Track to track fusion: PACsim data set

This paper presents a track to track fusion technique motivated by recent work in sparse subspace clustering (SSC). This technique was first tested on a synthetic dataset and then on the Passive-Active Contact Simulator (PACsim) data. The PACsim dataset is a multistatic simulation designed to approximate real-life data. In this paper, we apply the subspace clustering technique to the track to track fusion problem. Results demonstrate that this technique improves overall tracking performance. Specifically, we demonstrate that the SSC algorithm is robust to noisy data and perfectly clusters track fragments from the PACsim dataset.