4 May 2009 Adaptive processing for enhanced target acquisition
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Abstract
Conventional air-to-ground target acquisition processes treat the image stream in isolation from external data sources. This ignores information that may be available through modern mission management systems which could be fused into the detection process in order to provide enhanced performance. By way of an example relating to target detection, this paper explores the use of a-priori knowledge and other sensor information in an adaptive architecture with the aim of enhancing performance in decision making. The approach taken here is to use knowledge of target size, terrain elevation, sensor geometry, solar geometry and atmospheric conditions to characterise the expected spatial and radiometric characteristics of a target in terms of probability density functions. An important consideration in the construction of the target probability density functions are the known errors in the a-priori knowledge. Potential targets are identified in the imagery and their spatial and expected radiometric characteristics are used to compute the target likelihood. The adaptive architecture is evaluated alongside a conventional non-adaptive algorithm using synthetic imagery representative of an air-to-ground target acquisition scenario. Lastly, future enhancements to the adaptive scheme are discussed as well as strategies for managing poor quality or absent a-priori information.
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Scott F. Page, Scott F. Page, Moira I. Smith, Moira I. Smith, Duncan Hickman, Duncan Hickman, Mark Bernhardt, Mark Bernhardt, William Oxford, William Oxford, Norman Watson, Norman Watson, F. Beath, F. Beath, } "Adaptive processing for enhanced target acquisition", Proc. SPIE 7338, Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIII, 733807 (4 May 2009); doi: 10.1117/12.818459; https://doi.org/10.1117/12.818459
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