Results 121 to 130 of about 48,416 (251)
Kalman Filtering of Distributed Time Series
, 2017 7 pages, 9 figures, International Conference on Control Systems and Computer Science ...
Stefanoiu, Dan, Culita, Janetta
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Quarterly Journal of the Royal Meteorological Society, EarlyView.The study evaluates five factors affecting the assimilation of surface‐sensitive Advanced Microwave Sounding Unit‐A (AMSU‐A) radiances over land, including the simultaneous estimation of surface emissivity and the standard set of state variables, to improve numerical weather prediction (NWP) at Environment and Climate Change Canada (ECCC).
Zheng Qi Wang +4 more
wiley +1 more source
How consistently do ensemble prediction systems represent the growth of atmospheric uncertainty?
Quarterly Journal of the Royal Meteorological Society, EarlyView.Spread‐based diagnostics calculated for 12 ensemble prediction systems are compared to understand the consistency with which they represent atmospheric uncertainty growth. Good correlation between all these systems is found in the extratropics for a lead time range from 48 hr to between 96 hr and 192 hr.
Douglas Wood +3 more
wiley +1 more source
Optimally (Distributional-)Robust Kalman Filtering
, 2010 We present optimality results for robust Kalman filtering where robustness is understood in a distributional sense, i.e.; we enlarge the distribution assumptions made in the ideal model by suitable neighborhoods. This allows for outliers which in our context may be system-endogenous or -exogenous, which induces the somewhat conflicting goals of ...
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Distributed Widely Linear Complex Kalman Filtering
, 2013 We introduce cooperative sequential state space estimation in the domain of augmented complex statistics, whereby nodes in a network collaborate locally to estimate noncircular complex signals. For rigour, a distributed augmented (widely linear) complex Kalman filter (D-ACKF) suited to the generality of complex signals is introduced, allowing for ...
Dini, Dahir H. +2 more
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A structurally localized ensemble Kalman filtering approach
Quarterly Journal of the Royal Meteorological Society, EarlyView.We derive an inherently localized ensemble Kalman filtering (EnKF) approach, avoiding the need for any auxiliary localization technique. The idea is to first use the variational Bayesian optimization to approximate the (continuous) state analysis probability density function (pdf) by a product of independent marginal pdfs corresponding to small ...
Boujemaa Ait‐El‐Fquih +1 more
wiley +1 more source
An Efficient Ceiling-view SLAM Using Relational Constraints Between Landmarks
International Journal of Advanced Robotic Systems, 2014 In this paper, we present a new indoor 'simultaneous localization and mapping‘ (SLAM) technique based on an upward-looking ceiling camera. Adapted from our previous work [ 17 ], the proposed method employs sparsely-distributed line and point landmarks in
Hyukdoo Choi, Ryunseok Kim, Euntai Kim
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Quarterly Journal of the Royal Meteorological Society, EarlyView.We document for the first time how the assimilation of CS2SMOS observations improves the model representation of Arctic sea‐ice thickness (SIT) and its variability: biases are reduced (top row), while excessive variability in the Beaufort Sea and lack of variability in the ice pack are both corrected (bottom row).
Jiping Xie +3 more
wiley +1 more source
Initial State Privacy of Nonlinear Systems on Riemannian Manifolds
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT In this paper, we investigate initial state privacy protection for discrete‐time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances.
Le Liu, Yu Kawano, Antai Xie, Ming Cao
wiley +1 more source
Survey on AI‐Enabled Computer Vision Technologies and Applications for Space Robotic Missions
Journal of Field Robotics, EarlyView.ABSTRACT This survey provides a comprehensive overview of recent advancements and challenges in Artificial Intelligence (AI)‐enabled computer vision (CV) techniques for space robotic missions, spanning critical phases such as Entry, Descent, and Landing (EDL), orbital operations, and planetary surface exploration.
Maciej Quoos +6 more
wiley +1 more source