Synchronization of Input and Output Measurements using a Kalman Filter

J. Fox (Germany)


Kalman filter, sigma-point Kalman filter, latency estima tion, asynchronous measurements


Kalman filters are used when data from different sensors is combined to obtain a suboptimal estimation of a dynamic system’s state. In most applications, the sensor data enters the filter in two places: some data is fed to the inputs of the dynamic system while other data is used as reference measurements of the system’s outputs. In order to yield the best possible estimations, both types of sensors have to be well synchronized, but a hardware synchronization mech anism is not always available. In this paper, the Kalman filter is modified to estimate both the system’s state and the time delay between input and output measurements. Simu lations show that an accurate software synchronization can be achieved by using this method and that the state esti mates improve largely.

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