IEEE Transactions on Aerospace and Electronic Systems · 1990 · 59 citations · 7 references
ComputingAutonomous SystemsProcess ControlStochastic ModelingUncertainty QuantificationAdaptive ControlKalman FilteringState EstimationState-space ModelsTracking SystemsUncertainty EstimationAdaptive Kalman FilterError Variance EstimationFilteringKalman Filter EstimationKalman Filter TrackingMeasurement Noise EstimationProcess Noise EstimationTarget Tracking
A simple algorithm for estimating the unknown process noise variance of an otherwise known linear plant, using a Kalman filter is suggested. The process noise variance estimator is essentially dead beat, using the difference between the expected prediction error variance, computed in the Kalman filter, and the measured prediction error variance. The estimate is used to adapt the Kalman filter. The use of the adaptive filter is demonstrated in a simulated example in which a wildly maneuvering target is tracked.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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