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Definition of "Kalman filter" |
A computational algorithm that processes measurements to deduce an optimum estimate of the past, present, or future state of a linear system by using a time sequence of measurements of the system behavior, plus a statistical model that characterizes the system and measurement errors, plus initial condition information. / The Kalman filter, also known as linear quadratic estimation, is an algorithm that uses a series of measurements observed over time, containing noise and other inaccuracies, and produces estimates of unknown variables that tend to be more precise than those based on a single measurement alone. More formally, the Kalman filter operates recursively on streams of noisy input data to produce a statistically optimal estimate of the underlying system state. The filter is named for Rudolf E. Kalman, one of the primary developers of its. / High Definition Compatible Digital is a digital encoding and decoding process for compact disc and DVD audio recording. / the method of recursively estimating the state vector of a linear dynamic system based on noisy output measurements.This method combines the knowledge of system parameters, statistical characteristics of initial state, process and measurement noises,and the current measurement to update the existing estimate of the state. Kalman filter is the minimum variance filter if the initial state and the noises are Gaussian distributed;otherwise, it is the linear minimum variance filter. In addition to providing the expected value of the state conditional on the measurement,this filter generates the estimation error covariance, which signifies the uncertainty associated with this estimate. This covariance can be calculated off-line before running the filter. |
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