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. 
A new method for obtaining velocity and diffusivity from timedependent distributions of a tracer via the maximum likelihood estimator for the advectiondiffusion equation
An inverse problem for the advectiondiffusion equation is considered, and a method of maximum likelihood (ML) estimation is developed to derive velocity and diffusivity from timedependent distributions of a tracer. Piterbarg and Rozovskii showed theoretically that the ML estimator for diffusivity is consistent ever in an asymptotic case of infinite number of observational spatial modes. In the present work, the ML estimator is studied based on numerical experiments with a tracer in a twodimensional flow under the condition of a limited number of observations in space. The numerical experiments involve the direct and the inverse problems. For the former, themore » 
Efficient LevenbergMarquardt minimization of the maximum likelihood estimator for Poisson deviates
Histograms of counted events are Poisson distributed, but are typically fitted without justification using nonlinear least squares fitting. The more appropriate maximum likelihood estimator (MLE) for Poisson distributed data is seldom used. We extend the use of the LevenbergMarquardt algorithm commonly used for nonlinear least squares minimization for use with the MLE for Poisson distributed data. In so doing, we remove any excuse for not using this more appropriate MLE. We demonstrate the use of the algorithm and the superior performance of the MLE using simulations and experiments in the context of fluorescence lifetime imaging. Scientists commonly form histograms ofmore » 
Measuring galaxy cluster masses with CMB lensing using a Maximum Likelihood estimator: statistical and systematic error budgets for future experiments
We develop a Maximum Likelihood estimator (MLE) to measure the masses of galaxy clusters through the impact of gravitational lensing on the temperature and polarization anisotropies of the cosmic microwave background (CMB). We show that, at low noise levels in temperature, this optimal estimator outperforms the standard quadratic estimator by a factor of two. For polarization, we show that the Stokes Q/U maps can be used instead of the traditional E and Bmode maps without losing information. We test and quantify the bias in the recovered lensing mass for a comprehensive list of potential systematic errors. Using realistic simulations, wemore »