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Title: SAR image effects on coherence and coherence estimation.

Abstract

Radar coherence is an important concept for imaging radar systems such as synthetic aperture radar (SAR). This document quantifies some of the effects in SAR which modify the coherence. Although these effects can disrupt the coherence within a single SAR image, this report will focus on the coherence between separate images, such as for coherent change detection (CCD) processing. There have been other presentations on aspects of this material in the past. The intent of this report is to bring various issues that affect the coherence together in a single report to support radar engineers in making decisions about these matters.

Authors:
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1147517
Report Number(s):
SAND2014-0369
498351
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English

Citation Formats

Bickel, Douglas Lloyd. SAR image effects on coherence and coherence estimation.. United States: N. p., 2014. Web. doi:10.2172/1147517.
Bickel, Douglas Lloyd. SAR image effects on coherence and coherence estimation.. United States. doi:10.2172/1147517.
Bickel, Douglas Lloyd. Wed . "SAR image effects on coherence and coherence estimation.". United States. doi:10.2172/1147517. https://www.osti.gov/servlets/purl/1147517.
@article{osti_1147517,
title = {SAR image effects on coherence and coherence estimation.},
author = {Bickel, Douglas Lloyd},
abstractNote = {Radar coherence is an important concept for imaging radar systems such as synthetic aperture radar (SAR). This document quantifies some of the effects in SAR which modify the coherence. Although these effects can disrupt the coherence within a single SAR image, this report will focus on the coherence between separate images, such as for coherent change detection (CCD) processing. There have been other presentations on aspects of this material in the past. The intent of this report is to bring various issues that affect the coherence together in a single report to support radar engineers in making decisions about these matters.},
doi = {10.2172/1147517},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Jan 01 00:00:00 EST 2014},
month = {Wed Jan 01 00:00:00 EST 2014}
}

Technical Report:

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  • MREG V1.1 is the sixth generation SAR image registration algorithm developed by the Signal Processing&Technology Department for Synthetic Aperture Radar applications. Like its predecessor algorithm REGI, it employs a powerful iterative multi-scale paradigm to achieve the competing goals of sub-pixel registration accuracy and the ability to handle large initial offsets. Since it is not model based, it allows for high fidelity tracking of spatially varying terrain-induced misregistration. Since it does not rely on image domain phase, it is equally adept at coherent and noncoherent image registration. This document provides a brief history of the registration processors developed by Dept. 5962more » leading up to MREG V1.1, a full description of the signal processing steps involved in the algorithm, and a user's manual with application specific recommendations for CCD, TwoColor MultiView, and SAR stereoscopy.« less
  • While typical SAR imaging employs a co-located (monostatic) RADAR transmitter and receiver, bistatic SAR imaging separates the transmitter and receiver locations. The transmitter and receiver geometry determines if the scattered signal is back scatter, forward scatter, or side scatter. The monostatic SAR image is backscatter. Therefore, depending on the transmitter/receiver collection geometry, the captured imagery may be quite different that that sensed at the monostatic SAR. This document presents imagery and image products formed from captured signals during the validation stage of the bistatic SAR research. Image quality and image characteristics are discussed first. Then image products such as two-colormore » multi-view (2CMV) and coherent change detection (CCD) are presented.« less
  • This report describes the significant processing steps that were used to take the raw recorded digitized signals from the bistatic synthetic aperture RADAR (SAR) hardware built for the NCNS Bistatic SAR project to a final bistatic SAR image. In general, the process steps herein are applicable to bistatic SAR signals that include the direct-path signal and the reflected signal. The steps include preprocessing steps, data extraction to for a phase history, and finally, image format. Various plots and values will be shown at most steps to illustrate the processing for a bistatic COSMO SkyMed collection gathered on June 10, 2013more » on Kirtland Air Force Base, New Mexico.« less
  • Complex pixel values for Synthetic Aperture Radar (SAR) images of uniform distributed clutter can be represented as either real/imaginary (also known as I/Q) values, or as Magnitude/Phase values. Generally, these component values are integers with limited number of bits. For clutter energy well below full-scale, Magnitude/Phase offers lower quantization noise than I/Q representation. Further improvement can be had with companding of the Magnitude value.
  • This report presents a quantization analysis of the digital image formation processor (IFP) of a linear-FM synthetic aperture radar (SAR). The IFP is configured as a patch processor and forms the final image by performing a two dimensional Fast Fourier Transform (FFT). The quantization analysis examines the effects of using fixed precision arithmetic in the image formation process. Theoretical bounds for the worst-case errors introduced by using fixed point arithmetic and experimental results verifying the theoretical bounds are presented. 34 refs., 23 figs., 7 tabs.