A concise summary of techniques for multiple target tracking is provided and their main
characterics assessed qualitatively. The techniques have been catergorised into more than …

Kalman filter, particle filter, IMM, PDA, ITS, random sets... The number of useful object-
tracking methods is exploding. But how are they related? How do they help track everything …

A common problem in multi-target tracking is to approximate a Gaussian mixture by one
containing fewer components; similar problems can arise in integrated navigation. A …

This paper considers recursive tracking of one mobile emitter using a sequence of time
difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurement pairs …

In Gilholm et al.'s extended target model, the number of measurements generated by a
target is Poisson distributed with measurement rate γ. Practical use of this extended target …

Human drivers are endowed with an inborn ability to put themselves in the position of other
drivers and reason about their behavior and intended actions. State-of-the-art driving …

The evolving complexity of distribution networks with higher levels of uncertainties is a new
challenge faced by system operators. This paper introduces the use of Gaussian mixtures …

This paper presents a new prediction update for extended targets whose extensions are
modeled as random matrices. The prediction is based on several minimizations of the …

This study proposes the use of Gaussian mixture models to represent non-Gaussian
correlated input variables, such as wind power output or aggregated load demands in the …

This paper develops a probabilistic anticipation algorithm for dynamic objects observed by
an autonomous robot in an urban environment. Predictive Gaussian mixture models are …