Performance evaluation of unscented Kalman Filter using multi-core processors environment

The Unscented Kalman Filter (UKF) is widely used to solve nonlinear systems, like submarine tracking, aircraft surveillance, autonomous robotics and mobile systems. One of the typical problems solved using UKF is Bearing-Only Target Motion Analysis (BOTMA) for manoeuvring and non manoeuvring targets. This paper proposes a methodology for parallel execution of UKF with an aim to enhance its performance in terms of computational throughput. Parallel algorithm and its execution of UKF for BOTMA will use multi-core processor environment. The study concentrate on identifying the phases of UKF enabled BOTMA that can be parallelized to execute on the hardware underneath to enhance the response time. The performance is observed and results are verified.