Pre-conference tutorials have been organized to provide in-depth learning prior to the start of the technical program. All courses will be taught in a classroom setting. Electronic course notes will be made available for download by registered attendees from the conference website; registered attendees are encouraged to download notes in advance of the tutorials. Paper notes will not be provided. Power will not be available to course attendees for individual laptop computers; please come prepared with adequate battery power if required.

Tutorial registration is required for each individual course. ION reserves the right to cancel a tutorial based on inadequate registration or the unavailability of the instructor. Registration for tutorials is accomplished online through the normal conference registration process.

Tutorial Registration Rates:
Before March 23: $400 per course unit
After March 23: $450 per course unit

Monday, April 23: 9:00 a.m. - 12:30 p.m.
Contemporary and Emerging Inertial Sensor Technologies
Ralph E. Hopkins
Alternative Navigation Methods Exploiting Integration with Inertial Measurements
Dr. Maarten Uijt de Haag
Monday, April 23: 1:30 p.m. - 5:00 p.m.
Fundamentals of Inertial Navigation Systems and Aiding
Dr. Michael Braasch
Fundamentals of Nonlinear Recursive Estimation
Dr. Michael J. Veth, Ph.D.

Contemporary and Emerging Inertial Sensor Technologies

Time: Monday, April 23, 9:00 a.m. - 12:30 p.m.
Room: Spyglass 1

This course will present an overview of current state-of-the art inertial instrument technology and how emerging developments in nano and micro-scale fabrication, solid-state optics and cold atom technologies are influencing gyroscope and accelerometer design. The course will initially focus on the recent developments in MEMS-based inertial instruments and how MEMS technology is revolutionizing the inertial guidance navigation and control (GN&C) industry. Current industry trends will be discussed along with examples of MEMS inertial technology in the commercial, military and space sectors, including advanced systems, which integrate inertial MEMS with GPS. New developments in inertial instrument design will follow with discussion of how advanced nano and microfabrication methods, new solid-state optical component developments and cold atom interferometry are being exploited in the next generation of precision gyro and accelerometer designs.

Suitable for experienced inertial instrument practitioners, it will also be of interest to novice developers, as it will cover an overview of basic inertial sensing principles, and detailed discussion of gyroscope and accelerometer designs. This course will appeal to R&D, systems and manufacturing engineers, managers and executives, and will conclude with a discussion on the future direction of advanced inertial technologies.

Course Outline:

  • Overview of Inertial Sensing
  • MEMS Accelerometers and Gyroscopes
  • Emerging Inertial Sensors
  • Emerging INS Applications and Integration
  • Future Direction of Inertial Technology

Ralph E. Hopkins Ralph E. Hopkins is a Distinguished Member of the Technical Staff and Group Leader in the Guidance Hardware Division at Draper Laboratory where he is responsible for the design and development of inertial instruments and sensors. He is an invited speaker for short course tutorials on inertial instruments and inertial technology and has presented internationally for the NATO Science Technology Organization sponsored lecture series and symposia on navigation technology.




Alternative Navigation Methods Exploiting Integration with Inertial Measurements

Time: Monday, April 23, 9:00 a.m. - 12:30 p.m.
Room: Spyglass 2

This tutorial introduces the latest technology trends for navigating in difficult urban and indoor environments where the performance of typical Global Navigation Satellite System (GNSS) receivers is deteriorated or absent. This introduction will shortly discuss three broad categories of alternative navigation (Alt-Nav) techniques including image/Ladar/Doppler/dead-reckoning aiding of inertial sensors, beacon-based navigation (including pseudolites), and navigation using signals-of-opportunity such as Wi-Fi signals. Then the course will focus on the latest alternative navigation technologies based on electro-optical techniques specifically. The Alt-Nav technologies presented include laser- and image-aided INS and Simultaneous Localization and Mapping (SLAM) methods using laser and imaging sensors. In the former methods, tight integration with an INS should lead to navigation performance similar to that achieved in today’s GPS/INS integrations. The discussion includes the basic principles of integration with an IMU; EO/IMU integration mechanizations; the use of correlation techniques, feature-based techniques or optical-flow-based techniques; the use of a priori information such as terrain and feature databases; and SLAM approaches.

Course Outline:

  • Introduction to alternative navigation,
  • Alternative navigation categories,
  • Basic principles of integration with an IMU,
  • EO/IMU integration mechanizations,
  • Correlation techniques, feature-based techniques or optical-flow-based techniques,
  • Use of passive and active electro-optical sensors to aid the inertial,
  • Passive EO sensors: image-based navigation using features,
  • Active EO sensors: Ladar-based navigation using correlation and feature based techniques,
  • Simultaneous Localization and Mapping approaches;
  • Integration of image-based and Ladar-based sensors.

