Titlebook: Kalman Filtering with Real-Time Applications; Charles K. Chui,Guanrong Chen Textbook 19871st edition Springer-Verlag Berlin Heidelberg 198

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Preliminaries,d even among many applied mathematicians and engineers. The main objective of this treatise is to present a thorough discussion of the mathematical theory, computational algorithms, and application to real-time problems of the Kalman filter.

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Correlated System and Measurement Noise Processes,ve assumed all along that . for .,. = 0,1,.... However, in applications such as aircraft inertial navigation systems, where vibration of the aircraft induces a common source of noise for both the dynamic driving system and onboard radar measurement, the system and measurement noise sequences {..} an

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Extended Kalman Filter and System Identification, procedure is usually performed in deriving the filtering equations. We will consider a real-time linear Taylor approximation of the system function at the previous state estimate and that of the observation function at the corresponding predicted position. The Kalman filter so obtained will be call

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Decoupling of Filtering Equations,al-time. However, if the state vector is of very high dimension ., and only a few components are of interest, this filter gives an abundance of useless information, an elimination of which should improve the efficiency of the filtering process. A decoupling method is introduced in this chapter for t

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Notes, real-time applications. No attempt was made to cover all the rudiment of the theory, and only a small sample of its applications has been included. There are many texts in the literature that were written for different purposes. The most recent ones include Balakrishnan (1984), Chen (1985), Goodwin

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