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Point-Source Location Using Hexagonal Detector Arrays
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1987
Year
RadarArray ProcessingHexagonal DetectorsMachine VisionEngineeringSensor ArrayAutomatic Target RecognitionCentroid AlgorithmComputer EngineeringNoiseDetection TechniqueInstrumentationRange ImagingComputational GeometryLocalizationSignal ProcessingClutter Equivalent TargetImage Sensor
For staring sensors, improved performance in the location of point sources can be achieved by use of an array of hexagonal detectors instead of the usual array of square or rectangular detectors. This improvement is demonstrated by calculating the accuracy of the centroid algorithm as a function of signal-to-noise ratio and blur spot size for both types of detector arrays. The probability density function for the centroid random variable is derived and is used to perform all noise analysis. The analysis indicates that the algorithm error is reduced by as much as a factor of 3, the sensitivity to noise is reduced by 17%, the computational load is decreased by 23%, and the data storage requirement is reduced by 22%. The clutter-induced noise, as measured by the clutter equivalent target, is essentially identical for square and hexagonal detectors of the same area.