Track-Before-Detect with Kullback-Leibler Divergence Sampling

Track-before-detect (TBD) is a joint detection and tracking approach that takes advantage of a targets motion over time. For most TBD algorithms, the computationally load is very demanding and efficient implementations need to be developed. An algorithm recently proposed for maritime radar is the Bernoulli TBD particle filter with the number of particles determined heuristically. However, this is not a good approach in the maritime domain due to time and range-varying characteristics of sea clutter. In this paper, an efficient TBD algorithm is developed using Kullback Leibler divergence (KLD) sampling to achieve computational efficiency and adaptive selection of the number of particles. Monte Carlo simulations demonstrate that the adaptive selection of particle number results in excellent detection and tracking results.