Experiments in coherent change detection for synthetic aperture sonar

Sternlicht, Daniel D.; Harbaugh, J. Kent; Nelson, Matthew A.

doi:10.23919/oceans.2009.5422261

Cited by 6 publications

(3 citation statements)

References 5 publications

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“…Coherent change detection (CCD) is typically applied to satellite and synthetic aperture radar (SAR) imaging for the detection of subtle changes in a geographical region under investigation. [1][2][3] This technique relies on comparison, via interferometric-type processing, of old and new images of the region. It is therefore an imagingbased method pertinent to scenarios where imaging is possible via the knowledge of the propagation medium (e.g., air or free space) where wave propagation takes place from the reflection target to the sensors.…”

Section: Introductionmentioning

confidence: 99%

Physical layer mechanisms for coherent change detection

Marengo

2023

Radar Sensor Technology XXVII

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Coherent change detection (CCD) is an approach for detecting changes in a region that is based on interferometric-type processing of existing data or imagery. It is utilized in satellite and SAR imagery and is quite successful in the detection and localization of subtle scene changes. This work provides further expansion of the theoretical framework for this approach through the application of fundamental wave scattering principles. It is shown that this approach has an interesting physical interpretation, since it implicitly incorporates, as priors, power or energy-budget issues relevant to wave scattering and reflection phenomena. Moreover, a discussion of an alternative form that is more broadly applicable is provided. This general variant enables the detection of changes or threats (such as intrusion) even if the propagation medium is complex and completely unknown.

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Section: Introductionmentioning

confidence: 99%

Physical layer mechanisms for coherent change detection

Marengo

2023

Radar Sensor Technology XXVII

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“…Change detection has been studied for sidescan sonar in [1] and SAS in [2], [3]. In [4] and [5] the spatial decorrelation as a function of baseline (displacement of tracks) is discussed.…”

Section: Introductionmentioning

confidence: 99%

Change detection using Synthetic Aperture Sonar: Preliminary results from the Larvik trial

Midtgaard

Hansen

Sæbø

et al. 2011

Oceans'11 MTS/Ieee Kona

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In April of 2011, FFI led a sea trial near Larvik, Norway on FFIs research vessel the H.U. Sverdrup II with participation by representatives from Canada, United States, and France. One objective of the sea trial was to acquire a data set suitable for examining incoherent and coherent change detection and automated target recognition (ATR) algorithms applied to Synthetic Aperture Sonar (SAS) imagery. The end goal is to produce an automated tool for detecting recently placed objects on the seafloor. To test these algorithms two areas were chosen, one with a comparatively benign seafloor and one with a boulder strewn complex seafloor. Each area was surveyed before and after deployment of objects. The survey time intervals varied from two days to eight days. In this paper we present the trial and show examples of SAS images and change detection of the images.

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“…Single pass pairs are simultaneously collected from two separate receiver arrays on the same platform, while repeat-pass pairs are collected from a single receiver array but at different times. There are two common applications for interferometric processing: (1) bathymetric mapping of the seafloor [1,2] which typically uses single-pass pairs, and (2) coherent change detection (CCD) [3][4][5] using a repeat pass collection. CCD is a powerful method of detecting changes in a scene by making use of the coherent properties of SAS images and allows detection of sub-resolution sized changes [5].…”

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confidence: 99%

Exploitation of SAS interferometric phase statistics for coherent change detection

Shouldice,

Myers

2023

Electronics Letters

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Coherent change detection (CCD) takes advantage of the interferometric processing of synthetic aperture sonar (SAS) images and enables the detection of small scale changes to the scene between image pairs. This paper builds upon interferometric phase statistics developed for synthetic aperture radar and presents a method to differentiate between possible sources of decorrelation. A single‐pass pair of SAS images is categorized into four zones based on acoustic amplitude and coherence properties. Results suggest that regions of low coherence caused by a scene change can be differentiated from regions of low coherence due to other sources of decorrelation. Phase statistics could provide a technique to reduce the false alarm rate in CCD. Further studies are required to validate the approach for repeat‐pass SAS imagery and consider the effects of temporal decorrelation and misregistration errors on the phase distributions.

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Experiments in coherent change detection for synthetic aperture sonar

Cited by 6 publications

References 5 publications

Physical layer mechanisms for coherent change detection

Physical layer mechanisms for coherent change detection

Change detection using Synthetic Aperture Sonar: Preliminary results from the Larvik trial

Exploitation of SAS interferometric phase statistics for coherent change detection

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