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In theory, a good joint particle filter allows to approximate the exact Bayesian filter solution arbitrarily well. This has motivated a strong and successful development of single target tracking particle filters. Nevertheless, for tracking multiple closely spaced maneuvering targets, there is evidence in literature which seems to contradict the theoretical(More)
The beta, gamma-crystallins form a class of homologous proteins in the eye lens. Each gamma-crystallin comprises four topologically equivalent, Greek key motifs; pairs of motifs are organized around a local dyad to give domains and two similar domains are in turn related by a further local dyad. Sequence comparisons and model building predicted that(More)
In this paper the so called mixed labeling problem inherent, or at least thought to be inherent to a joint state multi target particle filter implementation is treated. The mixed labeling problem would be prohibitive for track extraction from a joint state multi target particle filter. It is shown and proven using the theory of Markov chains, that the mixed(More)
In this paper we address the problem of tracking multiple targets based on raw measurements by means of Particle filtering. This strategy leads to a high computational complexity as the number of targets increases, so that an efficient implementation of the tracker is necessary. We propose a new multitarget Particle Filter (PF) that solves such challenging(More)
This paper is concerned with the application of target tracking in a network of sensors that provide binary output. The binary sensor network tracking problem is formulated in a sequential Bayesian estimation framework and is readily solved by means of a particle filter. We will perform sensor selection by means of a newly proposed scheme. This proposed(More)
We consider the problem of scheduling an agile sensor for performing optimal search for a target. A probability density function is created for representing our knowledge about where the target might be and it is utilized by the proposed sensor management criteria for finding optimal search strategies. The proposed criteria are: an information-driven(More)
— For certain types of sensor-target configurations a point target model or approach is not suitable and the physical extent of the target has to be accounted for in the processing. An extended target track before detect algorithm is presented and the performance is compared to an algorithm based on the point target assumption. Simulations illustrate the(More)
In this article we introduce a new Gaussian proposal distribution to be used in conjunction with the sequential Monte Carlo (SMC) method for solving non-linear filtering problem. This proposal incorporates all the information about the to be estimated current state from both the available state and observation processes. This makes it more effective than(More)