Maneuvering Target Tracking Algorithm Based on Interacting Multiple Models

Aiming at improving the accuracy and quick response of the filter in nonlinear maneuvering target tracking problems, the Interacting Multiple Models Cubature Information Filter (IMMCIF) is proposed. In IMMCIF, the Cubature Information Filter (CIF) is brought into Interacting Multiple Model (IMM), which can not only improve the accuracy but also enhance the quick response of the filter. CIF is a multisensor nonlinear filtering algorithm; it evaluates the information vector and information matrix rather than state vector and covariance, which can reduce the error of nonlinear filtering algorithm. IMM disposes all the models simultaneously through Markov Chain, which can enhance the quick response of the filter. Finally, the simulation results show that the proposed filter exhibits fast and smooth switching when disposing different maneuver models; it performs better than the IMMCKF and IMMUKF on tracking accuracy.

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Distributed hybrid consensus–based square-root cubature quadrature information filter and its application to maneuvering target tracking

International Journal of Distributed Sensor Networks ◽

10.1177/1550147719895952 ◽

2019 ◽

Vol 15 (12) ◽

pp. 155014771989595

Author(s):

Jun Liu ◽

Yu Liu ◽

Kai Dong ◽

Ziran Ding ◽

You He ◽

...

Keyword(s):

Target Tracking ◽

Nonlinear Filtering ◽

Computational Cost ◽

Quadrature Rule ◽

Square Root ◽

Maneuvering Target Tracking ◽

Maneuvering Target ◽

Matrix Operations ◽

Information Filter ◽

Update Strategy

To handle nonlinear filtering problems with networked sensors in a distributed manner, a novel distributed hybrid consensus–based square-root cubature quadrature information filter is proposed. The proposed hybrid consensus–based square-root cubature quadrature information filter exploits fifth-order spherical simplex-radial quadrature rule to tackle system nonlinearities and incorporates a novel measurement update strategy into the hybrid consensus filtering framework, which takes the predicted measurement error into account and hence produces more accurate estimates. In addition, the proposed hybrid consensus–based square-root cubature quadrature information filter inherits the complementary positive features of both consensus on information and consensus on measurements methods and avoids sensitive matrix operations such as square-root decompositions and inversion of covariances, which is beneficial for numerical stability. Stability analysis with respect to consensus, convergence, and consistency for the proposed hybrid consensus–based square-root cubature quadrature information filter is also developed. The effectiveness of the proposed hybrid consensus–based square-root cubature quadrature information filter is validated through a maneuvering target tracking scenario. The simulation results show that the proposed hybrid consensus–based square-root cubature quadrature information filter outperforms the existing algorithms at the expense of a slight increase in computational cost.

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A Filtering Algorithm for Maneuvering Target Tracking Based on Smoothing Spline Fitting

Abstract and Applied Analysis ◽

10.1155/2014/127643 ◽

2014 ◽

Vol 2014 ◽

pp. 1-6 ◽

Cited By ~ 5

Author(s):

Yunfeng Liu ◽

Jidong Suo ◽

Hamid Reza Karimi ◽

Xiaoming Liu

Keyword(s):

Target Tracking ◽

Curve Fitting ◽

Multiple Model ◽

Maneuvering Target Tracking ◽

Filtering Algorithm ◽

Maneuvering Target ◽

Spline Fitting ◽

Interactive Multiple Model ◽

Kalman Filter Algorithm ◽

The Common

Maneuvering target tracking is a challenge. Target’s sudden speed or direction changing would make the common filtering tracker divergence. To improve the accuracy of maneuvering target tracking, we propose a tracking algorithm based on spline fitting. Curve fitting, based on historical point trace, reflects the mobility information. The innovation of this paper is assuming that there is no dynamic motion model, and prediction is only based on the curve fitting over the measured data. Monte Carlo simulation results show that, when sea targets are maneuvering, the proposed algorithm has better accuracy than the conventional Kalman filter algorithm and the interactive multiple model filtering algorithm, maintaining simple structure and small amount of storage.

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