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Electro-optical sensors, when used to track space objects, are often used to produce detections for some orbit determination scheme. Instead, this paper proposes a series of methods to use electro-optical images directly in orbit determination. This work uses the SNR optimal image filter, called a matched filter, to search for partially known space objects. By defining a metric for measuring matched filter template similarity, a bank of matched filters is efficiently defined by partitioning the prior knowledge set. Once partitioned sets are known, the matched filter bank can be localized to regions of the sky. A method for hypothesis testing the result of a matched filter for a space object is developed. Finally, a framework for orbit determination based on the matched filter result is developed. Simulation shows that the analytic results enable a better framework for implementing matched filters for low SNR object detection.

A statistical methodology for the global and local analysis of star tracker image content is presented that is based on the A-Contrario framework. A level set analysis using this methodology effectively weights signals with a confidence interval based on the information content. Globally this analysis can represent the non-planar noise floor associated with the sky background. Locally, this analysis can automatically define the annulus that represents the partial pixels associated with the boundary between signal and noise. The performance of centroiding with information theoretic weighting is evaluated compared to traditional thresholding methods for simulated and real star tracker images.

This paper presents an automatic RSO detection and tracking scheme operating at the optical sensor system level. The software presented is a pipeline for processing ground or space-based imagery built from several subalgorithms which processes raw or calibrated imagery, detects and discriminates non-star objects, and associates observations over time. An orbit determination routine uses an admissible region to start off an unscented particle filter. This preliminary orbit estimate allows prediction of the appearance of the object in the next frame. A matched filter uses this imagery to provide feedback to the initial detection and tracking process.