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This paper presents a Gaussian tracking algorithm with direction-of-arrival (DOA) measurements modelled via the Kent distribution. The key aspect of the algorithm is that the Kent distribution directly models the specific characteristics of DOA measurements in the 3-D space, and can account for different uncertainties in azimuth and elevation, which the von Mises-Fisher distribution cannot. At each update step, the algorithm performs iterated statistical linear regressions. We provide two implementations of the algorithms, one based on sigma-points and the other on analytical linearisation. The effectiveness of the approach is evaluated via numerical simulations. [ABSTRACT FROM AUTHOR]