Results 1 to 10 of about 12,239 (165)
Measurement Noise Recommendation for Efficient Kalman Filtering over a Large Amount of Sensor Data
Sensors, 2019 To effectively maintain and analyze a large amount of real-time sensor data, one often uses a filtering technique that reflects characteristics of original data well.
Sebin Park +3 more
doaj +3 more sources
Advancements in Buoy Wave Data Processing through the Application of the Sage–Husa Adaptive Kalman Filtering Algorithm [PDF]
Sensors, 2023 In this paper, we propose a combined filtering method rooted in the application of the Sage–Husa Adaptive Kalman filtering, designed specifically to process wave sensor data.
Sha Jiang, Yonghua Chen, Qingkui Liu
doaj +2 more sources
Kalman filtering to reduce measurement noise of sample entropy: An electroencephalographic study. [PDF]
PLoS ONEIn the analysis of electroencephalography (EEG), entropy can be used to quantify the rate of generation of new information. Entropy has long been known to suffer from variance that arises from its calculation.
Nan Zhang +6 more
doaj +2 more sources
Kalman Filtering With Intermittent Observations
IEEE Transactions on Automatic Control, 2004 Motivated by navigation and tracking applications within sensor networks, we consider the problem of performing Kalman filtering with intermittent observations. When data travel along unreliable communication channels in a large, wireless, multihop sensor network, the effect of communication delays and loss of information in the control loop cannot be ...
Bruno Sinopoli +2 more
exaly +2 more sources
The Optimal Distributed Kalman Filtering Fusion With Linear Equality Constraint
IEEE Access, 2021 In this paper, the optimal distributed Kalman filtering fusion with linear equality constraint (LEC) is proposed. When the Kalman filter subject to LEC is applied in state estimation of distributed linear dynamic system, all local error covariance ...
Hua Li, Shengli Zhao
doaj +1 more source
Two-Stage Cubature Kalman Filtering Based on T-Transform and Its Application
Complexity, 2021 According to the actual application system model which has bias, this paper analyzes the shortage of the conventional augmented algorithm, the two-stage cubature Kalman filtering algorithm, which is presented on the basis of a two-stage nonlinear ...
Lu Zhang +3 more
doaj +1 more source
The Salted Kalman Filter: Kalman filtering on hybrid dynamical systems
Automatica, 2021 Many state estimation and control algorithms require knowledge of how probability distributions propagate through dynamical systems. However, despite hybrid dynamical systems becoming increasingly important in many fields, there has been little work on utilizing the knowledge of how probability distributions map through hybrid transitions.
Nathan J. Kong +3 more
openaire +2 more sources
Inverse problem of incomplete boundaries and unknown parameters in two-dimensional Poisson equation
Nantong Daxue xuebao. Ziran kexue ban, 2022 The inverse problem of Poisson equation with incomplete boundary or unknown parameters have been solved by using the method of fundamental solutions (MFS) and Kalman filtering technique.
WANG Yue; JIANG Quan
doaj +1 more source
Physica D: Nonlinear Phenomena, 2001 The Kalman filter combines forecasts and new observations to obtain an estimation which is optimal in the sense of a minimum average quadratic error. The Kalman filter has two main restrictions: (i) the dynamical system is assumed linear and (ii) forecasting errors and observational noises are taken Gaussian.
Sornette, Didier, Ide, Kayo
openaire +3 more sources
IEEE Signal Processing Letters, 2021 In this paper, a new filter in the nonlinear Kalman filtering framework is proposed. The new filter is referred to as the lattice Kalman filter (LKF) and is based on a class of quasi-Monte Carlo (QMC) methods known as lattice rules. The proposed LKF method uses the Korobov type lattice rule to deterministically generate sample points that are randomly ...
Abolfazl Rahimnejad +2 more
openaire +2 more sources