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CONTINUOUS LINEAR FILTERS
CHAPTER 3 PROPERTIES OF KALMANS EQUATIONS
CHAPTER k SOME APPLICATIONS OF KALMANS
1 other sections not shown
AP(t application of Kalman's applied assumed becomes best estimate bounded by positive Chapter control vector cost function covariance defined derivative with respect determined Dirac function equations 3-1 equations 3-25 equations of motion error e(t estimate of x(t estimate x(t estimation problem estimation theory estimator equation expected value expression filter h t,v filtering theory Gaussian process h t,t)K t,y h t,v)K v,y)dv h t,y initial conditions input vector Kalman-Bucy filter least squares Liapunov function linear dynamic system linear filter linear system markovian matrix of eq nominal trajectory non-singular observable and uniformly on-board optimal estimate optimum filter output positive definite process of known random function random process represents rewritten right-hand side satisfy section 3-5 shown that P(t side of eq sinh(fv solved spacecraft stochastic process Substituting eq sufficient condition transition matrix uncorrelated uniformly completely controllable uniformly completely observable variables variance equation eq Wiener-Hopf equation Wiener's equation zero