GOATS Image Projection Component
- Created: Friday, 01 April 2011
When doing mission analysis and design of an imaging system in orbit around the Earth, answering the fundamental question of imaging performance requires an understanding of the image products that will be produced by the imaging system. At the highest level, this understanding can be gained by a first-principles analysis of the geometric image projections involved in image capture from space. Going back to first principles allows for requirements to be quickly analyzed and the fundamental specifications of the imaging systems to be tweaked and traded quickly to aid in rapid mission design and analysis. The problem then becomes encapsulating these first-principle algorithms in a set of easy-to-use and modular functions to be used in coordination with other mission design tools.
GOATS software represents a series of MATLAB functions to provide for geometric image projections. Unique features of the software include function modularity, a standard MATLAB interface, easy-to-understand first-principles-based analysis, and the ability to perform geometric image projections of framing type imaging systems. The software modules are created for maximum analysis utility, and can all be used independently for many varied analysis tasks, or used in conjunction with other orbit analysis tools.
By basing the tools purely on first principles and utilizing a high degree of generalization, the same set of tools can be applied to imaging systems not in orbit (i.e., helicopters, high-altitude planes, etc.). The image projection tools begin with a simple description of the imaging system to be analyzed. This description is based on the highest level of imaging parameters (system F-number, pixel pitch, aperture size, etc.), which are among the first parameters settled upon when contemplating a new system. The tools are structured this way to allow for early analysis of the highest level requirements and the performance of rather detailed trade studies to best settle upon these high-level requirements early on.
Using these high-level parameters and the imaging geometry of the proposed system, one can geometrically project the imaging system onto the ground and determine many of the features of the collected imagery. These features include ground sample distances, actual image size and geolocation, image stretching and warping, etc. With these features calculated, there is a direct link between imaging system hardware parameters and performance requirements. Additionally, the same tools can be used to do some level of image processing. Existing image data sets can be processed and re-projected to simulate what they would look like had they been taken with an imaging system with different parameters. The functions provide a robust toolset to quickly answer several types of imaging questions that typically arise when considering missions around framing imaging systems.