Efficient Area Coverage for Space-based and Aerial Imaging Sensors

R.S. Holt, J.S. Nikom, P.B. Jones, and G.R. Condon (USA)


Planning Systems, Intelligent Decision Support Systems, Dynamic Optimization, Area Coverage Algorithms


Space-based or aerial imaging sensors are often tasked with imaging areas larger than the image footprint. To accom plish this, the sensors take a series of images, whose com bined footprints cover the entire area, and stitch them to gether during post-processing. Due to time-sensitivity of coverage requests, it is highly desirable to minimize the number of images required to cover the area and the time spent creating the collection plan. Optimal selection of the aimpoints is constrained by platform trajectory. The sen sor is assumed to be steerable, but staged on a vehicle with a fixed flight path. This trajectory determines the orienta tion of each image in the series. Therefore, the goal is to choose a series of image aimpoints, given a sequence of image orientations. Currently, human operators choose the aimpoints due to the complexity of the selection process. This represents a system inefficiency, particularly problem atic in time-sensitive situations. This paper formulates the efficient area coverage problem, in terms of out-coverage, multi-coverage, and gaps. Three approaches to solving the coverage problem when the sensor footprint is rotationally constrained are presented. Metrics are proposed that compare the cover age efficiency of each approach. Simulation results demon strate the impact of gaps created during the coverage pro cess.

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