Why Use Kalman Filters? | Understanding Kalman Filters, Part 1

Download our Kalman Filter Virtual Lab to practice linear and extended Kalman filter design of a pendulum system with interactive exercises and animations in MATLAB and Simulink: https://bit.ly/3g5AwyS Discover common uses of Kalman filters by walking through some examples. A Kalman filter is an optimal estimation algorithm used to estimate states of a system from indirect and uncertain measurements. In the first example, you’re going to see how a Kalman filter can be used to estimate the state of a system (the internal temperature of a combustion chamber) from an indirect measurement (the external temperature of the combustion chamber). The second example demonstrates another common use of Kalman filters, in which you can optimally estimate the state of a system (e.g., the position of a car) by fusing measurements from multiple sources (e.g., an inertial measurement unit (IMU), an odometer, and a GPS receiver) in the presence of noisy measurements. Check out additional resources: Download examples and code - Design and Simulate Kalman Filter Algorithms: https://bit.ly/2Iq8Hks Kalman Filter Design Example: https://bit.ly/3a0nLWs Design and use Kalman filters in MATLAB and Simulink: https://bit.ly/3i4VKwG -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2022 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.