Advance Tracking Algorithms to Meet Modern Threats - MP 143-14

ABSTRACT:This project addresses the development and benchmarking of advanced algorithms to track modern supermaneuverable targets. The objective is to develop, demonstrate, and validate an assessment tool that provides future radar architecture design performance requirements to the acquisition community for tracking algorithms that will succeed against these modern threats. In Phase I, we enumerated and tested a wide set of tracking approaches, from traditional, fielded Kalman filter algorithms including the extended Kalman filter and unscented Kalman filter, to state-of-the-art nonlinear filtering algorithms, such as the resampling particle filter and homotopy particle filter. We benchmarked these algorithms in simulation against a set of supermaneuvering targets using simulated radar measurements. The effort showed the failure mechanisms of standard Kalman-based approaches and brought to light the significant improvements available from modern, cutting edge nonlinear filtering algorithms. In Phase II, we propose to extend and refine the trackers developed in Phase I, test the methods with high-fidelity flight data, and use these results to produce recommendations for future systems.BENEFIT:The anticipated results from the project are: (i) an analysis of modern nonlinear filtering algorithms on modern supermaneuverable threats which shows military-relevant performance improvements over conventional tracking algorithms, to include: increased detection range and improved target localization, (ii) Matlab-level prototyping of these new tracking algorithms that are robust and computationally efficient, and (iii) a method of using these tools to predict in-theatre performance and recommend radar design and settings to optimize the performance. The immediate benefit of the Phase II tracking capability is to provide the Air Force with a quantitative assessment of the performance improvement possible when using modern tracking algorithms. Furthermore, the analysis will provide methods for determining how to design future systems to maximize in-theatre performance by selecting radar parameters and surveillance platform trajectories.