Tracking an entity for a long duration allows the gathering of intelligence on a target. While the system comprises a collection of different elements (e.g., tracking, sensor tasking, etc.), the ability to track objects continuously over long periods rests on feature measurements that are collected "on-the-fly" and used to uniquely characterize the target of interest. These features are then used to track the target over extended periods of time and through situations in which the targets can be confused with other moving objects. The collecting of features helps support tracking the target when it becomes kinematically ambiguous with other objects. If the system is unable to avoid ambiguities between the target of interest and other moving objects, features collected post-ambiguity can be used to resolve the ambiguities. A collection of algorithms that model and attempt to resolve any association ambiguity between a target of interest and the tracks in the fusion and tracking database is required to accomplish this task. This module is referred to as the Tracked Object Manager (TOM) and forms the backbone of a system for the continuous tracking of high-value targets. The TOM utilizes the collected features to help correct track switches and, if appropriate, stitch tracks together to maintain continuous track on high-value targets. The algorithms are being incorporated into and evaluated using Toyon's Intelligence, Surveillance and Reconnaissance (ISR) simulation environment named SLAMEM.
We evaluate VCSEL interconnects for next-generation High Productivity Computers in which hundreds of terabits of bandwidth are envisioned. We present results for VCSEL based links operating PAM-4 signaling using a commercial 0.13μm CMOS technology. We perform a complete link analysis of the Bit Error Rate, Q factor, random and deterministic jitter by measuring waterfall curves versus margins in time and amplitude. We demonstrate that VCSEL based PAM-4 can match or even improve performance over binary signaling under conditions of bandwidth limited 100meter multi-mode optical link at 5Gbps. We present the first sensitivity measurements for optical PAM-4 and compare it with binary signaling. An empirical relationship for VCSEL scaling versus bit rate and aperture is presented in order to explore reliability of VCSEL-based links. Reliability is found to degrade with aperture with a fourth order power law dependence.
We have developed and implemented an approach to performing feature-aided tracking (FAT) of ground vehicles using ground moving target indicator (GMTI) radar measurements. The feature information comes in the form of high-range resolution (HRR) profiles when the GMTI radar is operating in the HRR mode. We use a Bayesian approach where we compute a feature association likelihood that is combined with a kinematic association likelihood. The kinematic association likelihood is found using an IMM filter that has onroad, offroad, and stopped motion models. The feature association likelihood is computed by comparing new measurements to a database of measurements that are collected and stored on each object in track. The database consists of features that have been collected prior to the initiation of the track as well as new measurements that were used to update the track. We have implemented and tested our algorithm using the SLAMEM simulation.
We describe an algorithm for class-independent automated target recognition (ATR) and association using range-Doppler images of moving targets and SAR images of stationary targets. This algorithm can be used both for target identification (by comparison against a pre-existing database of measurements of all potential targets) and target association (not requiring a pre-existing database). The algorithm computes a one-dimensional signature for each received range-Doppler image; these signatures are stored in a database for comparison against other detections. The signatures used in our algorithm are range profiles, generated from the clutter-suppressed, filtered image by incoherently integrating the image energy across a number of Doppler bins centered on the target. The result is then normalized, to remove information about the overall cross-section from the profile, and range-aligned with other collected profiles by matching the profile centroids. Statistical models of the profiles are created as the targets are tracked, and newly-created profiles are compared against the existing models by computing the likelihood of the new profile given a particular model.