In this paper, we apply a statistically rigorous track-before-detect (TBD) method, the Bernoulli particle filter, to actual imagery of resident space objects (RSOs). Robust methods in this realm will lead to better space domain awareness (SDA) while reducing the cost of sensors and optics. We focus on estimating sensor-level kinematics of RSOs for low signal-to-noise ratio (SNR) short-arc obser...

Rich clusters of galaxies are interesting as the most massive gravitationally bound objects in the Universe. Although containing only about 1 % of all galaxies, they provide an environment for the formation and evolution of galaxies that is unique, and in many regards, the population of galaxies seen today in rich clusters di ers from that found in the eld. We therefore propose to complement th...

We present a computationally efficient track-before-detect algorithm that achieves more than 50% true detection at 0.000001 false alarm rate for pixel sized unknown number of multiple targets when the signal-to-noise ratio is less than 7dB. Without making any assumptions on the distribution functions, we select a small number of cells, so called as needles, and generate motion hypotheses using ...