Code covered by the BSD License  

Highlights from
Introduction to Unscented Kalman Filtering


5.0 | 2 ratings Rate this file 52 Downloads (last 30 days) File Size: 2.29 MB File ID: #24917
image thumbnail

Introduction to Unscented Kalman Filtering



04 Aug 2009 (Updated )

Unscented Kalman filtering tutorial: Simulink and tilt sensor case study.

| Watch this File

File Information

This engineering note is the first of two parts:

Part 1 Design and Simulation.
Part 2 Real-World System Realization. (Being written)

It aims at demonstrating how you may use Matlab/Simulink together with Rapid STM32 blockset and ARM Cortex-M3 processors (STM32) to develop digital signal processing systems; using a tilt sensor as a case study.

It covers the development process from design, simulation, hardware-in-the-loop testing, and creating a stand-alone embedded system. The content is supposed to be as simple/introductory as possible.

In this first part:

1. The motivation for using Simulink for embedded system development is explained.
2. A simplified model of tilt sensor system is developed.
3. Kalman filtering and Unscented Kalman filtering (UKF) theory is summarized.
4. Graphical instructions are then provided to guide you through the whole process of implementing a Simulink model to design, simulate, and evaluate the performance of an UKF for a tilt sensor system.

Note: Source code is also provided to perform Monte Carlo simulation based on Simulink model to evaluate UKF performance using covariance analysis.

In the second part, graphical instructions will be provided to guide you through the process of transferring your design from Simulink model to real-world stand-alone tilt sensor system based on Rapid STM32 - R1 Stamp board.

Visit for more information.

Required Products Simulink Coder
Embedded Coder
MATLAB release MATLAB 7.8 (R2009a)
Tags for This File   Please login to tag files.
Please login to add a comment or rating.
Comments and Ratings (2)
09 Apr 2010 AYYADI Othmane  
19 Oct 2009 addie irawan

Thanks your model helps me a lot ...if you have extended document please e-mail to...

05 Aug 2009

Change the Title and add a link to another introductory note on Kalman filtering at

05 Aug 2009

Add seed1 and seed 2 declarations to PreLoadFcn callback so the model can run stand-alone.

Contact us