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CDC
2010
IEEE
120views Control Systems» more  CDC 2010»
8 years 9 months ago
Statistical properties of the error covariance in a Kalman filter with random measurement losses
In this paper we study statistical properties of the error covariance matrix of a Kalman filter, when it is subject to random measurement losses. We introduce a sequence of tighter...
Eduardo Rohr, Damián Marelli, Minyue Fu
CDC
2010
IEEE
144views Control Systems» more  CDC 2010»
8 years 9 months ago
Optimal UAV coordination for target tracking using dynamic programming
This work focuses on optimal routing for two camera-equipped UAVs cooperatively tracking a single target moving on the ground. The UAVs are small fixed-wing aircraft cruising at a ...
Steven A. P. Quintero, Francesco Papi, Daniel J. K...
CDC
2010
IEEE
139views Control Systems» more  CDC 2010»
8 years 9 months ago
An adaptive-covariance-rank algorithm for the unscented Kalman filter
Abstract-- The Unscented Kalman Filter (UKF) is a nonlinear estimator that is particularly well suited for complex nonlinear systems. In the UKF, the error covariance is estimated ...
Lauren E. Padilla, Clarence W. Rowley
PROCEDIA
2010
87views more  PROCEDIA 2010»
9 years 25 days ago
Forecast sensitivity to the observation error covariance in variational data assimilation
The development of the adjoint of the forecast model and of the adjoint of the data assimilation system (adjoint-DAS) make feasible the evaluation of the derivative-based forecast...
Dacian N. Daescu
AUTOMATICA
2008
75views more  AUTOMATICA 2008»
9 years 2 months ago
Probabilistic performance of state estimation across a lossy network
We consider a discrete time state estimation problem over a packet-based network. In each discrete time step, a measurement packet is sent across a lossy network to an estimator u...
Michael Epstein, Ling Shi, Abhishek Tiwari, Richar...
ICASSP
2009
IEEE
9 years 9 months ago
Particle filtering for Quantized Innovations
In this paper, we re-examine the recently proposed distributed state estimators based on quantized innovations. It is widely believed that the error covariance of the Quantized In...
Ravi Teja Sukhavasi, Babak Hassibi
SC
2009
ACM
9 years 9 months ago
Many task computing for multidisciplinary ocean sciences: real-time uncertainty prediction and data assimilation
Error Subspace Statistical Estimation (ESSE), an uncertainty prediction and data assimilation methodology employed for real-time ocean forecasts, is based on a characterization an...
Constantinos Evangelinos, Pierre F. J. Lermusiaux,...
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