A new maximumlikelihood change estimator for twopass SAR coherent change detection
Abstract
In past research, twopass repeatgeometry synthetic aperture radar (SAR) coherent change detection (CCD) predominantly utilized the sample degree of coherence as a measure of the temporal change occurring between two complexvalued image collects. Previous coherencebased CCD approaches tend to show temporal change when there is none in areas of the image that have a low cluttertonoise power ratio. Instead of employing the sample coherence magnitude as a change metric, in this paper, we derive a new maximumlikelihood (ML) temporal change estimate—the complex reflectance change detection (CRCD) metric to be used for SAR coherent temporal change detection. The new CRCD estimator is a surprisingly simple expression, easy to implement, and optimal in the ML sense. As a result, this new estimate produces improved results in the coherent pair collects that we have tested.
 Authors:
 Sandia National Lab. (SNLNM), Albuquerque, NM (United States)
 Publication Date:
 Research Org.:
 Sandia National Lab. (SNLNM), Albuquerque, NM (United States)
 Sponsoring Org.:
 USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation (NA20)
 OSTI Identifier:
 1237379
 Report Number(s):
 SAND20152024J
Journal ID: ISSN 01962892; 569615
 Grant/Contract Number:
 AC0494AL85000
 Resource Type:
 Journal Article: Accepted Manuscript
 Journal Name:
 IEEE Transactions on Geoscience and Remote Sensing
 Additional Journal Information:
 Journal Volume: PP; Journal Issue: 99; Journal ID: ISSN 01962892
 Country of Publication:
 United States
 Language:
 English
 Subject:
 58 GEOSCIENCES; 47 OTHER INSTRUMENTATION; coherent change detection; maximum likelihood estimator; radar interferometry; synthetic aperture radar
Citation Formats
Wahl, Daniel E., Yocky, David A., Jakowatz, Jr., Charles V., and Simonson, Katherine Mary. A new maximumlikelihood change estimator for twopass SAR coherent change detection. United States: N. p., 2016.
Web. doi:10.1109/TGRS.2015.2502219.
Wahl, Daniel E., Yocky, David A., Jakowatz, Jr., Charles V., & Simonson, Katherine Mary. A new maximumlikelihood change estimator for twopass SAR coherent change detection. United States. doi:10.1109/TGRS.2015.2502219.
Wahl, Daniel E., Yocky, David A., Jakowatz, Jr., Charles V., and Simonson, Katherine Mary. 2016.
"A new maximumlikelihood change estimator for twopass SAR coherent change detection". United States.
doi:10.1109/TGRS.2015.2502219. https://www.osti.gov/servlets/purl/1237379.
@article{osti_1237379,
title = {A new maximumlikelihood change estimator for twopass SAR coherent change detection},
author = {Wahl, Daniel E. and Yocky, David A. and Jakowatz, Jr., Charles V. and Simonson, Katherine Mary},
abstractNote = {In past research, twopass repeatgeometry synthetic aperture radar (SAR) coherent change detection (CCD) predominantly utilized the sample degree of coherence as a measure of the temporal change occurring between two complexvalued image collects. Previous coherencebased CCD approaches tend to show temporal change when there is none in areas of the image that have a low cluttertonoise power ratio. Instead of employing the sample coherence magnitude as a change metric, in this paper, we derive a new maximumlikelihood (ML) temporal change estimate—the complex reflectance change detection (CRCD) metric to be used for SAR coherent temporal change detection. The new CRCD estimator is a surprisingly simple expression, easy to implement, and optimal in the ML sense. As a result, this new estimate produces improved results in the coherent pair collects that we have tested.},
doi = {10.1109/TGRS.2015.2502219},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
number = 99,
volume = PP,
place = {United States},
year = 2016,
month = 1
}
Web of Science

Abstract not provided.

A New MaximumLikelihood Change Estimator for TwoPass SAR Coherent Change Detection.
In this paper, we derive a new optimal change metric to be used in synthetic aperture RADAR (SAR) coherent change detection (CCD). Previous CCD methods tend to produce false alarm states (showing change when there is none) in areas of the image that have a low cluttertonoise power ratio (CNR). The new estimator does not suffer from this shortcoming. It is a surprisingly simple expression, easy to implement, and is optimal in the maximumlikelihood (ML) sense. The estimator produces very impressive results on the CCD collects that we have tested. 
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