Variational Bayes for robust radar single object tracking. (arXiv:2209.14397v1 [eess.SP])

We address object tracking by radar and the robustness of the current
state-of-the-art methods to process outliers. The standard tracking algorithms
extract detections from radar image space to use it in the filtering stage.
Filtering is performed by a Kalman filter, which assumes Gaussian distributed
noise. However, this assumption does not account for large modeling errors and
results in poor tracking performance during abrupt motions. We take the
Gaussian Sum Filter (single-object variant of the Multi Hypothesis Tracker) as
our …

arxiv bayes radar tracking