Improving space domain awareness through unequal-cost multiple hypothesis testing in the space surveillance telescope

This paper investigates algorithms to improve the detection of space objects with the space surveillance telescope (SST) system. These space objects include natural objects such as asteroids and artificial satellites in Earth orbit. Using a proposed multiple hypothesis test (MHT), the detection performance is compared to the currently used algorithm as well as a matched filter and an equal-cost MHT algorithm. To compare these algorithms, a data set collected by the SST of a geosynchronous Earth orbit satellite, ANIK-F1 entering the Earth's eclipse, is utilized. It is found that an unequal-cost MHT gives increased performance over a point detector, a matched filter, and equal-cost MHT over a large range of potential intensities. Results are presented as probability of detection and receiver operating characteristic curves. In addition, the performance of the algorithm as a function of number of hypotheses used is investigated.