Square Root Cubature Information Filter

Chandra, Kumar Pakki Bharani; Gu, Da‐Wei; Postlethwaite, Ian

doi:10.1109/jsen.2012.2226441

Cited by 118 publications

(95 citation statements)

References 30 publications

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“…In addition, SCKF is an analytic Gaussian approximate filter based on QR matrix decomposition, which is outstanding in nonlinear tracking problem. The detailed derivation of the two algorithms can be referenced literature [5] and [14].…”

Section: Imm-sckf Algorithm Designmentioning

confidence: 99%

“…The probability of the model is updated according to equation (14). (5) Interactive output By combining the output results ˆj kk x and j kk P of each filter, the input of the rth filter and the corresponding covariance can be obtained according to equations (15) and (16).…”

Section: Figure 2 Structure Of Imm-sckf (Tda Means Triangular Decompmentioning

confidence: 99%

“…Both the motion model and the measurement model of the missile have very strong nonlinearity, which leads to the problem that the covariance matrix in the filtering algorithm appears to be non-normal and asymmetric. To solve this problem, the paper [14] proposes a Square-root Cubature Kalman Filter based on QR matrix decomposition. Therefore, this paper introduces the SCKF into the IMM frame and then tracks the maneuvering target by the angle measurement information of the space-based platform.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Marine Maneuvering Target Tracking Based on Space-Based Bearing-Only Measurement

Li¹,

Cao²,

Lin³

et al. 2018

dtcse

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Based on monitoring and tracking the maritime maneuvering target, the passive tracking system of space-based bearing-only measurement is constructed. Due to the strong maneuverability of target and strong nonlinearity of tracking system, an algorithm based on Bayes estimation is introduced in the interacting multiple model (IMM). By deriving the equivalent description of IMM's covariance matrix in SCKF (Square-root Cubature Kalman Filter), this paper solves the problem of mismatch between the input and output of the two algorithms, and a new algorithm flowchart is proposed. The simulation results show that the proposed algorithm can adapt to the maneuverability quickly and estimate the probability of target motion model accurately. To be more accurately, the average position and speed tracking accuracy can reach 53.79m and 1.54 / ms respectively, which verifies the effectiveness of the proposed algorithm.

show abstract

Section: Imm-sckf Algorithm Designmentioning

confidence: 99%

Section: Figure 2 Structure Of Imm-sckf (Tda Means Triangular Decompmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Marine Maneuvering Target Tracking Based on Space-Based Bearing-Only Measurement

Li¹,

Cao²,

Lin³

et al. 2018

dtcse

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show abstract

“…Unlike Local Map Sequencing strategy to join maps sequentially [11], D&C scheme joins local maps in a binary-tree hierarchical fashion, as shown in Figure 2 …”

Section: The Divide and Conquer Submap Joining Schemementioning

confidence: 99%

An Innovative Combined Filter SLAM Algorithm for Mobile Robots in Large-Scale Environment

Cai¹,

Zhong²,

Zhang³

2017

IJCA

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show abstract

“…UKF is a derivationfree filter, which can commendably overcome the defects of EKF. However, there exist some tunable parameters in sigma points, the selection of which lacks rigorous mathematical basis, and the negative weight on the center point may reduce the numerical stability for high-dimensional system [8,9].…”

Section: Introductionmentioning

confidence: 99%

Simplex Cubature Kalman‐Consensus Filter for Distributed Space Target Tracking

Yang

Ding

et al. 2018

Wireless Communications and Mobile Computing

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A simplex cubature Kalman-consensus filter, which is suitable for distributed space target tracking using multiple radars, is proposed to improve the target tracking accuracy. The detailed orbital dynamics model and radar measurement model are given as the system filtering models. The intractable nonlinear Gaussian weighted integral in the filter is decomposed into the spherical integral and radial integral, which are calculated using the spherical simplex rule and the second-order Gauss-Laguerre quadrature rule, respectively. In this way, a new simplex cubature rule is derived. By means of the statistical linear regression method, the posterior mean, covariance, and the transmitted messages in the extended Kalman-consensus filter are approximated using the deduced simplex cubature rule, which results in the proposed simplex cubature Kalman-consensus filter. No data fusion center exists in the filter, and each radar only needs to exchange the information with its neighbors to reach a consensus estimate. The simulation results show that the proposed filter can achieve more accurate results compared with the cubature Kalman-consensus filter.

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Square Root Cubature Information Filter

Cited by 118 publications

References 30 publications

Marine Maneuvering Target Tracking Based on Space-Based Bearing-Only Measurement

Marine Maneuvering Target Tracking Based on Space-Based Bearing-Only Measurement

An Innovative Combined Filter SLAM Algorithm for Mobile Robots in Large-Scale Environment

Simplex Cubature Kalman‐Consensus Filter for Distributed Space Target Tracking

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