60 citations · 128 across the 11 of their papers we have counts for
7 papers · 1 filter
ProNet: Adaptive Process Noise Estimation for INS/DVL Fusion
Barak Or, Itzik Klein
Inertial and Doppler velocity log sensors are commonly used to provide the navigation solution for autonomous underwater vehicles (AUV). To this end, a nonlinear filter is adopted…
Deep Learning for Inertial Sensor Alignment
Maxim Freydin, Niv Sfaradi, Nimrod Segol +2
Accurate alignment of a fixed mobile device equipped with inertial sensors inside a moving vehicle is important for navigation, activity recognition, and other applications. Accura…
A Hybrid Adaptive Velocity Aided Navigation Filter with Application to INS/DVL Fusion
Barak Or, Itzik Klein
Autonomous underwater vehicles (AUV) are commonly used in many underwater applications. Usually, inertial sensors and Doppler velocity log readings are used in a nonlinear filter t…
A Hybrid Model and Learning-Based Adaptive Navigation Filter
Barak Or, Itzik Klein
The fusion between an inertial navigation system and global navigation satellite systems is regularly used in many platforms such as drones, land vehicles, and marine vessels. The…
Adaptive Step Size Learning with Applications to Velocity Aided Inertial Navigation System
Barak Or, Itzik Klein
Autonomous underwater vehicles (AUV) are commonly used in many underwater applications. Recently, the usage of multi-rotor unmanned autonomous vehicles (UAV) for marine application…
Learning Vehicle Trajectory Uncertainty
Barak Or, Itzik Klein
A novel approach for vehicle tracking using a hybrid adaptive Kalman filter is proposed. The filter utilizes recurrent neural networks to learn the vehicle's geometrical and kinema…
Learning Car Speed Using Inertial Sensors for Dead Reckoning Navigation
Maxim Freydin, Barak Or
A deep neural network (DNN) is trained to estimate the speed of a car driving in an urban area using as input a stream of measurements from a low-cost six-axis inertial measurement…