Monday, April 24
8:30 a.m. - 9:30 a.m.	Introduction to Inertial Navigation Systems (INS) and Aiding	Dr. Michael Braasch
9:30 a.m. - 11:00 a.m.	Image Aided Inertial Navigation – Design, Analysis, and Alternatives	Dr. Michael Veth
11:15 a.m. - 12:45 p.m.	Magnetic Aided Inertial Navigation	Dr. Aaron Nielsen
12:45 p.m. – 2:15 p.m., Lunch on Your Own
2:15 p.m. - 3:45 p.m.	Signals of Opportunity Based Navigation	Dr. José A. del Peral-Rosado and Dr. Christian Gentner
4:00 p.m. - 5:30 p.m.	Factor Graphs for Non-linear Estimation Problems	Dr. Clark Taylor

Introduction to Inertial Navigation Systems (INS) and Aiding

Time: Monday, April 24, 8:30 a.m. - 9:30 a.m.
Room: Big Sur

For over 70 years inertial navigation systems have proven to be indispensable in the aerospace industry. They are immune to jamming and provide position, velocity and attitude with low noise, high data rates and low data latencies. Since the 1960s, the long-term drift inherent in any inertial system has typically been corrected through the integration of an external aiding source via an extended Kalman filter. In this lecture we will review the key operating principles of inertial navigation and will highlight the major error characteristics. The primary inertial-aiding design architectures will then be discussed along with performance considerations.

Dr. Michael Braasch is a Professor of EE at Ohio University and has taught inertial navigation short courses at Honeywell, Kearfott and Northrop Grumman.

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Image Aided Inertial Navigation – Design, Analysis, and Alternatives

Time: Monday, April 24, 9:30 a.m. - 11:00 a.m.
Room: Big Sur

This course focuses on the rapidly growing area of image and video-based navigation techniques. The topics will include detailed descriptions of camera calibration and removal of image distortion, feature extraction techniques, methods for solving the correspondence problem and extracting navigation information. Strategies for incorporating image updates into navigation systems are presented including feature matching and tracking, optical flow, and methods for coupling with inertial sensors.

Examples of real-time implementations are presented along with references to open-source software packages. Applicable references are provided for further study.

This course will be presented at an engineering level with the goal of understanding the various components and algorithms required to construct a multi-sensor image-aided navigation system. The course is appropriate for engineers with experience in the navigation field with an interest in learning practical approaches for incorporating image observations into navigation systems.

Dr. Michael Veth is the president and CEO of Veth Research Associates. He leads a team of engineers dedicated to pursuing novel solutions in autonomous navigation, control, and tracking applications for GNSS-denied and degraded environments.

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Magnetic Aided Inertial Navigation

Time: Monday, April 24, 11:15 a.m. - 12:45 p.m.
Room: Big Sur

Magnetic-Aided Inertial Navigation (MagNav) uses the magnetic anomaly of the Earth’s crust as a map to provide corrections to an inertial navigation system. This tutorial covers the essentials required for MagNav, including the required sensor technology, magnetic anomaly maps for navigation, as well as removal of the magnetic fields generated by vehicles and the techniques to incorporate magnetic measurements into an inertial navigator.

Dr. Aaron Nielsen is a research assistant professor at the Air Force Institute of Technology. He received a PhD in Physics from the University of Maryland focused on magnetic microscopy of superconductors and then worked in industry with a focus on airborne magnetics.

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12:45 p.m. – 2:15 p.m., Lunch on Your Own

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Signals of Opportunity Based Navigation

Time: Monday, April 24, 2:15 p.m. - 3:45 p.m.
Room: Big Sur

Signals of Opportunity (SoO) can be used to complement or back-up Global Navigation Satellite Systems (GNSS) and other dedicated positioning systems. This tutorial covers the fundamentals principles of SoO based navigation together with practical examples from indoor positioning, Simultaneous Localization and Mapping (SLAM) methods using SoO and 5G networks for positioning.

Dr. José A. del Peral-Rosado is working within the Future Navigation Programs Department at Airbus Defence and Space GmbH. He conducted theoretical and experimental research activities on hybrid GNSS, LTE, and 5G localization.

Dr. Christian Gentner is working at the Institute of Communications and Navigation of the German Aerospace Center (DLR). His current research focuses on multipath assisted and indoor positioning. In 2020, he founded the DLR-spin-off TrackIn which offers an accurate, simple, and affordable ultra-wideband based localization technology which is used in retail.

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Factor Graphs for Non-linear Estimation Problems

Time: Monday, April 24, 4:00 p.m. - 5:30 p.m.
Room: Big Sur

While the Kalman Filter (KF) family (linear KF, EKF, UKF, etc.) has been the workhorse of navigation systems for several decades, the factor graph is a generalization of the Kalman Filter that offers improved performance for non-linear systems and is more easily applied to complex systems. In this tutorial, factor graph method for estimating non-linear systems will be introduced to those who are already familiar with Kalman Filter estimators. A comparison of the factor graph vs the extended Kalman Filter will be presented.

Dr. Clark Taylor is the ANT Center director and an assistant professor at the Air Force Institute of Technology. He received his PhD from University of California, San Diego, and previously worked as a senior research engineer with the Air Force Research Laboratory and an assistant professor in electrical engineering at Brigham Young University.

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