A novel location estimation based on pattern matching algorithm in underwater environments

Lee, Kun Chou; Ou, Jhih Sian; Huang, Min; Fang, Ming-Chung

doi:10.1016/j.apacoust.2008.05.004

Cited by 19 publications

(17 citation statements)

References 13 publications

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“…Along the same line, some systems have been proposed that attempt to localize a node based on a collection of acoustic channel fingerprints measured in the localization area [1]. Similarly, [5] proposes to localize based on the matching of a received fingerprint against a set of fingerprints measured by an array of receivers. However, the practical application of systematic fingerprint measurements beyond controlled environments seems limited due to the rapidly changing nature of underwater acoustic channels.…”

Section: Related Workmentioning

confidence: 99%

“…Based on the knowledge of the local bathymetry and SSP, we create a model of multipath propagation in the localization area without any substantial offline preparation phase. Unlike in [5], this process does not require any explicit measurements. We then track the path of the source by leveraging the channel response differences induced by bottom reflections of the acoustic signals from different locations.…”

Section: Related Workmentioning

confidence: 99%

“…In this paper, we extend the state of the art and propose an approach to localize a source emitting acoustic signals via a single receiver moored at a fixed location. Our approach is inspired by indoor fingerprinting localization approaches, e.g., [5], and hinges on the spatial diversity of the sea bottom bathymetry. Specifically, we target those environments where the bathymetry and the sound speed profile (SSP) in the water column induce different channel impulse responses (CIRs) for different emitter-receiver location pairs.…”

Section: Introductionmentioning

confidence: 99%

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Anchorless underwater acoustic localization

Dubrovinskaya

Diamant

Casari

2017

2017 14th Workshop on Positioning, Navigation and Communications (WPNC)

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We consider the problem of estimating the trajectory of a submerged source emitting acoustic signals without using any anchor nodes or receiving array. This approach is required for several applications, including the localization of acoustic sources such as marine mammals or underwater vehicles, for which the cost of covering a broad area with multiple receivers would be excessively high. Since multi-lateration is impossible in this scenario, we perform localization by incorporating bathymetry information. Specifically, we assume that the receiver retains knowledge of the environmental parameters that affect the signal propagation, and that the bathymetry of the area is sufficiently diverse to induce distinguishable channel impulse responses for different source locations. Our method compares the channel estimates obtained from the received acoustic signals against a database of channel responses, pre-computed through an acoustic ray tracing model. The set of possible node locations that result are then organized in trellis form to obtain a final estimate of the source's trajectory via a path tracking method similar to the Viterbi algorithm. Our results show that the proposed approach can estimate node locations and paths with very small error, provided that the receiver has sufficiently accurate and up-todate environmental information.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Anchorless underwater acoustic localization

Dubrovinskaya

Diamant

Casari

2017

2017 14th Workshop on Positioning, Navigation and Communications (WPNC)

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“…In some literature it has been mainly assumed that the RSS value is converted to the distance and they pay less attention on the this conversion circumstance [7]. Reference [8] categorized its proposed network operations into two steps: offline and online. In offline mode, several devices beacon at different distances to sensors.…”

Section: Introductionmentioning

confidence: 99%

Efficient Underwater RSS Value to Distance Inversion Using the Lambert Function

Hosseini

Chizari

Poston³

et al. 2014

Mathematical Problems in Engineering

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There are many applications for using wireless sensor networks (WSN) in ocean science; however, identifying the exact location of a sensor by itself (localization) is still a challenging problem, where global positioning system (GPS) devices are not applicable underwater. Precise distance measurement between two sensors is a tool of localization and received signal strength (RSS), reflecting transmission loss (TL) phenomena, is widely used in terrestrial WSNs for that matter. Underwater acoustic sensor networks have not been used (UASN), due to the complexity of the TL function. In this paper, we addressed these problems by expressing underwater TL via the Lambert W function, for accurate distance inversion by the Halley method, and compared this to Newton-Raphson inversion. Mathematical proof, MATLAB simulation, and real device implementation demonstrate the accuracy and efficiency of the proposed equation in distance calculation, with fewer iterations, computation stability for short and long distances, and remarkably short processing time. Then, the sensitivities of LambertWfunction and Newton-Raphson inversion to alteration in TL were examined. The simulation results showed that LambertWfunction is more stable to errors than Newton-Raphson inversion. Finally, with a likelihood method, it was shown that RSS is a practical tool for distance measurement in UASN.

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“…In other words, not only the existence of fishes but also the fish type can be identified. For instance, Lee, et al [6] proposed a novel location estimation approach based on maximum likelihood approach to underwater localization based on signals collected by the sound receivers.…”

Section: Introductionmentioning

confidence: 99%

Using echo ultrasound from schooling fish to detect and classify fish types

Handoko

Nazaruddin

2009

J Bionic Eng

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Fish finders have already been widely available in the fishing market for a number of years. However, the sizes of these fish finders are too big and their prices are expensive to suit for the research of robotic fish or mini-submarine. The goal of this research is to propose a low-cost fish detector and classifier which suits for underwater robot or submarine as a proximity sensor. With some pre-condition in hardware and algorithms, the experimental results show that the proposed design has good performance, with maximum value 100% detection and 94% classification of two types of fish. Both the existing type of fish and the group behavior can be revealed by statistical interpretations such as hovering passion and sparse swimming mode.

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A novel location estimation based on pattern matching algorithm in underwater environments

Cited by 19 publications

References 13 publications

Anchorless underwater acoustic localization

Anchorless underwater acoustic localization

Efficient Underwater RSS Value to Distance Inversion Using the Lambert Function

Using echo ultrasound from schooling fish to detect and classify fish types

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