Track-before-detect filter for sensors with point spread function using thresholded measurements

This paper presents a joint target detection and tracking filter for sensors with point spread function using thresh-olded measurements. State-of-the-art solution of this problem is implemented using unthresholded measurements. However, it takes a large amount of memory and bandwidth to store and transport the raw data. We use the thresholded measurements (indexes of the bins that have past the low threshold detection) to address the joint detection and tracking problem. The conceptual solution of the filter in the Bayesian framework is derived. A particle filter implementation of the proposed filter is proposed. Numerical examples shows that the proposed filter performs good at target detection and tracking compared with the state-of-the-art approaches. Meanwhile, the computational complexity of the proposed filter is comparatively small.