Kalman Filtering: Theory and Applications

MECH&AE 830.70
This course is designed for practitioners who want to develop, streamline, or enhance their knowledge and experiences in Kalman filters.
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What you can learn.

  • Learn about GPS navigation, integrated inertial navigation, precision navigation using GPS carrier-phase, spacecraft stellar-inertial attitude determination, precision clock, and radar/laser target tracking
  • Develop insights through hands-on experience with MATLAB augment lectures
  • Learn 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

About this course:

This course is designed for practitioners, such as system engineers, system analysts, software engineers, hardware engineers, and project managers, as well as military operational personnel who want to develop, streamline, or enhance their knowledge and experiences in Kalman filters. Instruction provides a solid foundation for both the basic theory and practical application of Kalman filtering. Case studies illustrate the latter, including GPS navigation, integrated inertial navigation, precision navigation using GPS carrier-phase, spacecraft stellar-inertial attitude determination, precision clock, and radar/laser target tracking.

The course is unique in providing participants with a ready-to-use, step-by-step approach for employing Kalman filtering to their practical applications. The instructors have a combined 50 years of experience in Kalman filter design, analysis, tuning, implementation, validation, and verification. Instruction includes detailed discussions on the hardware and software architectures of Kalman filter-based systems, as well as system integration issues, such as time-tagging and precision time matching of sensor measurements, numerical stability, and divergence prevention. Computer lab sessions using MATLAB augment lectures to help participants develop insights through hands-on experience.

Using the knowledge and skills gained through this course, participants 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.

 

 

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