Award

Objects tracked by optical sensors in ascent phase and midcourse are frequently obscured on the focal plane by closely spaced objects, countermeasures and debris (or clutter) that affect the performance of discrimination and tracking algorithms. Problems include missed detections, false alarms, corrupted signatures and masking of pixels that contain lethal objects. The objective of the proposed effort is to develop a focal plane clutter identification and mitigation algorithm suite that can execute on-board the ABIR, PTSS and SM-3 platforms. The suite uses multiple band focal plane data to identify regions of interest that contain clutter via characterization of the surface material properties found on the focal plane. Once identified, regions are processed by generating image maps that are manipulated to reject"hot"clutter thereby enhancing signatures of relatively"cool"targets of interest. The suite then leverages the CCIR3.1 closely spaced object (CSO) algorithm to provide target detections. This phase II effort will focus on maturation, testing and integration of the algorithm suite into the SM-3 Block IIA testbed, laying the groundwork for a successful phase III transition.