Correlated uncertain angular quantities can be modeled using the bivariate wrapped normal distribution. In this paper, we focus on the problem of estimating the distribution's parameters from a given set of samples. For this purpose, we propose several new parameter estimation methods and compare them to estimation techniques found in literature. All methods are thoroughly evaluated in simulations. One of the novel methods is shown to combine the advantages of maximum likelihood estimation and moment-based methods, thus outperforming current state-of-the-art techniques.
['Gerhard Kurz', 'Uwe D. Hanebeck']
Parameter estimation for the bivariate wrapped normal distribution