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20182023
most citedInertial Navigation Meets Deep Learning: A Survey of Current Trends and Future Directions

98 citations · 349 across the 25 of their papers we have counts for

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Showing 2022 · eess.SPShow all

5 papers · 2 filters

eess.SP2022

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…

eess.SP2022★ 7 cited

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…

eess.SP2022★ 15 cited

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…

eess.SP2022★ 10 cited

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…

eess.SP2022★ 28 cited

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…