Understanding Sensor Fusion and Tracking, Part 4: Tracking a Single Object With an IMM Filter

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: https://bit.ly/2MKu4Om
The mathematics behind IMM: https://bit.ly/2J1Fcpl
Kalman Filters - Overview: https://bit.ly/2Me89QJ

Previous Lectures:
1. Understanding Sensor Fusion and Tracking, Part 1: What Is Sensor Fusion?
2. Understanding Sensor Fusion and Tracking, Part 2: Fusing a Mag, Accel, & Gyro Estimate
3. Understanding Sensor Fusion and Tracking, Part 3: Fusing a GPS and IMU to Estimate Pose