Results 21 to 30 of about 425,572 (237)
Proceedings of the National Academy of Sciences, 2001 The Kalman Filter commonly employed by control engineers and other physical scientists has been successfully used in such diverse areas as the processing of signals in aerospace tracking and underwater sonar, and statistical quality control.
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An Indoor Positioning Method Based on UWB and Visual Fusion
Sensors, 2022 Continuous positioning and tracking of multi-pedestrian targets is a common concern for large indoor space security, emergency evacuation, location services, and other application areas.
Pingping Peng +5 more
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IEEE Transactions on Automatic Control, 2009 In this paper, we present a new nonlinear filter for high-dimensional state estimation, which we have named the cubature Kalman filter (CKF). The heart of the CKF is a spherical-radial cubature rule, which makes it possible to numerically compute multivariate moment integrals encountered in the nonlinear Bayesian filter. Specifically, we derive a third-
Ienkaran Arasaratnam, Simon Haykin 0001
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Robust Kalman Filtering Based on Chi-square Increment and Its Application
Remote Sensing, 2020 In Global Navigation Satellite System (GNSS) positioning, gross errors seriously limit the validity of Kalman filtering and make the final positioning solutions untrustworthy.
Bo Li +7 more
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Sensors, 2008 This paper proposes a new distributed Kalman filtering fusion with random state transition and measurement matrices, i.e., random parameter matrices Kalman filtering.
Donghua Wang +5 more
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An Alignment Method Based on KF-ASMUKF Hybrid Filtering for Ship’s SINS under Mooring Conditions
Sensors, 2021 To solve the problem that the ship’s strapdown inertial navigation system (SINS) alignment accuracy decreases with the increase of the nonlinear filtering state dimension under mooring conditions, a method based on Kalman filter (KF) and Adaptive scale ...
Pengchao Yao, Gongliu Yang, Xiafu Peng
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Kalman filtering as a performance monitoring technique for a propensity scorecard [PDF]
, 2011 Propensity scorecards allow forecasting, which bank customers would like to be granted new credits in the near future, through assessing their willingness to apply for new loans. Kalman filtering can help to monitor scorecard performance.
Bijak, Katarzyna
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A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation
Sensors, 2016 The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of ...
Chen Jiang, Shu-Bi Zhang, Qiu-Zhao Zhang
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A Federated Derivative Cubature Kalman Filter for IMU-UWB Indoor Positioning
Sensors, 2020 The inertial measurement unit and ultra-wide band signal (IMU-UWB) combined indoor positioning system has a nonlinear state equation and a linear measurement equation.
Chengyang He, Chao Tang, Chengpu Yu
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CoRR, 2021 The Kalman filter is a fundamental filtering algorithm that fuses noisy sensory data, a previous state estimate, and a dynamics model to produce a principled estimate of the current state. It assumes, and is optimal for, linear models and white Gaussian noise. Due to its relative simplicity and general effectiveness, the Kalman filter is widely used in
Beren Millidge +3 more
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