Cubature rule-based distributed optimal fusion with identification and prediction of kinematic model error for integrated UAV navigation

Gao, Bingbing; Hu, Gaoge; Zhong, Yongmin; Zhu, Xinhe

doi:10.1016/j.ast.2020.106447

Cited by 62 publications

(21 citation statements)

References 34 publications

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“…From (16), a new set of cubature points is generated by…”

Section: Measurement Updatementioning

confidence: 99%

“…WAC based distributed unscented Kalman filtering (DUKF) 11 was designed for nonlinear state estimation in DWSN, but the nonpositive problem of covariance matrix in high-dimensional systems is still an unsolved problem for DUKF. [14][15][16] To overcome the drawback of DUKF, distributed cubature information filtering (DCIF) was developed based on WAC. 6,12 As the algebraic equivalent form of cubature Kalman filtering, cubature information filtering can provide more precise and stable estimations than most of Gaussian filters.…”

Section: Introductionmentioning

confidence: 99%

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Distributed adaptive cubature information filtering for bounded noise system in wireless sensor networks

Zhang

Gao

Xia

et al. 2021

Intl J Robust & Nonlinear

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This article is concerned with the nonlinear state estimation for the multisenor networked system with uncertain bounded noise. Traditional distributed methods only pay attention to the information fusion of state estimations, but neglect the fusion of noise statistics. The difference of noise statistics among sensor nodes usually affects the precision of state estimation in wireless sensor networks, especially for the distributed state estimation. In this article, in order to improve the accuracy of noise statistic estimations, a distributed noise statistic estimator is derived based on covariance intersection criterion and modified Sage-Husa maximum posterior. Then, distributed adaptive cubature information filtering (DACIF) is founded based on weighted average consensus to obtain accurate state estimation. Two-step information fusion, including the information fusion of state estimations and noise statistics, is derived to enhance the precision of state estimations. Meanwhile, a novel weighted rule is devised based on the state and measurement innovation vectors to improve the accuracy of distribution information fusion. Next, the estimation errors of DACIF are proved to be bounded in mean square. Simulations and semisimulation experiments are conducted to verify the effectiveness of the proposed algorithm.

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“…From (16), a new set of cubature points is generated by…”

Section: Measurement Updatementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed adaptive cubature information filtering for bounded noise system in wireless sensor networks

Zhang

Gao

Xia

et al. 2021

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

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“…Arroyo-Marioli et al used KF to estimate the basic reproduction number of COVID-19 based on a linearized form of the SIR model [ 2 ]. Nevertheless, RLS and KF can be applied to linear systems only [ 12 ], while the existing epidemiological models for COVID-19 forecast are nonlinear. The constrained least-squares (CLS) [ 13 ] and Markov chain Monte Carlo (MCMC) [ 14 ] are the commonly used estimation method for nonlinear epidemiological models.…”

Section: Introductionmentioning

confidence: 99%

Extended Kalman filter based on stochastic epidemiological model for COVID-19 modelling

Zhu

Gao

Zhong

et al. 2021

Computers in Biology and Medicine

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This paper presents a new stochastic-based method for modelling and analysis of COVID-19 spread. A new deterministic Susceptible, Exposed, Infectious, Recovered (Re-infected) and Deceased-based Social Distancing model, named SEIR(R)D-SD, is proposed by introducing the re-infection rate and social distancing factor into the traditional SEIRD (Susceptible, Exposed, Infectious, Recovered and Deceased) model to account for the effects of re-infection and social distancing on COVID-19 spread. The deterministic SEIRD(R)D-SD model is further converted into the stochastic form to account for uncertainties involved in COVID-19 spread. Based on this, an extended Kalman filter (EKF) is developed based on the stochastic SEIR(R)D-SD model to simultaneously estimate both model parameters and transmission state of COVID-19 spread. Simulation results and comparison analyses demonstrate that the proposed method can effectively account for the re-infection and social distancing as well as uncertain effects on COVID-19 spread, leading to improved accuracy for prediction of COVID-19 spread.

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“…The optimal estimation of all parameters and fault-tolerant processing of the system state are carried out. In [17], a distributed optimal fusion method combining the volume rules of motion model error identification and prediction is proposed to solve the nonlinear integration problem of MIMU/GNSS/CNS systems. [18] proposed a robust fault-tolerant federated filter for SINS/GNSS/CNS/DVL integrated navigation.…”

Section: Introductionmentioning

confidence: 99%

Navigation Switching Strategy‐Based SINS/GPS/ADS/DVL Fault‐Tolerant Integrated Navigation System

Zhang

Hongjie³

2021

Journal of Sensors

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Considering the conventional federated filtering-based fault-tolerant integrated navigation system is difficult to be implemented by serial data processing circuits, this paper presents navigation switching strategy-based SINS/GPS/ADS/DVL fault-tolerant integrated navigation system to guarantee the reliability of integrated navigation system under sensor faults. When sensor failure appears, SINS and fault-free sensors are selected successively to form an integrated navigation system, such that reliable navigation parameters can be obtained. The simulation tests are implemented to verify that the SINS/GPS/ADS/DVL integrated navigation system can provide reliable navigation parameters when ADS and DVL are disabled.

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Cubature rule-based distributed optimal fusion with identification and prediction of kinematic model error for integrated UAV navigation

Cited by 62 publications

References 34 publications

Distributed adaptive cubature information filtering for bounded noise system in wireless sensor networks

Distributed adaptive cubature information filtering for bounded noise system in wireless sensor networks

Extended Kalman filter based on stochastic epidemiological model for COVID-19 modelling

Navigation Switching Strategy‐Based SINS/GPS/ADS/DVL Fault‐Tolerant Integrated Navigation System

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