@article{upm67070,
           month = {January},
          author = {Jaime L{\'o}pez-Araquistain L{\'o}pez and {\'A}ngel Joaqu{\'i}n Jarama Pellico and Juan Alberto Besada Portas and Gonzalo de Miguel Vela and Jos{\'e} Ram{\'o}n Casar Corredera},
            year = {2019},
       publisher = {Elsevier},
         journal = {Information Fusion},
           title = {A new approach to map-assisted Bayesian tracking filtering},
           pages = {79--95},
          volume = {45},
        abstract = {This paper presents a new non-linear filter designed to track targets following a road network, taking advantage of the road map information. The algorithm is based on a Bayesian Multiple Hypotheses modelling of movement process, postulating and evaluating different hypotheses on the segments being followed by the target after road junctions. Then, the along-road tracking is carried out, for each hypothesis, by a longitudinal IMM filter capable of tracking target movements along straight roads, circular segments, and generic curvilinear segments defined through B{\'e}zier curves. The algorithm also includes a lateral drift estimator, which tracks the lateral motion of the target with respect to road axis, to be able to estimate target piloting error and especially to track targets in wide roads. The paper completely describes the filter and associated measurement preprocessing procedures, and also includes a comparative evaluation of the proposed filter with other filtering methods in the literature.},
             url = {https://oa.upm.es/67070/},
        keywords = {MHT; Ground target tracking;IMM; Non-linear tracking; Context based tracking}
}