Autonomous Tracking and State Estimation With Generalized Group Lasso.

@article{Gao2021AutonomousTA,
  title={Autonomous Tracking and State Estimation With Generalized Group Lasso.},
  author={Rui Gao and Simo Sarkka and Rub'en Claveria-Vega and Simon J. Godsill},
  journal={IEEE transactions on cybernetics},
  year={2021},
  volume={PP}
}
We address the problem of autonomous tracking and state estimation for marine vessels, autonomous vehicles, and other dynamic signals under a (structured) sparsity assumption. The aim is to improve the tracking and estimation accuracy with respect to the classical Bayesian filters and smoothers. We formulate the estimation problem as a dynamic generalized group Lasso problem and develop a class of smoothing-and-splitting methods to solve it. The Levenberg-Marquardt iterated extended Kalman… 
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