Paul L. Poehler

Adaptive compression algorithm results for complex synthetic aperture radar data

Research conducted on complex Synthetic Aperture Radar (SAR) data over the last two years has culminated in the development of a compression algorithm1 compatible with current imagery standards. This new algorithm also includes adaptive attributes which identify the radar data type, data characteristics, and then selects optimal quantization parameters, generated based on the statistics of the data, from a knowledge base. This algorithm has achieved near-lossless compression ratios in excess of 20 to 1, with reduced Root Mean Square Error (RMSE) and increased Peak Signal to Noise Ratio (PSNR). This algorithm also produces minimal degradation when producing phase-derived radar products. This paper describes the algorithm development, operation, and test results obtained using this compression algorithm., The algorithm component elements are described including the use of an adaptive preprocessor, modified quantizer, and knowledge base. This paper details the improved results observed for compressed data, magnitude imagery, and phase-derived products generated during the study.

SAR coherent change detection (CCD) for search and rescue

Recent advances in the areas of phase history processing, interferometry, and radargrammetric adjustment have made possible extremely accurate information extraction from synthetic aperture radar (SAR) image pairs by means of interferometric techniques. The potential gain in accuracy is significant since measurements can theoretically be determined to within a fraction of a wavelength (subcentimeter accuracy) as opposed to a fraction of pixel distance (meter accuracy). One promising application of interferometric SAR (IFSAR) is the use of coherent change detection (CCD) over large areas to locate downed aircraft. This application poses an additional challenge since IFSAR must be processed at longer wavelengths to achieve foliage penetration. In this paper a combination of advanced techniques is described for using airborne SAR imagery to carry out this mission. Performance parameters are derived, and some examples are given from actual data.

Digital workstation for Venus topographic mapping

A digital workstation was developed and is currently at the U.S. Geological Survey (USGS) in Flagstaff, Arizona to be used for Venus topographic mapping. The system is based on a mapping and geocoding image correlation (GIS MAGIC) system developed by Science Applications International Corporation (SAIC) for the creation of precisely geocoded imagery data bases for both optical and synthetic aperture radar (SAR) imagery. A multitude of data from various sources has been processed, including conventional aerial photographs, airborne and orbital SAR, and Spot. This paper covers the GIS MAGIC development history, hardware/software features and capabilities. Also covered are the types of modifications required to accommodate Venus radar data and results which can be achieved using the GIS MAGIC System.

Complex synthetic aperture radar data compression

Existing compression algorithms, primarily designed for visible electro-optical (EO) imagery, do not work well for Synthetic Aperture Radar (SAR) data. The best compression ratios achieved to date are less than 10:1 with minimal degradation to the phase data. Previously, phase data has been discarded with only magnitude data saved for analysis. Now that the importance of phase has been recognized for Interferometric Synthetic Aperture Radar (IFSAR), Coherent Change Detection (CCD), and polarimetry, requirements exist to preserve, transmit, and archive the both components. Bandwidth and storage limitations on existing and future platforms make compression of this data a top priority. This paper presents results obtained using a new compression algorithm designed specifically to compress SAR imagery, while preserving both magnitude and phase information at compression ratios of 20:1 and better.

Wavenumber shift in search and rescue synthetic aperture radar

The wavenumber shift is an important tool in multiple pass synthetic aperture radar interferometry. In addition to overcoming baseline decorrelation, it has proven to have additional benefits. Chief among these is the ability to filter out much of the decorrelated signal, leaving the coherent portion. In the presence of foliage induced temporal decorrelation, this corresponds to filtering out much of the foliage return while strengthening any coherent ground return. We will examine this and other benefits of the wavenumber shift within the context of the Search and Rescue SAR program. An example based on ERS 1/2 data is provided.

Complex data compression techniques: some new approaches

The most important parameter in search and rescue is the time it takes to locate the downed aircraft and rescue the survivors. The resulting requirement for wide-area coverage, fine resolution, and day-night all-weather operation dictates the use of a synthetic aperture radar (SAR) sensor. The time urgency combined with the high data volume leads to the need for a new type of data compression. This paper presents and evaluates candidate compression algorithms for SAR raw phase history and for SAR complex imagery.

Foliage problem in interferometric SAR

Interferometric SAR exploits the coherent nature of multiple synthetic aperture radar images to recover phase (range difference) information and thence terrain evaluation data as well as other phase derivative products such as Coherent Change Detection (CCD). Of the numerous factors that can degrade the coherency of multiple SAR collections, foliage constitutes one of the most challenging. The foliage problem in IFSAR is discussed and an airborne multiple pass collection is used to illustrate some facets of the problem. Resolution as a variable in the tradeoff between the bias and variance of the interferogram is discussed in the context of the example.

IFSAR phase unwrapping in foliage and extreme terrain

Recent advances in the areas of phase history processing, interferometric SAR (IFSAR) processing algorithms, and radargrammetric adjustment have made it possible to extract extremely accurate Digital Elevation Model (DEM) information from SAR images. Results of tests using recent improvements by the authors in the phase unwrapping and interferogram conditioning steps show that it might be possible to obtain good elevation accuracy from noisy interferograms resulting from foliage or extreme terrain. Results of ERS-1/ERS-2 Tandem data are presented.

IFSAR reductions from ERS-1,/2 tandem data

Recent advantages in the areas of phase history processing, interferometric synthetic aperture radar processing algorithms, and the use of photogrammetric techniques have made it possible to extract extremely accurate DEM generation from Synthetic Aperture Radar images. Recent improvements by the authors in the phase unwrapping and interferogram conditioning steps are described which make it possible to obtain good elevation accuracy from noisy interferograms resulting from temporal decorrelation due to foliage or extreme terrain. Results are shown of data reductions from separate passes of the ERS-1,/2 Tandem System over Ft. Irwin, California, and Aschaffenburg, Germany.

IFSAR phase unwrapping in the presence of Dirichlet boundary conditions

Phase unwrapping is one of the key computational elements in digital elevation model generation from interferometric SAR. In this paper we present a reformulation of the weighted least squares phase unwrapping approach that incorporates Dirichlet boundary conditions. The application of this formulation to the incorporation of control points into the solution as well as for unwrapping the interferogram in stages is discussed. The ability of the weighted least squares approach to fully unwrap an interferogram can be very dependent on the weight matrix used. This has led us to develop an adaptive approach to updating the weight matrix to be used in conjunction with our weighted least squares approach. Examples along the preliminary results based on ERS data will be presented.