Weak in the NEES?: Auto-tuning Kalman Filters with Bayesian Optimization

Zhaozhong Chen
Zhaozhong Chen
Simon Julier
Simon Julier

FUSION, pp. 1072-1079, 2018.

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Abstract:

Kalman filters are routinely used for many data fusion applications including navigation, tracking, and simultaneous localization and mapping problems. However, significant time and effort is frequently required to tune various Kalman filter model parameters, e.g. process noise covariance, pre-whitening filter models for non-white noise, ...More

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