Distributed High-Degree Cubature Information Filter With Embedded Hybrid Consensus

Li, Jun; Liu, Yu; Dong, Kai; Ding, Ziran; He, Yong

doi:10.1109/access.2019.2933565

Cited by 3 publications

(2 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The ''innovations'' consensus approach is extended in Das and Moura, 10 where the optimal gain is considered. A few of nonlinear filtering methods based on consensus strategy were introduced in Li et al, 11 Liu and Tian, 12 and Chen et al 13 In Chen et al 14 and Liu et al, 15 the high-dimensional distributed state estimation problem was investigated for a class of sensor networks within the cubature Kalman filtering framework. Recently, the problem of distributed filtering has been studied for a class of uncertain systems with uncertain noise variances.…”

Section: Introductionmentioning

confidence: 99%

Distributed filtering in sensor networks based on linear minimum mean square error criterion with limited sensing range

Shao

2022

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

One of the fundamental problems in sensor networks is to estimate and track the target states of interest that evolve in the sensing field. Distributed filtering is an effective tool to deal with state estimation in which each sensor only communicates information with its neighbors in sensor networks without the requirement of a fusion center. However, in the majority of the existing distributed filters, it is assumed that typically all sensors possess unlimited field of view to observe the target states. This is quite restrictive since practical sensors have limited sensing range. In this article, we consider distributed filtering based on linear minimum mean square error criterion in sensor networks with limited sensing range. To achieve the optimal filter and consensus, two types of strategies based on linear minimum mean square error criterion are proposed, that is, linear minimum mean square error filter based on measurement and linear minimum mean square error filter based on estimate, according to the difference of the neighbor sensor information received by the sensor. In linear minimum mean square error filter based on measurement, the sensor node collects measurement from its neighbors, whereas in linear minimum mean square error filter based on estimate, the sensor node collects estimate from its neighbors. The stability and computational complexity of linear minimum mean square error filter are analyzed. Numerical experimental results further verify the effectiveness of the proposed methods.

show abstract

Section: Introductionmentioning

confidence: 99%

Distributed filtering in sensor networks based on linear minimum mean square error criterion with limited sensing range

Shao

2022

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

show abstract

“…However, the third-degree SCR is not enough accurate, then the spherical integral and radial integral of arbitrary degree are derived in [14], which introduces highdegree SCR (HSCR). A distributed high-degree cubature information filter is designed to solve the problem of distributed nonlinear state estimation in sensor networks [15]. Two-stage high-degree cubature information filter is proposed for the nonlinear system with the unknown random bias in order to estimate the high-dimensional state and centralized process the measurement values [16].…”

Section: Introductionmentioning

confidence: 99%

A New Approach for Nonlinear Transformation of Means and Covariances in Direct Statistical Analysis of Nonlinear Systems

Fan

et al. 2021

IEEE Access

View full text Add to dashboard Cite

Covariance analysis describing function technique is a conventional method to solve the performance analysis of the nonlinear missile guidance system. Aiming at the faultiness of covariance analysis describing function technique and its improved method, this paper proposes a new method to solve the mean and covariance transfer issue by using the high-degree spherical-radial cubature rule. In terms of simulation models, the nonlinear missile guidance system contains the saturation link to limit the lateral acceleration command and the initial heading error is introduced. In addition, the zero-mean target evasive maneuver with exponentially-decaying autocorrelation function is chosen as the input of the missile guidance system. Furthermore, compared with the existing methods, the proposed method has higher computational efficiency, accuracy and better applicability in high-dimensional nonlinear systems by theoretical derivation and simulation results from the mean and covariance values of relative lateral separation. Finally, the presented analysis method can be used as a general method for the design and statistical analysis of multidimensional nonlinear systems.

show abstract

A Novel Distributed Cubature Kalman Filter and Its Application to Target Tracking

Liu

Wang

et al. 2021

2021 IEEE International Conference on Unmanned Systems (ICUS)

View full text Add to dashboard Cite

Distributed High-Degree Cubature Information Filter With Embedded Hybrid Consensus

Cited by 3 publications

References 42 publications

Distributed filtering in sensor networks based on linear minimum mean square error criterion with limited sensing range

Distributed filtering in sensor networks based on linear minimum mean square error criterion with limited sensing range

A New Approach for Nonlinear Transformation of Means and Covariances in Direct Statistical Analysis of Nonlinear Systems

A Novel Distributed Cubature Kalman Filter and Its Application to Target Tracking

Contact Info

Product

Resources

About