Check out the other videos in the series: Part 1 - What Is Sensor Fusion?: Part 2 - Fusing an Accel, Mag, and Gyro to Estimation Orientation: Part 3 - Fusing a GPS and IMU to Estimate Pose: Part 4 - Tracking a Single Object With an IMM Filter: Part 5 - How to Track Multiple Objects at Once: This video describes how we can improve tracking a single object by estimating state with an interacting multiple model filter. We will build up some intuition about the IMM filter and show how it is a better tracking algorithm than a single model Kalman filter. We cover what makes tracking a harder problem than positioning and localization because there is less information available to the tracking filter. We explain how the IMM makes up for the lack of information, and show some simulated results. Check out these other references! Tracking Maneuvering Targets - Example: The mathematics behind IMM: Kalman Filters - Overview: Multi-Object Tracking for Autonomous Systems and Surveillance Systems - Ebook - Multi-Object Tracking: -------------------------------------------------------------------------------------------------------- Get a free product trial: Learn more about MATLAB: Learn more about Simulink: See what's new in MATLAB and Simulink: © 2019 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.