Publications

Imaging systems such as Synthetic Aperture Radar collect band-limited data from which an image of a target scene is rendered. The band-limited nature of the data generates sidelobes, or ''spilled energy'' most evident in the neighborhood of bright point-like objects. It is generally considered desirable to minimize these sidelobes, even at the expense of some generally small increase in system bandwidth. This is accomplished by shaping the spectrum with window functions prior to inversion or transformation into an image. A window function that minimizes sidelobe energy can be constructed based on prolate spheroidal wave functions. A parametric design procedure allows doing so even with constraints on allowable increases in system bandwidth. This approach is extended to accommodate spectral notches or holes, although the guaranteed minimum sidelobe energy can be quite high in this case. Interestingly, for a fixed bandwidth, the minimum-mean-squared-error image rendering of a target scene is achieved with no windowing at all (rectangular or boxcar window).

A Synthetic Aperture Radar (SAR) image is a two-dimensional projection of the radar reflectivity from a 3-dimensional object or scene. Stereoscopic SAR employs two SAR images from distinct flight paths that can be processed together to extract information of the third collapsed dimension (typically height) with some degree of accuracy. However, more than two SAR images of the same scene can similarly be processed to further improve height accuracy, and hence 3-dimensional position accuracy. This report shows how.

Superresolution concepts offer the potential of resolution beyond the classical limit. This great promise has not generally been realized. In this study we investigate the potential application of superresolution concepts to synthetic aperture radar. The analytical basis for superresolution theory is discussed. The application of the concept to synthetic aperture radar is investigated as an operator inversion problem. Generally, the operator inversion problem is ill posed. A criterion for judging superresolution processing of an image is presented.

Abstract not provided.

Interferometric SAR (IFSAR) can be shown to be a special case of 3-D SAR image formation. In fact, traditional IFSAR processing results in the equivalent of merely a super-resolved, under-sampled, 3-D SAR image. However, when approached as a 3-D SAR problem, a number of IFSAR properties and anomalies are easily explained. For example, IFSAR decorrelation with height is merely ordinary migration in 3-D SAR. Consequently, treating IFSAR as a 3-D SAR problem allows insight and development of proper motion compensation techniques and image formation operations to facilitate optimal height estimation. Furthermore, multiple antenna phase centers and baselines are easily incorporated into this formulation, providing essentially a sparse array in the elevation dimension. This paper shows the Polar Format image formation algorithm extended to 3 dimensions, and then proceeds to apply it to the IFSAR collection geometry. This suggests a more optimal reordering of the traditional IFSAR processing steps.

The requirement to efficiently form images over a large range of geometries has a profound impact on the design of a Synthetic Aperture Radar (SAR) system. This article shows how a data set conducive to efficient processing might increase the total RF bandwidth. It also presents examples of how a fixed RF bandwidth might then limit SAR geometries.

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 that is required for this to work are two distinct passes with suitably different geometries from any plain old SAR.

Lynx is a high resolution, synthetic aperture radar (SAR) that has been designed and built by Sandia National Laboratories in collaboration with General Atomics (GA). Although Lynx may be operated on a wide variety of manned and unmanned platforms, it is primarily intended to be fielded on unmanned aerial vehicles. In particular, it may be operated on the Predator, I-GNAT, or Prowler II platforms manufactured by GA Aeronautical Systems, Inc. The Lynx production weight is less than 120 lb. and has a slant range of 30 km (in 4 mm/hr rain). It has operator selectable resolution and is capable of 0.1 m resolution in spotlight mode and 0.3 m resolution in stripmap mode. In ground moving target indicator mode, the minimum detectable velocity is 6 knots with a minimum target cross-section of 10 dBsm. In coherent change detection mode, Lynx makes registered, complex image comparisons either of 0.1 m resolution (minimum) spotlight images or of 0.3 m resolution (minimum) strip images. The Lynx user interface features a view manager that allows it to pan and zoom like a video camera. Lynx was developed under corporate finding from GA and will be manufactured by GA for both military and commercial applications. The Lynx system architecture will be presented and some of its unique features will be described. Imagery at the finest resolutions in both spotlight and strip modes have been obtained and will also be presented.

This paper addresses theoretical aspects of forming images from an airborne Synthetic Aperture Radar (SAR) of targets buried below the earth's surface. Soil is generally a lossy, dispersive medium, with wide ranging variability in these attributes depending on soil type, moisture content, and a host of other physical properties. Focussing a SAR subsurface image presents new dimensions of complexity relative to its surface-image counterpart, even when the soil's properties are known. This paper treats the soil as a lossy, dispersive half space, and presents a practical model for the radar echo-delay time to point scatterers within it. This model is then used to illustrate effects of refraction, dispersion, and attenuation on a SAR's phase histories, and the resulting image. Various data collection geometries and processing strategies are examined for both 2-Dimensional and 3-Dimensional SAR images. The conclusions from this work are that 1) focussing a SAR image must generally take into account both refraction and dispersion, 2) resolving targets at different depths in lossy soils requires perhaps unprecedented sidelobe attenuation, that for some soils may only be achievable with specialized window functions, 3) the impulse response of the soil itself places a practical limit on the usable bandwidth of the radar, and 4) dynamic ranges and sensitivities will need to be orders of magnitude greater than typical surface-imaging SARs, leading to significant impact on SAR parameters, for example compressing the usable range of pulse repetition frequencies (PRFs).

Synthetic Aperture Radar (SAR) is used to form images that are maps of radar reflectivity of some scene of interest, from range soundings taken over some spatial aperture. Additionally, the range soundings are typically synthesized from a sampled frequency aperture. Efficient processing of the collected data necessitates using efficient digital signal processing techniques such as vector multiplies and fast implementations of the Discrete Fourier Transform. Inherent in image formation algorithms that use these is a trade-off between the size of the scene that can be acceptably imaged, and the resolution with which the image can be made. These limits arise from migration errors and spatially variant phase errors, and different algorithms mitigate these to varying degrees. Two fairly successful algorithms for airborne SARs are Polar Format processing, and Overlapped Subaperture (OSA) processing. This report introduces and summarizes the analysis of generalized Tiered Subaperture (TSA) techniques that are a superset of both Polar Format processing and OSA processing. It is shown how tiers of subapertures in both azimuth and range can effectively mitigate both migration errors and spatially variant phase errors to allow virtually arbitrary scene sizes, even in a dynamic motion environment.

Synthetic Aperture Radar (SAR) from an airborne platform has been proposed for imaging targets beneath the earth`s surface. The propagation of the radar`s energy within the ground, however, is much different than in the earth`s atmosphere. The result is signal refraction, echo delay, propagation losses, dispersion, and volumetric scattering. These all combine to make SAR image formation from an airborne platform much more challenging than a surface imaging counterpart. This report treats the ground as a lossy dispersive half-space, and presents a model for the radar echo based on measurable parameters. The model is then used to explore various imaging schemes, and image properties. Dynamic range is discussed, as is the impact of loss on dynamic range. Modified window functions are proposed to mitigate effects of sidelobes of shallow targets overwhelming deeper targets.