19 citations · 19 across the 4 of their papers we have counts for
5 papers
Physics-informed machine learning for sensor fault detection with flight test data
Brian M. de Silva, Jared Callaham, Jonathan Jonker +7
We develop data-driven algorithms to fully automate sensor fault detection in systems governed by underlying physics. The proposed machine learning method uses a time series of typ…
Efficient Robust Parameter Identification in Generalized Kalman Smoothing Models
Jonathan Jonker, Peng Zheng, Aleksandr Y. Aravkin
Dynamic inference problems in autoregressive (AR/ARMA/ARIMA), exponential smoothing, and navigation are often formulated and solved using state-space models (SSM), which allow a ra…
Preliminary Results in Current Profile Estimation and Doppler-aided Navigation for Autonomous Underwater Gliders
Jonathan Jonker, Andrey Shcherbina, Richard Krishfield +3
This paper describes the development and experimental results of navigation algorithms for an autonomous underwater glider (AUG) that uses an on-board acoustic Doppler current prof…
Robust Singular Smoothers For Tracking Using Low-Fidelity Data
Jonathan Jonker, Aleksandr Aravkin, James V. Burke +2
Tracking underwater autonomous platforms is often difficult because of noisy, biased, and discretized input data. Classic filters and smoothers based on standard assumptions of Gau…
Fast Robust Methods for Singular State-Space Models
Jonathan Jonker, Aleksandr Y. Aravkin, James V. Burke +2
State-space models are used in a wide range of time series analysis formulations. Kalman filtering and smoothing are work-horse algorithms in these settings. While classic algorith…