On a Fast CPD-Tensor Operator for Target Tracking

In this paper, a novel tensor operator is introduced that directly solves the prediction step of the Bayes recursion for multi-dimensional discretized probability densities in Canonical Polyadic Decomposition form. The proposed operator combines computational efficiency with the possibility for non-linear and non-Gaussian scenarios. Based on the Continuous White Noise Velocity model, it enables a broad range of application in target tracking.