Results 1 to 10 of about 70,135 (188)
Optimally Distributed Kalman Filtering with Data-Driven Communication [PDF]
Sensors, 2018 For multisensor data fusion, distributed state estimation techniques that enable a local processing of sensor data are the means of choice in order to minimize storage and communication costs.
Katharina Dormann +2 more
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Adaptive Distributed Student’s T Extended Kalman Filter Employing Allan Variance for UWB Localization [PDF]
SensorsThis study proposes an adaptive distributed Student’s t extended Kalman filter (EKF) using Allan variance for ultrawide-band (UWB) localization. First of all, we model the state equation using the target’s position and velocity in east and north ...
Yanli Gao +6 more
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IEEE Access, 2021 With the rising number of applications for sensor networks comes a need for more accurate cooperative fusion algorithms. In this paper, a distributed and optimal state estimator is presented for implementation through a dynamically switching, yet ...
Matthew D. Howard, Zhihua Qu
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IEEE Access, 2021 We present an approach which combines the sample regenerating particle filter (SRGPF) and unequal weight ensemble Kalman filter (UwEnKF) to obtain a more accurate forecast for nonlinear dynamic systems.
Xiao Li, Ai Jie Cheng, Hai Xiang Lin
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Distributed receding horizon Kalman filter [PDF]
49th IEEE Conference on Decision and Control (CDC), 2010 In this paper a distributed version of the Kalman filter is proposed. In particular, the estimation problem is reduced to the optimization of a cost function that depends on the system dynamics and the latest output measurements and state estimates which is distributed among the local subsystems by means of dual decomposition.
Maestre J.M., Giselsson P., Rantzer A.
openaire +3 more sources
Applied Sciences, 2023 For nonlinear systems, both the cubature Kalman filter (CKF) and square-root cubature Kalman filter (SCKF) can get good estimation performance under Gaussian noise. However, the actual driving environment noise mostly has non-Gaussian properties, leading
Pingshu Ge +4 more
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Sensors, 2023 In the distributed information fusion of wireless sensor networks (WSNs), the filtering accuracy is commonly negatively correlated with energy consumption.
Chunxi Yang +3 more
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Distributed Kalman estimation with decoupled local filters [PDF]
Automatica, 2021 We study a distributed Kalman filtering problem in which a number of nodes cooperate without central coordination to estimate a common state based on local measurements and data received from neighbors. This is typically done by running a local filter at each node using information obtained through some procedure for fusing data across the network.
Marelli, Damian, Sui, Tianju, Fu, Minyue
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Joint Estimation and Localization in Sensor Networks [PDF]
, 2014 This paper addresses the problem of collaborative tracking of dynamic targets in wireless sensor networks. A novel distributed linear estimator, which is a version of a distributed Kalman filter, is derived.
Atanasov, Nikolay +4 more
core +5 more sources
Electric Vehicle State Parameter Estimation Based on DICI-GFCKF
IEEE Access, 2022 To improve the estimation accuracy of the state parameters of distributed electric vehicles, a double inverse covariance intersection generalized fifth-order cubature Kalman filter (DICI-GFCKF) es-timation algorithm is proposed.
Zhang Rongyun +5 more
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