Data association for target tracking by IR sensors

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Data association for target tracking by IR sensors

Li, Chen / Han, Chongzhao / Chen, Huimin / Zhu, Hongyan

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This paper seeks to examine the dynamic problem of associating measurements at a given period from several IR sensors in the presence of clutter, missed detections.

Design/methodology/approach –

On the basis of a dynamic S-D assignment algorithm, a new association algorithm for associating and tracking multiple targets is presented. By considering the special feature of the IR sensor, the dynamic assignment cost coefficient incorporates the radiation intensity information into the association process using a joint probabilistic model for the two separate sources of information (intensity and trajectory).

Findings –

The simulation results show that the new algorithm can attain almost the same accuracy of tracking estimation with less computational load by utilizing special feature information of the IR sensor into dynamic S-D assignment.

Research limitations/implications –

There are still some parameters to be set in advance, which influence the estimate result to some extent. And the tracking stage follows the image processor, so the tracking performance is also related with the quality of images. Those problems will be considered deeply in the future research based on different maneuvering level of targets and the real tracking environment.

Practical implications –

This new algorithm may be adopted by tracking systems based on passive sensors in the future.

Originality/value –

This new algorithm utilizes more information and fairly small and stable errors in position and velocity can be obtained. At the same time, it decreases computational load.