(Sponsored) Extended Kalman Filter - Sensor Fusion #3 - Phil's Lab #37

Phil explains the theory, practical considerations, and overview of the Extended Kalman Filter for sensor fusion on microcontrollers.

Extended Kalman Filter (EKF) overview, theory, and practical considerations. Real-world implementation on an STM32 microcontroller in C in the following video. Part 3 of sensor fusion video series. (AD: This video includes a paid promotion for Altium.) [SUPPORT] Free trial of Altium Designer: altium.com/yt/philslab (AD) Patreon: patreon.com/phils94 [LINKS] Git: github.com/pms67 Sensor Fusion Part 2: youtu.be/BUW2OdAtzBw Sensor Fusion Part 1: youtu.be/RZd6XDx5VXo Small Unmanned Aircraft (Book): uavbook.byu.edu/doku.php State observers: Observers: en.wikipedia.org/wiki/State_observer Euler Angles: control.asu.edu/Classes/MMAE441/Aircraft/441Lecture9.pdf (from slide 17) [TIMESTAMPS] 00:00 Introduction 00:28 Previous Videos 00:41 Altium Designer Free Trial (Ad) 01:05 Content 01:43 Sensor Fusion Recap 02:26 Complementary Filter Recap 03:08 Choosing alpha 03:29 Kalman Filter Overview 04:19 Estimation Error and Covariance 05:00 Non-Linear and Discrete-Time Kalman Filter 05:47 Book Recommendation 06:05 EKF Algorithm Overview 07:19 Practical Example (Attitude Estimation) 07:49 Prediction (EKF Step 1) 10:14 Update (EKF Step 2) 13:32 Complete EKF Algorithm 14:04 Practical Issues and Considerations 15:14 Next Video ID: QIBvbJtYjWuHiTG0uCoK