Quantitative backscatter measurements with a long-range side-scan sonar

Mitchell, Neil C.; Somers, M. L.

doi:10.1109/48.35987

Cited by 59 publications

(50 citation statements)

References 10 publications

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“…Our estimate of G is probably accurate to within 6 dB; this is one of the largest sources of error in our calculations.This Time-Varied Gain (TVG) is used to compensate for the decreasing intensity of the backscattered signal and keeps the signal output within the dynamic range of the recorder. The TVG is not continuous but is actually produced in a series of 1.5-dB steps (Mitchell & Somers 1989) (2)…”

Section: Methodsmentioning

confidence: 99%

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Using Side-Scan Sonar instrument to Characterize and map of seabed identification target in punggur sea of the Riau Islands, Indonesia.

Lubis

Anurogo

Khoirunnisa

et al. 2017

J. Geoscience Eng. Environ. Technol.

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Punggur sea has many habitats, object, and structured of seabed with hight tide and wave. Side scan sonar is an underwater acoustic instrument for identification of seabed. This research aims to classify types of seabed and measure seabed identification into the sea water with grain size (dB), location, altitude (m) and target using side scan sonar instrument. This research also uses one types of side scan sonar in one places with 3 line of collecting data to get more variant seabed. Side scan sonar data of 20 km of side-scan sonar profiling (CM2, C-MAX Ltd, UK) with altitude max 20 m and a working acoustic frequency of 325 kHz with the zone is taken in the punggur sea (104°08.7102 E, 1°03.2448 N until 1°03.3977N 104°08.8133 E). The data side scan sonar processed using max view software to display the image of the seabed. Results of seabed imagery in the punggur sea on track 1 have Objects found on the ship coordinates 03.3101N 1 ° and 104 ° 08.7362 E with the highest gain value is 6 dB, altitude 18 m on ping 75. Linear regression has y = 0.7016x+12.952 with R 2 = 0.4125 (41%). Track 2 has target 1 is the sunken object on the seabed, while objects in the form of sand can be seen clearly. Objects found on the sunken object coordinates 1°02.8143 N ° and 104°08.5228 E with highest gain value is 9 dB with altitude 17.7 m and data ping 69. Linear regression has y = 0.2093+12.577 with R 2 = 0.2093 (20%). Track 3 has Target 1 is the ship object on the seabed, while objects in the form of sand can be seen clearly. Objects found on the sunken object coordinates 1°02.5817 N and 104°08.7337 E with the highest gain value is 8 dB with altitude 16.5 m and data ping 3984. Linear regression has y = 0.5106x +12.84 with R 2 = 0.5106 (51%). Track 1 has many targets identification results compared Track 2 and 3.

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Section: Methodsmentioning

confidence: 99%

“…To attenuate sidelobes in the correlator output, the rectangular FM pulse is correlated with an amplitude shaded (Hamming in Mitchell & Somers 1989) reference, rather than with a matched rectangular pulse. The equation of this Hamming function in (Mitchell & Somers 1989) is given by:…”

Section: Methodsmentioning

confidence: 99%

Using Side-Scan Sonar instrument to Characterize and map of seabed identification target in punggur sea of the Riau Islands, Indonesia.

Lubis

Anurogo

Khoirunnisa

et al. 2017

J. Geoscience Eng. Environ. Technol.

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“…Similar techniques have also been utilized in the interpretation of side-scan sonar data (e.g. Blondel et al, 1998;Carmichael et al, 1996;Huvenne et al, 2002;Mitchell and Somers, 1989). Geomorphometric techniques have generally performed well in submarine environments.…”

Section: Marine Geomorphology Geophysics and Geohazardsmentioning

confidence: 99%

A review of marine geomorphometry, the quantitative study of the seafloor

Lecours

Dolan

Micallef

et al. 2016

Hydrol. Earth Syst. Sci.

183

120

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Abstract. Geomorphometry, the science of quantitative terrain characterization, has traditionally focused on the investigation of terrestrial landscapes. However, the dramatic increase in the availability of digital bathymetric data and the increasing ease by which geomorphometry can be investigated using geographic information systems (GISs) and spatial analysis software has prompted interest in employing geomorphometric techniques to investigate the marine environment. Over the last decade or so, a multitude of geomorphometric techniques (e.g. terrain attributes, feature extraction, automated classification) have been applied to characterize seabed terrain from the coastal zone to the deep sea. Geomorphometric techniques are, however, not as varied, nor as extensively applied, in marine as they are in terrestrial environments. This is at least partly due to difficulties associated with capturing, classifying, and validating terrain characteristics underwater. There is, nevertheless, much common ground between terrestrial and marine geomorphometry applications and it is important that, in developing marine geomorphometry, we learn from experiences in terrestrial studies. However, not all terrestrial solutions can be adopted by marine geomorphometric studies since the dynamic, fourdimensional (4-D) nature of the marine environment causes its own issues throughout the geomorphometry workflow. For instance, issues with underwater positioning, variations in sound velocity in the water column affecting acousticbased mapping, and our inability to directly observe and measure depth and morphological features on the seafloor are all issues specific to the application of geomorphometry in the marine environment. Such issues fuel the need for a dedicated scientific effort in marine geomorphometry.This review aims to highlight the relatively recent growth of marine geomorphometry as a distinct discipline, and offers the first comprehensive overview of marine geomorphometry to date. We address all the five main steps of geomorphometry, from data collection to the application of terrain attributes and features. We focus on how these steps are relevant to marine geomorphometry and also highlight differences and similarities from terrestrial geomorphometry. We conclude with recommendations and reflections on the future of marine geomorphometry. To ensure that geomorphometry is used and developed to its full potential, there is a need to increase awareness of (1) marine geomorphometry amongst scientists already engaged in terrestrial geomorphometry, and of (2) geomorphometry as a science amongst marine scientists with a wide range of backgrounds and experiences.

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“…The various generations of sensing systems have incrementally been building up a repertoire of processing mechanisms to deal with various sources of error. We shall revisit in some depth in Chapter 2, some of these issues for the sensors dealt with in this thesis, but the reader may also wish to refer to specific examples of processing side-scan sonar data from GLORIA [79] AUVs lies not in the actual sensors but rather in integrating these sensors on the platform in question. When the accuracy of our navigation system is lesser that the accuracy of the resolution of the sensor by orders of magnitude then this shows up as inconsistencies in the mapping efforts when we try to grid the sensor data to the limits of sensor resolution.…”

Section: Side Scan Sonar Technology Todaymentioning

confidence: 99%

An entropic framework for AUV sensor modelling

Singh¹

1995

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Quantitative backscatter measurements with a long-range side-scan sonar

Cited by 59 publications

References 10 publications

Using Side-Scan Sonar instrument to Characterize and map of seabed identification target in punggur sea of the Riau Islands, Indonesia.

Using Side-Scan Sonar instrument to Characterize and map of seabed identification target in punggur sea of the Riau Islands, Indonesia.

A review of marine geomorphometry, the quantitative study of the seafloor

An entropic framework for AUV sensor modelling

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