Abstract:

Based on the elements of the covariance matrix, this paper presents a multiple targets angle tracking algorithm, in which by updating the elements of the covariance matrix, a set of linear equations is derived through linear approximations. Angle difference can be obtained by solving these equations. Different from the subspace tracking algorithm, this method need not update the signal subspace; the angles estimated at different times are auto associated, so we can omit the process of data association. This method works well when the number of targets is greater than the number of sensors. At the same time, this algorithm can diminish the effect of noise. Simulation results show this algorithm has high tracking performance.

Key words: multiple targets tracking, angle tracking, covariance matrix, subspace tracking