Regarding the detection and measurement of resolved significantly blurred targets on an optical sensor’s Focal Plane Array (FPA), a study of the relationship between centroiding precision and Signal to Noise Ratio (SNR) is conducted for two types of centroiding algorithms. Due to hardware constraints on the Orion vehicle, alignment targets are near the docking camera causing them to be severely out of focus and in poor lighting conditions resulting in predicted low SNR. The alignment targets are used to estimate the camera’s alignment relative to hardware on the Orion vehicle post launch to effectively use the camera as a relative navigation sensor. Precisely measuring the location of the alignment target’s centroid on the FPA is critical to accurately estimating the camera’s alignment. For the study, targets are assumed to have Gaussian reflectance function and be centered in a region of interest on the FPA. Two Point Spread Functions (PSF) cases are considered. The first case assumed the optical system is focused and the PSF is much smaller than the target signal. The second case uses the sensor’s predicted optical PSF at the expected range of the alignment target. White Gaussian noise is added to the simulated region of interest proportional to the predicted sensor readout noise. A definition of Matched Filter (MF) SNR is presented. Monte Carlo simulations are run over a range of MF SNR values to obtain the centroid precision for the studied algorithms and PSFs. The algorithms studied include a Matched Filter Peak Detection (MFPD) algorithm and a standard Centroiding algorithm. Comparing the algorithm performance, the MFPD is found to be optimal. An equation is fit to the MFPD algorithm performance thus deriving an expression for the expected optimal centroiding precision given a target SNR.


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    Title :

    CENTROIDING PRECISION OF RESOLVED BLURRED TARGET IMAGES


    Contributors:


    Publication date :

    2024-01-01


    Size :

    13 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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