Computational requirements for a discrete Kalman filter

How practical is a Kalman filter? One answer to this question is provided by the computational requirements for the filter. Computational requirements-computational time per cycle (iteration) and required storage-determine minimum sampling rates and computer memory size. These requirements are provided in this paper as functions of the dimensions of the important system matrices for a discrete Kalman filter. Two types of measurement processing are discussed: simultaneous and sequential. It is shown that it is often better to process statistically independent measurements in more than one batch and then to use sequential processing than to process them together via simultaneous processing.