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Filtering problem under unreliable sampling

Filtering problem under unreliable sampling

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The authors study the filtering problem under the assumption that sampling is unreliable; i.e. some of the measurement data are not obtained at some sampling instants. The minimum-variance estimator is derived and its stability is studied in connection with the degree of unreliability of the sampling.

Inspec keywords: estimation theory; filtering theory; sampled data systems; signal sampling

Other keywords: stability; minimum-variance estimator; filtering problem; unreliable sampling

Subjects: Signal processing and detection; Discrete control systems; Other topics in statistics; Information theory; Other topics in statistics

References

    1. 1)
      • T. Hagiwara , T. Fujimura , M. Araki . Generalized multirate-output controllers. Int. J. Control , 3 , 597 - 612
    2. 2)
      • A.H. Jazwinski . (1970) Stochastic processes and filtering theory.
    3. 3)
      • R.E. Kalman , R.S. Bucy . New results in linear filtering and prediction theory. J. Basic Eng. Trans. ASME , 950 - 1008
    4. 4)
      • J.J. Deyst , C.F. Price . Conditions for asymptotic stability of the discrete minimum-variancelinear estimator. IEEE Trans. Automatic Control , 6 , 702 - 705
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