1985
DOI: 10.1109/tac.1985.1103859
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A geometric approach to the singular filtering problem

Abstract: Abstract-We consider the least-squares filtering problem for a stationary Gaussian process when the observation is not fuJly corrupted by white noise, the so-called "singular" case. An optimal estimator is constructed consisting of an integrating part, which is, as in the regular case, computed from a spectral factorization or an equivalent matrix problem, and a differentiating part whose parameters are computed from a single matrix equation. This improves on older results which either work under restrictive a… Show more

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Cited by 26 publications
(7 citation statements)
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“…Because the examples in this article pertain only to a single-transducer, single-disturbance case, we merely refer the reader to Schumacher (1985) for a thorough treatment of this issue.…”
Section: Power Generation Limit For a Vibratory Energy Harvestermentioning
confidence: 99%
“…Because the examples in this article pertain only to a single-transducer, single-disturbance case, we merely refer the reader to Schumacher (1985) for a thorough treatment of this issue.…”
Section: Power Generation Limit For a Vibratory Energy Harvestermentioning
confidence: 99%
“…The early applications of this problem have been confined to the SISO case where the interpolation has been performed by a scalar transfer function [l], [3]. The extension to the multivariable case was first introduced in [2] and used by many others [7], [8]; it has imposed, however, the interpolation requirements on the whole matrix. Since the straightforward extension of the SISO interpolation problem has led to overdetermined solutions in the multivariable case, a directional interpolation problem has been presented in [9] which resolves the overdetermination.…”
Section: Discussionmentioning
confidence: 99%
“…M that leads, for a minimum value of X 2 0, to MTI -T 1 = XU (2) where U is an inner transfer function matrix in H,oO,, that satisfies the following:…”
Section: Given T1'hzl and Tzeh?xr Where Is Nonsingular And R'mentioning
confidence: 99%
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“…The first two conditions on Q m require that Q, is a rank-minimizing solution of a linear matrix inequality. The same linear matrix inequality is also appearing in the szngular filtering problem (see [26], this problem is dual to the singular linear quadratic control problem). It can be shown that the largest solution of the linear matrix inequality, whose existence is guaranteed since ( a ) C,,, has L, norm less than or equal to y.…”
Section: A T P M + P a = P B B T P M A -B B T P M Is Asymptoticalmentioning
confidence: 98%