar follow similar design and operational principles. In the current work, the key sonar design characteristic of beamwidth is examined in technical and biosonar. To this end, beamwidth data has been obtained for 23 engineered sonar systems and from numerical beampattern predictions for 151 emission and reception elements (noseleaves and pinnae) from bat biosonar. Beamwidth data from these sources is compared to the beamwidth of a planar ellipsoidal transducer as a reference. The results show that engineered and biological both obey the basic physical limit on beamwidth as a function of the ratio of aperture size and wavelength. However, beyond that, the beamwidth data revealed very different behaviors between the engineered and the biological sonar systems. Whereas the beamwidths of the technical sonar systems were very close to the planar transducer limit, the biological samples showed a very wide scatter away from this limit. This scatter was as large -if not wider -than what was seen in a small reference data set obtained with random aluminum cones. A possible interpretation of these differences in the variability could be that whereas sonar engineers try to minimize beamwidth subject to constraints on device size, the evolutionary optimization of bat biosonar beampatterns has been directed at other factors that have left beamwidth as a byproduct. Alternatively, the biosonar systems may require beamwidth values that are larger than the physical limit and differ between species and their sensory ecological niches.This work was supported by grants from the National Science Foundation (NSF Grant No. ID 1362886) and the Naval Engineering Education Consortium (NEEC, contract number N00174-16-C-0026). Comparison of the Role of Beamwidth in Biological and Engineered Sonar Bryan D. Todd (GENERAL AUDIENCE ABSTRACT)Sonar is an important method of sensing for engineers in undersea environments, but it is also used by several species of animals for for everyday use. The most prominent species that uses sonar, or echolocation, are bats, one of the most diverse groups of mammals. The study of bat biosonar systems serves as a counterpoint to many of the concepts in technical sonar. In technical sonar, arrays are made to be larger in size, with more elements, and operate at higher frequencies in order to decrease their beamwidth which increases their resolution. Unlike technical sonars bats must rely on smaller sized systems that they can carry around and they operate in air which has worse qualities for propagating sound waves. Even with these disadvantages, bats are able to operate in complex environments, such as dense vegetation, wit...

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“…In recent years, there has been a lively interest in target location using multistatic sonars [1][2][3][4][5][6][7][8][9][10][11][12][13]. In a multistatic sonar system, the sum of each pair of transmitter-target range and target-receiver range defines an ellipse.…”

Section: Introductionmentioning

confidence: 99%

“…Slightly more complex than the linear models, a quadratically constrained least squares model was constructed, which is generally difficult to solve effectively [27,30]. More recently, as another major methodology for parameter estimation, a Bayes estimator was presented for elliptical location, involving formidable numerical integration [4]. Intuitively, integrating other kinds of observations helps improve the positioning accuracy.…”

Section: Introductionmentioning

confidence: 99%

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Design and Analysis of a Non-Iterative Estimator for Target Location in Multistatic Sonar Systems with Sensor Position Uncertainties

Wang

Yang

et al. 2020

Mathematics

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Target location is the basic application of a multistatic sonar system. Determining the position/velocity vector of a target from the related sonar observations is a nonlinear estimation problem. The presence of possible sensor position uncertainties turns this problem into a more challenging hybrid parameter estimation problem. Conventional gradient-based iterative estimators suffer from the problems of initialization difficulties and local convergence. Even if there is no problem with initialization and convergence, a large computational cost is required in most cases. In view of these drawbacks, we develop a computationally efficient non-iterative position/velocity estimator. The main numerical computation involved is the weighted least squares optimization, which makes the estimator computationally efficient. Parameter transformation, model linearization and two-stage processing are exploited to prevent the estimator from iterative computation. Through performance analysis and experimental verification, we find that the proposed estimator reaches the hybrid Cramér–Rao bound and has linear computational complexity.

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A Bayesian Method for Localization by Multistatic Active Sonar

Cited by 30 publications

References 5 publications

A Modified Sampling Method for Localization Accuracy Improvement of Monte Carlo Localization

A Modified Sampling Method for Localization Accuracy Improvement of Monte Carlo Localization

A comparison of the role of beamwidth in biological and engineered sonar

Design and Analysis of a Non-Iterative Estimator for Target Location in Multistatic Sonar Systems with Sensor Position Uncertainties

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