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Abstract

An adjustable parameter model for tracking manoeuvring targets is presented using a modified variable variance intensity technique. This model is based on the Singer model but with modifications to its fixed manoeuvre statistical characteristics. Meanwhile, a ‘current model’ concept is adapted to describe the statistical distribution of the target's acceleration. Since the variance intensity of the proposed model is calculated using a variable manoeuvring probability density function with adequate covariance, it exhibits a strong adaptive ability for tracking a manoeuvring target and a reduced steady estimation bias in tracking a non-manoeuvring target. Computer simulation results show that a Kalman estimator based on this model can track both manoeuvring and non-manoeuvring targets with greater accuracy than either the Singer model or the interacting multiple model method and is suitable for online processing.

Keywords

manoeuvring target tracking Kalman filtering adaptive filtering Singer model

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References

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An adjustable parameter model for tracking a manoeuvring target

Abstract

Abstract

Keywords

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References