SkyRadar introduces an advanced object tracking methodology featuring both the linear Kalman filter and the interacting multiple model (iMM) filter. While the linear Kalman filter primarily focuses on longitudinal object positioning, the iMM algorithm expands capabilities to include lateral positioning, enhancing tracking robustness.
iMM - Going Further than Kalman
Apart of the linear Kalman filter, SkyRadar also presents a development concept of the interacting multiple model (iMM) filter for object tracking. The main difference between the linear Kalman filter, is the extension of object prediction and correction of the object positions also on the lateral positions.
The linear Kalman filter is mainly taking the longitudinal object positions as track updates. In the iMM algorithm, also the track updates on the lateral positions are considered. In this way more robustness on object tracking is added.
As main future work on this feature, we will add also the extended Kalman filter for non-linear environments, alpha-beta tracker, and a combination of all these tracking filter based on deep learning concepts.
In the following video, the difference between linear Kalman filter and iMMTracking for the same scene is shown in PPI scope. As expected, the object movement tracks are better and clearer detected/estimated.
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