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Title: A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection.

Abstract

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 clutter-to-noise 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 maximum-likelihood (ML) sense. The estimator produces very impressive results on the CCD collects that we have tested.

Authors:
; ;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1159161
Report Number(s):
SAND2014-18179
537768
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English

Citation Formats

Wahl, Daniel E., Yocky, David A., and Jakowatz, Charles V,. A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection.. United States: N. p., 2014. Web. doi:10.2172/1159161.
Wahl, Daniel E., Yocky, David A., & Jakowatz, Charles V,. A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection.. United States. doi:10.2172/1159161.
Wahl, Daniel E., Yocky, David A., and Jakowatz, Charles V,. 2014. "A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection.". United States. doi:10.2172/1159161. https://www.osti.gov/servlets/purl/1159161.
@article{osti_1159161,
title = {A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection.},
author = {Wahl, Daniel E. and Yocky, David A. and Jakowatz, Charles V,},
abstractNote = {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 clutter-to-noise 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 maximum-likelihood (ML) sense. The estimator produces very impressive results on the CCD collects that we have tested.},
doi = {10.2172/1159161},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2014,
month = 9
}

Technical Report:

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  • Abstract not provided.
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