Implementation of a C Library of Kalman Filters for Application on Embedded Systems

Having knowledge about the states of a system is an important component in most control systems. However, exact measurement cannot always be provided because it either not technically possible or only with significant effort. Therefore, state estimation plays role applications. The well-known and widely used Kalman filter often employed for this purpose. This paper describes implementation nonlinear algorithms, extended unscented square-rooting, programming language C, that are suitable use on embedded implementations deal single double precision data types depending application. newly implemented filters demonstrated context semi-active vehicle damper tire–road friction coefficient as application examples, providing real-time capability. Their per-formances were evaluated tests electronic unit rapid-prototyping platform.