10 papers · 1 filter
Bayesian Learning-Enhanced Navigation with Deep Smoothing for Inertial-Aided Navigation
Nadav Cohen, Itzik Klein
Accurate post-processing navigation is essential for applications such as survey and mapping, where the full measurement history can be exploited to refine past state estimates. Fi…
Dual-Branch INS/GNSS Fusion with Inequality and Equality Constraints
Mor Levenhar, Itzik Klein
Reliable vehicle navigation in urban environments remains a challenging problem due to frequent satellite signal blockages caused by tall buildings and complex infrastructure. Whil…
ResAlignNet: A Data-Driven Approach for INS/DVL Alignment
Guy Damari, Itzik Klein
Autonomous underwater vehicles rely on precise navigation systems that combine the inertial navigation system and the Doppler velocity log for successful missions in challenging en…
Adaptive Neural Unscented Kalman Filter
Amit Levy, Itzik Klein
The unscented Kalman filter is an algorithm capable of handling nonlinear scenarios. Uncertainty in process noise covariance may decrease the filter estimation performance or even…
Transformer-Based Robust Underwater Inertial Navigation in Prolonged Doppler Velocity Log Outages
Zeev Yampolsky, Nadav Cohen, Itzik Klein
Autonomous underwater vehicles (AUV) have a wide variety of applications in the marine domain, including exploration, surveying, and mapping. Their navigation systems rely heavily…
Enhancing Underwater Navigation through Cross-Correlation-Aware Deep INS/DVL Fusion
Nadav Cohen, Itzik Klein
The accurate navigation of autonomous underwater vehicles critically depends on the precision of Doppler velocity log (DVL) velocity measurements. Recent advancements in deep learn…