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Introduction to Unscented Kalman Filtering

5.0 | 3 ratings Rate this file 35 Downloads (last 30 days) File Size: 2.29 MB File ID: #24917 Version: 1.2
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Introduction to Unscented Kalman Filtering



04 Aug 2009 (Updated )

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

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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)
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Comments and Ratings (4)
15 Sep 2014 Krisada Sangpetchsong

Dear Adnan

Thank you for your kind comment.

I have not the time to finish part 2 - the real-world implementation example.

However, please visit our site at to learn about our hardware and software code generation tools for microcontrollers.

Specifically, this is the tutorial for getting started:

Comment only
03 Sep 2014 Adnan Ishtay

Thank you very very much, you are the best one who explains and simplifies KALMAN filter in this clear way. Could you please send me the part 2 upon been ready. it will be very helpful also, thanks again.

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 1.1

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

05 Aug 2009 1.2

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

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