skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Estimating IMU heading error from SAR images.

Abstract

Angular orientation errors of the real antenna for Synthetic Aperture Radar (SAR) will manifest as undesired illumination gradients in SAR images. These gradients can be measured, and the pointing error can be calculated. This can be done for single images, but done more robustly using multi-image methods. Several methods are provided in this report. The pointing error can then be fed back to the navigation Kalman filter to correct for problematic heading (yaw) error drift. This can mitigate the need for uncomfortable and undesired IMU alignment maneuvers such as S-turns.

Authors:
Publication Date:
Research Org.:
Sandia National Laboratories
Sponsoring Org.:
USDOE
OSTI Identifier:
952099
Report Number(s):
SAND2009-0183
TRN: US200913%%345
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
47 OTHER INSTRUMENTATION; ALIGNMENT; ANTENNAS; RADAR; IMAGES; DEFECTS; Error functions.; Synthetic aperture radar-Performance.

Citation Formats

Doerry, Armin Walter. Estimating IMU heading error from SAR images.. United States: N. p., 2009. Web. doi:10.2172/952099.
Doerry, Armin Walter. Estimating IMU heading error from SAR images.. United States. doi:10.2172/952099.
Doerry, Armin Walter. Sun . "Estimating IMU heading error from SAR images.". United States. doi:10.2172/952099. https://www.osti.gov/servlets/purl/952099.
@article{osti_952099,
title = {Estimating IMU heading error from SAR images.},
author = {Doerry, Armin Walter},
abstractNote = {Angular orientation errors of the real antenna for Synthetic Aperture Radar (SAR) will manifest as undesired illumination gradients in SAR images. These gradients can be measured, and the pointing error can be calculated. This can be done for single images, but done more robustly using multi-image methods. Several methods are provided in this report. The pointing error can then be fed back to the navigation Kalman filter to correct for problematic heading (yaw) error drift. This can mitigate the need for uncomfortable and undesired IMU alignment maneuvers such as S-turns.},
doi = {10.2172/952099},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Mar 01 00:00:00 EST 2009},
month = {Sun Mar 01 00:00:00 EST 2009}
}

Technical Report:

Save / Share:
  • SAR range-Doppler images are inherently 2-dimensional. Targets with a height offset lay over onto offset range and azimuth locations. Just which image locations are laid upon depends on the imaging geometry, including depression angle, squint angle, and target bearing. This is the well known layover phenomenon. Images formed with different aperture geometries will exhibit different layover characteristics. These differences can be exploited to ascertain target height information, in a stereoscopic manner. Depending on the imaging geometries, height accuracy can be on the order of horizontal position accuracies, thereby rivaling the best IFSAR capabilities in fine resolution SAR images. All thatmore » is required for this to work are two distinct passes with suitably different geometries from any plain old SAR.« less
  • SAR imagery for coastline detection has many potential advantages over conventional optical stereoscopic techniques. For example, SAR does not have restrictions on being collected during daylight or when there is no cloud cover. In addition, the techniques for coastline detection witth SAR images can be automated. In this paper, we present the algorithmic development of an automatic coastline detector for use with SAR imagery. Three main algorithms comprise the automatic coastline detection algorithm, The first algorithm considers the image pre-processing steps that must occur on the original image in order to accentuate the land/water boundary. The second algorithm automatically followsmore » along the accentuated land/water boundary and produces a single-pixel-wide coastline. The third algorithm identifies islands and marks them. This report describes in detail the development of these three algorithms. Examples of imagery are used throughout the paper to illustrate the various steps in algorithms. Actual code is included in appendices. The algorithms presented are preliminary versions that can be applied to automatic coastline detection in SAR imagery. There are many variations and additions to the algorithms that can be made to improve robustness and automation, as required by a particular application.« less
  • The objective of this work was to develop a systematic method of combining multifrequency polarized SAR images. It is shown that the traditional methods of correlation, hard targets, and template matching fail to produce acceptable results. Hence, a new algorithm was developed and tested. The new approach combines the three traditional methods and an interpolation method. An example is shown that demonstrates the new algorithms performance. The results are summarized suggestions for future research are presented.
  • SAR phase history data represents a polar array in the Fourier space of a scene being imaged. Polar Format processing is about reformatting the collected SAR data to a Cartesian data location array for efficient processing and image formation. In a real-time system, this reformatting or ''re-gridding'' operation is the most processing intensive, consuming the majority of the processing time; it also is a source of error in the final image. Therefore, any effort to reduce processing time while not degrading image quality is valued. What is proposed in this document is a new way of implementing real-time polar-format processingmore » through a variation on the traditional interpolation/2-D Fast Fourier Transform (FFT) algorithm. The proposed change is based upon the frequency scaling property of the Fourier Transform, which allows a post azimuth FFT interpolation. A post azimuth processing interpolation provides overall benefits to image quality and potentially more efficient implementation of the polar format image formation process.« less