**5. Conclusions**

In this paper, we detailed the implementation of a new tracker based on GLMB filter and a modified multi-scan estimator. In addition to lowering the localization error by performing RTS smoother on each individual estimated trajectory, the proposed tracker can also reduce cardinality errors by deleting the short-term tracks via track management and by completely eliminating track fragmentation. The computation time is shown to contribute to less than 0.5% of the total tracking time, although a fixed delay time is needed before the tracker can produce the estimate. Therefore, in applications when real-time updates are not required, the proposed tracker can be used to improve the tracking results given negligible extra computation time. However, as the smoothing results strongly depend on the quality of the estimates obtained from the forward filtering step, if the filtered estimate experiences strong distortion, the performance of the proposed tracker degrades significantly.

**Author Contributions:** Methodology, T.T.D.N. and D.Y.K.; visualization, T.T.D.N.; writing—original draft, T.T.D.N.; writing—review and editing, T.T.D.N. and D.Y.K.

**Funding:** This work was funded by the Australian Research Council grant number DP160104662.

**Acknowledgments:** The authors acknowledge the administrative and technical support from Curtin University and RMIT University.

**Conflicts of Interest:** The authors declare no conflict of interest.
