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A 3D solid model-aided object cueing method that matches phase angles of directional derivative vectors at image pixels to phase angles of vectors normal to projected model edges is described. It is intended for finding specific types of objects at arbitrary position and orientation in overhead images, independent of spatial resolution, obliqueness, acquisition conditions, and type of imaging sensor. It is shown that the phase similarity measure can be efficiently evaluated over all combinations of model position and orientation using the FFT. The highest degree of similarity over all model orientations is captured in a match surface of similarity values vs. model position. Unambiguous peaks in this surface are sorted in descending order of similarity value, and the small image thumbnails that contain them are presented to human analysts for inspection in sorted order.

This paper describes methods, algorithms, and software developed to select and represent landmarks from cartographic databases and to automatically determine the landmark position in GOES imagery. A simulation study was conducted to demonstrate that the landmark position can be measured with subpixel accuracy.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Space vehicle manual three-axis attitude control using vector reticle or control action display

A novel method for real time track assembly is presented which identifies new tracks, assigns measurementsto existing tracks, and eliminates false tracks. The method utilizes a sequence of two -dimensional frames ofbinary data from an infrared sensor where binary 1 in a picture element indicates target or noise abovethreshold and binary 0 is below threshold. Successive sets of two -dimensional frames are combined and then screened using a three -by -three pixel window. The track assembly is based upon neighborhood coding and "trackscoring" which uses the binary configuration in the three -by -three window to distinguish between target tracks and noise. The method makes use of successive levels of data processing, and in a cluttered environment(noise in 3% of the pixels) it may be necessary to use three or more levels to eliminate false tracks due to noise. A special coding technique is developed for the Floating Point System AP -120B off - the -shelf array processor to allow processing of 160,000 pixels per second independent of the number of targets. This paperexplains the coding scheme and the array processor mechanization.IntroductionRapid and accurate track assembly is a key aspect of many tracking problems. Representative applicationsinclude air defense against airplanes, ballistic missile defense against reentry vehicles, and ocean sur-veillance of ships. Important requirements for track assembly when there are multiple targets in a clutteredenvironment include initiating new tracks due to unknown targets, associating new measurements with the appro-priate track, and eliminating false tracks due to clutter.There are sophisticated algorithms for tracking of multiple targets, such as those of Reidl, which arecapable of calculating probabilities for various data association hypotheses. A comprehensive set of paperson multiple target tracking is included in the recent survey paper by Bar- Shalom2. The results of extensiveprevious work on automatic track initiation are summarized in the proceedings of a recent NATO Specialists