Darko. Mušicki

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Target tracking algorithms have to operate in an environment of uncertain measurement origin, in the presence of possibly non-detected target measurements as well as clutter measurements from unwanted scatterers. Integral part of expressions for data association probabilities is the estimate of clutter density. A priori knowledge of the clutter density may(More)
The paper presents a new algorithm for tracking a manoeuvring target in a cluttered environment. The algorithm combines the Integrated Track Splitting (ITS) filter with the Interacting Multiple Model (IMM) algorithm. The ITS filter is a multiscan method for automatic target tracking in clutter. The multiscan foundation provides good tracking capabilities(More)
Multitarget tracking in clutter has two levels of complexity. One is caused by the exponential increase of number of measurement histories in time, and the other is caused by complexity in allocating measurements to tracks in each scan, which is also exponential in the number of tracks and the number of measurements involved. Linear multitarget tracking is(More)
Optimal signal detection for false track discrimination is determined by simulation using the integrated probabilistic data association (IPDA) algorithm. The IPDA algorithm is an efficient probabilistic data association algorithm with estimates of target existence probabilities that can be used to distinguish true and false tracks. The rate of confirmed(More)
In a cluttered environment, measurements originate not only from the objects being tracked, but also from spurious sources. The number of existing objects (targets) to be tracked is also unknown. The Multi-Hypotheses Tracking (MHT) filter is generally considered to be the “optimal” nscan target tracking filter in such a multi-target cluttered environment.(More)
Target tracking algorithms have to operate in an environment of uncertain measurement origin, in the presence of randomly detected target measurements as well as clutter measurements from unwanted random scatterers. Most data association target tracking algorithms incorporate a measure of clutter density. Quite often the clutter density is non-uniform,(More)
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