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Highly Cited

2009

Highly Cited

2009

In this paper, we present a new nonlinear filter for high-dimensional state estimation, which we have named the cubature Kalman… Expand

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Highly Cited

2007

Highly Cited

2007

In this paper, we introduce three novel distributed Kalman filtering (DKF) algorithms for sensor networks. The first algorithm is… Expand

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Highly Cited

2005

Highly Cited

2005

The problem of distributed Kalman filtering (DKF) for sensor networks is one of the most fundamental distributed estimation… Expand

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Highly Cited

2004

Highly Cited

2004

Motivated by navigation and tracking applications within sensor networks, we consider the problem of performing Kalman filtering… Expand

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Highly Cited

2003

Highly Cited

2003

3 A deterministic construction of the Kalman filter 7 3.1 The quadratic criterion to be minimized in the absence of process… Expand

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Highly Cited

2003

Highly Cited

2003

Motivated by our experience in building sensor networks for navigation as part of the Networked Embedded Systems Technology (NEST… Expand

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Highly Cited

1992

Highly Cited

1992

Probability and Random Variables Mathematical Description of Random Signals Response of Linear Systems to Random Inputs Wiener… Expand

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Highly Cited

1989

Highly Cited

1989

Using known camera motion to estimate depth from image sequences is an important problem in robot vision. Many applications of… Expand

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Highly Cited

1987

Highly Cited

1987

"Kalman Filtering with Real-Time Applications" presents a thorough discussion of the mathematical theory and computational… Expand

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Highly Cited

1970

Highly Cited

1970

A Kalman filter requires an exact knowledge of the process noise covariance matrix Q and the measurement noise covariance matrix… Expand

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