Khashayar Hashim DeepUKF-VIN Adaptively-tuned Deep UKF for Visual-Inertial Navigation IMU-Vision-Net

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This work is par of the following journal paper:
[J]. K. Ghanizadegan and H. A. Hashim, “DeepUKF-VIN: Adaptively-tuned Deep Unscented Kalman Filter for 3D Visual-Inertial Navigation based on IMU-Vision-Net,” Expert Systems With Applications (ESA), Vol. PP, No. PP, pp. 1-13, 2025.

The authors are with the Department of Mechanical and Aerospace Engineering at Carleton University, Ottawa, Ontario, Canada.

This work was supported in part by National Sciences and Engineering
Research Council of Canada (NSERC), under the grants RGPIN-2022-04937.

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You may also read:
[Ref1] H. A. Hashim, M. Abouheaf, and M. A. Abido, "Geometric Stochastic Filter with Guaranteed Performance for Autonomous Navigation based on IMU and Feature Sensor Fusion", Control Engineering Practice, Elsevier, 2021, published.
URL: https://doi.org/10.1016/j.conengprac....
PDF arXiv: https://arxiv.org/abs/2108.11866

[Ref2] H. A. Hashim, "GPS-denied Navigation: Attitude, Position, Linear Velocity, and Gravity Estimation with Nonlinear Stochastic Observer," In Proc. of the 2021 IEEE American Control Conference (ACC'21), New Orleans, Louisiana, USA, pp. 1146-1151, 2021.
URL: https://doi.org/10.23919/ACC50511.202...
PDF arXiv: https://arxiv.org/abs/2104.09920

[Ref3] K. Ghanizadegan and H. A. Hashim, “Quaternion-based Unscented Kalman Filter for 6-DoF Vision-based Inertial Navigation in GPS-denied Regions,” IEEE Transactions on Instrumentation and Measurement (IEEE TIM), Vol. 74, No. PP, pp. 1-13, 2025.
doi: https://doi.org/10.1109/TIM.2024.3509582
pdf: https://arxiv.org/pdf/2412.02768.pdf