Asymmetrical Gating with Application on Maneuvering Target Tracking

A new asymmetrical gate with application in target tracking is proposed. Proposed gate has asymmetric shape that has large probability of target detection in the gate and has more advantages compared with elliptical gate. The gate is defined as the region in which the tracked target is expected to exist and just observation vectors in the gate are used as target detection. An analytical method to compute optimal size of gate is proposed and recursive estimation of asymmetric parameters of gate are studied. Comparison between proposed gate and conventional elliptical gate showed the efficiency of the proposed method in maneuvering target tracking applications and simulation results showed the proficiency of the proposed method.

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Maneuvering Target Tracking Based on Radar/ESM Sensors

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.713-715.672 ◽

2015 ◽

Vol 713-715 ◽

pp. 672-675 ◽

Cited By ~ 1

Author(s):

Xing Xiu Li ◽

Pan Long Wu

Keyword(s):

Dynamic System ◽

Target Tracking ◽

Interacting Multiple Model ◽

Multiple Model ◽

Maneuvering Target Tracking ◽

Heterogeneous Sensors ◽

System Models ◽

Maneuvering Target ◽

Blue Filter ◽

Simulation Results

A novel interacting multiple model based on BLUE filter (IMM-BLUE) for tracking a maneuvering target using radar/ESM heterogeneous sensors is presented in this paper. Under the architecture of the proposed algorithm, the interacting multiple model (IMM) deals with the model switching, while the BLUE filter accounts for non-linearity in the dynamic system models. The simulation results show that the presented IMM-BLUE has higher tracking precision than the IMM-DCM, and IMM-EKF.

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Maneuvering Target Tracking Algorithm Based on Particle PHD Filtering

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.989-994.2212 ◽

2014 ◽

Vol 989-994 ◽

pp. 2212-2215

Author(s):

Song Gao ◽

Chao Bo Chen ◽

Qian Gong

Keyword(s):

Particle Filter ◽

Target Tracking ◽

Tracking Accuracy ◽

Maneuvering Target Tracking ◽

Probability Hypothesis Density ◽

Filtering Algorithm ◽

Maneuvering Target ◽

Maneuvering Targets ◽

The Status ◽

Simulation Results

As for the problem of maneuvering target tracking in the clutter environment, this paper combines IMM with PHD and realizes it through approach of particle filter. This algorithm avoids the troublesome problem of data association, and takes advantage of probability hypothesis density (PHD) filter in tracking maneuvering targets and interacting multi-model (IMM) algorithm in the field of model switching effectively, in the clutter environment, the status of the targets can be estimated precisely and steadily. This paper compares the proposed filtering algorithm with the classical IMM algorithm in performance, and the simulation results show that, the improved filtering algorithm has good tracking performance and tracking accuracy.

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Parallel Filtering Algorithm in Three Dimensions for IMM Maneuvering Target Tracking

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.651-653.2362 ◽

2014 ◽

Vol 651-653 ◽

pp. 2362-2367 ◽

Cited By ~ 1

Author(s):

Xi Tao Zhang ◽

An Qing Zhang

Keyword(s):

Computational Complexity ◽

Target Tracking ◽

Three Dimensions ◽

Maneuvering Target Tracking ◽

Filtering Algorithm ◽

Maneuvering Target ◽

Model Set ◽

Simulation Results

According to the physical truths those are the complexity of special target maneuvering and the inconformity of maneuvering degrees in three dimensions, the problems of model mismatching and inaccuracy in traditional IMM were analysed, then a parallel filtering algorithm in three dimensions for IMM maneuvering target tracking is presented. The model set of this algorithm consists of the CV and the modified CS model, which can adaptively tracking target under different maneuvering levels; the parallel IMMs in three dimensions can update model probabilities respectively according its maneuvering reality,which ensures the accuracy of model probabilities. The simulation results indicate that the proposed algorithm gets higher tracking precision and decrease 1/3 computational complexity than traditional IMM. That is to say, it has a good practical prospect in maneuvering target tracking in space.

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