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Journal ArticleDOI

Estimation using a multirate filter

D. Andrisani, +1 more
- 01 Jul 1987 - 
- Vol. 32, Iss: 7, pp 653-656
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TLDR
This note presents both optimal and suboptimal filtering algorithms for estimating state variables based on measurements sampled at two different data rates.
Abstract
This note presents both optimal and suboptimal filtering algorithms for estimating state variables based on measurements sampled at two different data rates. The optimal algorithm consists of two parallel Kalman filters; one processes the fast rate measurement and is of reduced-order, and the other processes the residuals from the first filter along with the slow rate measurement. This algorithm is used to design a suboptimal algorithm that has decreased computational requirements with only a small performance penalty.

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Citations
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Journal ArticleDOI

Brief paper: Multi-rate stochastic H∞ filtering for networked multi-sensor fusion

TL;DR: A UI observer is proposed where PDs are represented as zero-mean white input noises of the linear time-variant estimation error system, and the results on the existence of a stable observer are proposed.
Journal ArticleDOI

Bias estimation for asynchronous multi-rate multi-sensor fusion with unknown inputs

TL;DR: A two-stage fusion scheme is proposed to estimate the state, the UI and the UI-driven bias for asynchronous multi-sensor fusion and is designed via the average consensus fusion rule weighted by matrices.
Journal ArticleDOI

Multi-rate optimal state estimation

TL;DR: This article formulates a multi-rate linear minimum mean squared error (LMMSE) state estimation problem, which includes four rates as follows: the state updating rate in the model, the measurement sampling rate, the estimate updating rate and the estimate output rate.
Journal ArticleDOI

Event-Based Finite-Time Filtering for Multirate Systems With Fading Measurements

TL;DR: The addressed finite-time filtering problem of NMSs is recast as a convex optimization one that can be solved via the semidefinite program method.
Journal ArticleDOI

Model-reduced fault detection for multi-rate sensor fusion with unknown inputs

TL;DR: This work proposes the model-reduced fault detection (MRFD) problem for multi-rate sensor fusion subject to UIs and faults imposed on the actuator and sensors, and designs a fast and computation-effective FD scheme based on the reduced model.
References
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Journal ArticleDOI

Novel Method for Data Compression in Recursive INS Error Estimation

TL;DR: A new data compression method is presented which is applicable to systems whose observables are a linear combination of only a part of the system states, and the peculiar Kalman filter form of this case is used.
Journal ArticleDOI

Multistage linear estimation using partitioning

TL;DR: In this article, a two-stage estimator consisting of two consecutive Kalman filters is proposed to solve the linear estimation problem, and the interconnections between this estimator structure and the more familiar one-stage optimal Kalman filter are discussed.
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