98 citations · 349 across the 25 of their papers we have counts for
6 papers · 1 filter
Outlier-Insensitive Kalman Filtering Using NUV Priors
Shunit Truzman, Guy Revach, Nir Shlezinger +1
The Kalman filter (KF) is a widely-used algorithm for tracking the latent state of a dynamical system from noisy observations. For systems that are well-described by linear Gaussia…
A Learning-based approach for bias elimination in low cost gyroscopes
Daniel Engelsman, Itzik Klein
Modern sensors play a pivotal role in many operating platforms, as they manage to track the platform dynamics at a relatively low manufacturing costs. Their widespread use can be f…
A Unified Filter for Fusion of Multiple Inertial Measurement Units
Yaakov Libero, Itzik Klein
Navigation plays a vital role in the ability of autonomous surface and underwater platforms to complete their tasks. Most navigation systems apply a fusion between inertial sensors…
Adaptive Attitude Estimation Using a Hybrid Model-Learning Approach
Eran Vertzberger, Itzik Klein
Attitude determination using the smartphone's inertial sensors poses a major challenge due to the sensor low-performance grade and variate nature of the walking pedestrian. In this…
Data-Driven Denoising of Stationary Accelerometer Signals
Daniel Engelsman, Itzik Klein
Modern navigation solutions are largely dependent on the performances of the standalone inertial sensors, especially at times when no external sources are available. During these o…
Uncertainty in Data-Driven Kalman Filtering for Partially Known State-Space Models
Itzik Klein, Guy Revach, Nir Shlezinger +3
Providing a metric of uncertainty alongside a state estimate is often crucial when tracking a dynamical system. Classic state estimators, such as the Kalman filter (KF), provide a…