Optimal Sensing Precision in Ensemble and Unscented Kalman Filtering

@article{Das2020OptimalSP,
  title={Optimal Sensing Precision in Ensemble and Unscented Kalman Filtering},
  author={Niladri Das and R. Bhattacharya},
  journal={arXiv: Signal Processing},
  year={2020}
}
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Sparse Sensing and Optimal Precision: Robust H∞ Optimal Observer Design with Model Uncertainty
We present a framework which incorporates three aspects of the estimation problem, namely, sparse sensor configuration, optimal precision, and robustness in the presence of model uncertainty. The…
Sensor Selection and Optimal Precision in $\mathcal{H}_2/\mathcal{H}_{\infty}$ Estimation Framework: Theory and Algorithms
TLDR
The proposed integrated framework formulates the precision minimization as a convex optimization problem subject to linear matrix inequalities, and it is solved using an algorithm based on the alternating direction method of multipliers (ADMM).
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TLDR
A framework is presented which incorporates three aspects of the estimation problem, namely, sparse sensor configuration, optimal precision, and robustness in the presence of model uncertainty, which is posed as a convex optimization problem subject to linear matrix inequalities.
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TLDR
This paper simultaneously determines the optimal sensor precision and the observer gain, which achieves the specified accuracy in the state estimates, which is applied to the linearized longitudinal model of an F-16 aircraft.

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