Dr. Maarten Uijt de Haag Dr. Maarten Uijt de Haag is the Edmund K. Cheng Professor of Electrical Engineering and Computer Science and a Principal Investigator (PI) with the Avionics Engineering Center at Ohio University since 1999. He has authored or co-authored has authored or co-authored over 140 navigation-related publications and seven book chapters, he is a senior member of the IEEE, an associate Fellow of the AIAA, is currently an associate editor for NAVIGATION: The Journal of the Institute of Navigation. Dr. Uijt de Haag was awarded the ION’s 2008 Thurlow Award for his contributions to laser-based navigation and integrity monitors for synthetic vision systems.




Fundamentals of Inertial Navigation Systems and Aiding

Time: Monday, April 23, 1:30 p.m. - 5:00 p.m.
Room: Spyglass 1

This tutorial will start by highlighting the basic principles of operation of an inertial navigation system. The course will focus initially on the concepts underlying the algorithms used to determine position, velocity and attitude from inertial sensor measurements. Key error characteristics will be described as well such as Schuler oscillation and vertical channel instability. We will also consider the impact of various sensor errors on system performance. The tutorial will continue by covering the basics of Kalman filtering and aided-inertial systems. The daunting matrix mathematics involved in the full algorithm can be extremely intimidating to the newcomer. The basic concepts of estimation theory will be briefly reviewed, and the Kalman Filter will be described first in terms of simple one-dimensional problems for which the full algorithm reduces to an approachable set of scalar equations. We will look at the performance of the filter in some simple case studies and by the end will have an intuitive feel for how the full filter operates. We will apply the Kalman filter to the aiding of inertial systems. We will see how external sources of position and velocity (such as GPS) can be used first to measure inertial system error and then, with the aid of the Kalman filter, to estimate and correct inertial sensor error as well as system error.

Dr. Michael Braasch Dr. Michael Braasch is the Thomas Professor of Electrical Engineering and is also a Principal Investigator with the Ohio University Avionics Engineering Center. Mike has over 30 years of experience in navigation research and has also taught graduate-level courses in inertial navigation, Kalman filtering and integrated navigation for the past 20 years. Mike has also taught short courses on these subjects at all of the major inertial navigation system manufacturers in the United States. Mike is a Fellow of the Institute of Navigation, a Senior Member of the IEEE and is an instrument-rated commercial pilot.




Fundamentals of Nonlinear Recursive Estimation

Time: Monday, April 23, 1:30 p.m. - 5:00 p.m.
Room: Spyglass 2

This course presents an overview of estimation techniques suitable for systems with nonlinearities that are not well suited to traditional linear or extended Kalman filter algorithms. The course begins with an overview of the generalized recursive estimation problem and associated notation and conventions. Next, the limitations of applying linear theory to nonlinear problems are addressed, along with techniques for compensating for these adverse effects, including a brief overview of the traditional extended Kalman filter and Gaussian sum techniques. In addition, the mathematical effects of system nonlinearities on random processes are presented and discussed along with computational techniques for efficiently capturing this information, which serves as the foundation for the development of many nonlinear estimators. Next, the unscented Kalman filter (UKF) and particle filters (PF) are presented and analyzed using multiple examples. Common limitations of nonlinear estimators are addressed and hybrid solutions are discussed including Rao-Blackwell marginalization approaches. The course concludes with a discussion and qualitative comparison of the strengths and weaknesses of various recursive estimation techniques from linear Kalman filtering to particle filtering, and their applicability to various problem spaces. Numerous Matlab examples are presented to illustrate sample nonlinear estimation algorithms and performance.

This course will be presented at an engineering level with the goal of understanding the fundamental concepts behind current nonlinear estimation algorithms and how they compare to traditional approaches. The course is appropriate for engineers and scientists with linear and extended Kalman filter experience with an interest in the potential benefits of nonlinear estimation algorithms for difficult problems. The “Fundamentals of Kalman Filtering” sequence by Dr. Gewal is a recommended prerequisite for students wishing to enhance their background prior to this course.

Dr. Michael J. Veth, Ph.D. Dr. Michael J. Veth, Ph.D., 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. He received his BSEE from Purdue University and a Ph.D. in Electrical Engineering from the Air Force Institute of Technology. He is a member of the ION, a Senior Member of the IEEE, and a graduate of the US Air Force Test Pilot School.