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Performance bounds for estimation under uncertainty

✍ Scribed by Mohamed Z. Dajani

Publisher
Elsevier Science
Year
1974
Tongue
English
Weight
537 KB
Volume
10
Category
Article
ISSN
0005-1098

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✦ Synopsis

Derived upper and lower bounds on the unconditional estimation error variance may be used as a performance measure for linear uncertain estimation problems such as those found in geophysicai systems.

Summary--For the class of linear Gauss-Markov systems with binary parameters uncertainty, the minimum variance estimate of the state and associated covariance of error expressions were derived in a closed form in [1,2]. In this paper expressions for the conditional and unconditional covariances of error matrices are presented for the M-ary case. Useful upper and lower bounds for the unconditional covariance of error are also presented which are valid, on the average, for any measurement sequence. A geophysical seismic data filtering example applying these results is also given.

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