Distributed event‐triggered cubature information filtering based on weighted average consensus

Tan, Qingke; Dong, Xiwang; Li, Qingdong; Zhang, Ren

doi:10.1049/iet-cta.2017.0575

Cited by 39 publications

(18 citation statements)

References 31 publications

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“…Based on the CKF, the distributed cubature information filtering method has been designed in Q. Tan et al (2017) for nonlinear systems with event-triggered protocol addressed by using weighted average consensus method, where the amount of data transmission has been reduced by employing the communication scheme and consensus method. In the light of the results in Q.…”

Section: Multi-sensor Distributed Fusion Filtering For Nonlinear Nssmentioning

confidence: 99%

“…In the light of the results in Q. Tan et al (2017), an improved distributed cubature information filtering approach has been proposed in J. for nonlinear systems with randomly occurring incomplete measurements based on the consensus method, where a new fusion weight method has been designed and the convergence of the fusion algorithm has been achieved. In Q. Ge et al (2016), a series of multisensor information fusion algorithms has been given for a class of nonlinear systems based on cubature squareroot information filter approach, which include the augmented measurements fusion, measurements weighted fusion, sequential filtering fusion and distributed fusion.…”

Section: Multi-sensor Distributed Fusion Filtering For Nonlinear Nssmentioning

confidence: 99%

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A survey on distributed filtering, estimation and fusion for nonlinear systems with communication constraints: new advances and prospects

Yang

2020

Systems Science & Control Engineering

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In this paper, some recent results on the distributed filtering, estimation and fusion algorithms for nonlinear systems with communication constraints are reviewed. First, some network-induced phenomena and communication protocols in the networked environment are recalled. Second, the recent advances of distributed fusion algorithms for nonlinear systems are discussed, which include distributed fusion extended Kalman filtering, distributed fusion unscented Kalman filtering, distributed fusion cubature Kalman filtering, distributed fusion particle filtering. Subsequently, some new distributed filtering, estimation and fusion algorithms for nonlinear systems subject to communication constraints are summarized and discussed. Finally, conclusion is given and several possible research topics on distributed filtering, estimation and fusion for nonlinear networked systems are pointed out.

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Section: Multi-sensor Distributed Fusion Filtering For Nonlinear Nssmentioning

confidence: 99%

Section: Multi-sensor Distributed Fusion Filtering For Nonlinear Nssmentioning

confidence: 99%

A survey on distributed filtering, estimation and fusion for nonlinear systems with communication constraints: new advances and prospects

Yang

2020

Systems Science & Control Engineering

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“…A modified MTCIF is designed for nonlinear system model and employed in local node for multi-target tracking in this section. Further, since the prior information of measurement noise is unknown or inaccurate, the modified SHMP [20] based noise estimator is designed for MTCIF to improve the precision of state estimation in consideration of the stability of NSE.…”

Section: Based On the Doa Measurement Setẑmentioning

confidence: 99%

An Advanced Cubature Information Filtering for Indoor Multiple Wideband Source Tracking With a Distributed Noise Statistics Estimator

et al. 2019

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Acoustic vector sensor (AVS) is an effective tool to tracking acoustic sources. However, for the problem of tracking multiple wideband sources using distributed AVS array (DAVS), there are still unsolved issues which include measurements-to-targets association and targets tracking under incorrect or unknown statistics of measurement noise. Joint probabilistic data association (JPDA) is an effective algorithm to solve data association between measurements and targets and JPDA based cubature information filter (MTCIF) is designed for nonlinear system. Meanwhile, noise statistics estimator (NSE) based on modified Sage-Husa maximum posterior (SHMP) is constructed to cope with incorrect or unknown statistics of measurement noise. Then, a two-step distributed information fusion based on weighted average consensus (WAC) is built for DAVS to improve the stability and accuracy of state estimator and NSE. Numerical simulations demonstrate the effectiveness of the proposed algorithms.INDEX TERMS Acoustic vector sensor, cubature information filter, joint probabilistic data association, noise statistics estimator, weighted average consensus.

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“…[29] proposed a distributed event‐triggered cubature information filter based on weighted average consensus for mobile sensor networks with non‐linear systems and a large amount of data transfer. In [29], each sensor was triggered if the difference between the most recent transmitted estimate and the current estimate exceeded a threshold, and energy penalty was not considered. Muehlebach and Trimpe [30] considered a system of different agents measuring the plant and exchanging data with each other and proposed a local event‐triggering protocol.…”

Section: Introductionmentioning

confidence: 99%

Distributed energy‐efficient target tracking algorithm based on event‐triggered strategy for sensor networks

Zhang

et al. 2019

IET Control Theory & Applications

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Distributed event‐triggered cubature information filtering based on weighted average consensus

Cited by 39 publications

References 31 publications

A survey on distributed filtering, estimation and fusion for nonlinear systems with communication constraints: new advances and prospects

A survey on distributed filtering, estimation and fusion for nonlinear systems with communication constraints: new advances and prospects

An Advanced Cubature Information Filtering for Indoor Multiple Wideband Source Tracking With a Distributed Noise Statistics Estimator

Distributed energy‐efficient target tracking algorithm based on event‐triggered strategy for sensor networks

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