AI RESEARCH
Hybrid Adaptive Kalman Filtering for Data-Efficient Joint Tracking and Classification
arXiv CS.LG
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ArXi:2606.02767v1 Announce Type: cross Kalman filtering performance is highly sensitive to model mismatch and noise covariance tuning. Learning-based approaches address these limitations but typically rely on supervised