Intensive Course on
Kalman Filtering –Theory and Applications
National Taiwan University of Science and Technology
3 credits certification will be given for accomplishing the course
April 22~June 21, 2013
18:15~21:05, each Tue., and Thu.
Offered by
Dr. Yeong-wei Andy wu
Chief Engineer (retired) Flight and Control Directorate
Space and Intelligence Systems, Boeing Company
Boeing Senior Technical Fellow
The Kalman filter is probably the most successful and widely-used part of so-called "modern estimation theory“
since R.E. Kalman published his famous paper in 1960 describing a recursive solution to the discrete-data linear
filtering problem. It has been used as the central piece of the algorithm for many applications in
aircraft/ship/ground vehicle navigation, spacecraft attitude determination, orbit determination, missile guidance
and control, RF antenna/laser terminal target acquisition/tracking, RF/optical signal acquisition and tracking,
seismic data processing, medical signal processing, and other fields in the industry.
This course is designed for graduate students and practitioners, such as system engineers, system analysts,
software engineers, hardware engineers, and project managers, as well as military operational personnel who
want to develop and/or enhance their knowledge and experiences in Kalman filters. It will provides a solid
foundation for both the basic theory and practical application of Kalman filtering. Specific case studies are
provided to illustrate the latter, including GPS navigation, integrated inertial navigation, precision navigation using
GPS carrier-phase, spacecraft stellar-inertial attitude determination, spacecraft orbit determination, precision
clock, and radar/laser target tracking. Lectures are further augmented by computer lab sessions using MATLAB to
help participants develop insights through hands-on experience.
Using the knowledge and skills gained through this course, students should be able to design Kalman filters for
their specific fields; analyze the performance; develop the system, hardware, and software architecture; and
resolve problems encountered in system integration, validation, and verification.
Lecturer Summary:
Dr. Wu has over 32 years of industry experience. He is a nationally recognized expert in the areas of spacecraft
attitude determination and control; spacecraft antenna pointing and beam steering; airborne/space optical sensor
Line-of-Sight (LOS) attitude determination and calibration; space cryogenic cooler vibration and temperature
controls; transfer alignment for weapon delivery systems; and gimbal LOS pointing and stabilization. Dr. Wu had
52 issued US patents in the above fields and 51 papers published in AAS/AIAA/IEEE Conference Proceedings,
AIAA Journal of GNC, and the Hughes Technical Journal. Dr. Wu has taught several technical courses including
the Boeing Advanced Technical Education Program (ATEP) course on “Spacecraft Attitude Determination” and
UCLA Extension courses on “Kalman Filtering – Theory and Applications” and “Spacecraft Attitude Control”
Awards:
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Recipient of 2005 Boeing Company Special Invention Awards
Recipient of 2003 Boeing Chief Technology Office Professional Excellence Award
Recipient of 2003 Asian American Engineer of the Year Award
Recipient of 2002 Boeing Company Special Invention Awards
Recipient of 2002 Boeing Satellite Systems Patent Award
Recipient of 2000 Boeing Satellite Systems Patent Award
Recipient of 1997 Hughes Space and Communication Technical Excellence Award
Recipient of 1994 Hughes Aircraft Company Patent Award
Registration please contact Miss Tu, (02) 27376685 or email to tu6685@mail.ntust.edu.tw
For any query, please email to su@orion.ee.ntust.edu.tw or call (02) 27376704 Prof. Shun-Feng Su
Intensive Course on
Kalman Filtering –Theory and Applications
National Taiwan University of Science and Technology
3 credits certification will be given for accomplishing the course
April 22~June 21, 2013
18:15~21:05, each Tue., and Thu.
Course Syllabus
1) Reviews of mathematics
○ Review of vectors & matrices
○ Review of linear system theory
• Frequency domain representation
• Time domain representation
○ Review of probability & random process
theory
2) Basic estimation theory
○ Deterministic estimation – least squared
and weighted least squared estimates
○ Probabilistic estimation – maximum
likelihood and Baysian estimates
○ Stochastic estimation – Wiener filter
○ Kalman-Bucy filter
3) Kalman filter theory & practical application
considerations
○ Continuous Kalman filter: from discrete to
continuous
○ Special cases
• Correlated process and
measurement noises
• Correlated measurement noises
○ Solution of the Riccati equation; steady
state Riccati equation
○ Kalman-Bucy filter
• Orthogonal projection principle
• Wiener filter/Kalman-Bucy filter
relationship
○ Adaptive Kalman filter
• Use of innovation process
• Use of real-time parameter
identification
○ Kalman filter implementation
considerations
• Modeling problems: filter
divergence
• Filter divergence solutions
− Estimate un-modeled
states
− Add process noise
− Finite memory filtering
− The Ɛ technique
○ Constraints imposed by the computer
• Computation complexity
• Finite word length effect
○ Numerical stability & alternative forms
• Joseph formulation
• Square root formulation
• UDUT covariance factorization
formulation
○ Kalman filter: architecture and algorithm
4)Case Studies
○ Case study 1: Kalman filter for precision
clock
○ Case study 2: Kalman filter for Stellar
Inertial Attitude Determination (SIAD)
○ Case study 3: Kalman filter for RF
Antenna Pointing/Acquisition/Tracking
○ Case study 4: Kalman filter for Integrated
Strap-Down Inertial Navigation
5)Computer Lab sessions
○ 1: Design & analysis of Kalman filter for
precision clock
○ 2: Hands-On Lab Session on Bearing
Only
Tracking problems
○ 3: Hands-On Lab Session on 2D-GPS
Registration please contact Miss Tu, (02) 27376685 or email to tu6685@mail.ntust.edu.tw
For any query, please email to su@orion.ee.ntust.edu.tw or call (02) 27376704 Prof. Shun-Feng Su