60 citations · 128 across the 11 of their papers we have counts for
11 papers
Learning Position From Vehicle Vibration Using an Inertial Measurement Unit
Barak Or, Nimrod Segol, Areej Eweida +1
This paper presents a novel approach to vehicle positioning that operates without reliance on the global navigation satellite system (GNSS). Traditional GNSS approaches are vulnera…
Surface Recognition for e-Scooter Using Smartphone IMU Sensor
Areej Eweida, Nimord Segol, Maxim Freydin +2
In recent years, as the use of micromobility gained popularity, technological challenges connected to e-scooters became increasingly important. This paper focuses on road surface r…
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…
Length Learning for Planar Euclidean Curves
Barak Or, Liam Hazan
In this work, we used deep neural networks (DNNs) to solve a fundamental problem in differential geometry. One can find many closed-form expressions for calculating curvature, leng…
Optimal Disturbance Attenuation Approach with Measurement Feedback to Missile Guidance
Barak Or, Joseph Z. Ben-Asher, Isaac Yaesh
Pursuit-evasion differential games using the Disturbance Attenuation approach are revisited. Under this approach, the pursuer actions are considered to be control actions, whereas…