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In military, target identification is often conducted
manually and based on personal experience. The goal is
mainly focused to clarify the target allegiance and its class
like ally or enemy, bomber, fighter or commercial jet, etc
There are some proposed methods:
Some early works determine the target class based on kinematic features such as the maximum speed or estimated acceleration, trajectories. They tried to measure how close the trajectory to the nearest known flight path that has already pre-defined.
Other approaches use machine learning, deep learning for classification. These methods have multidimensional data problems.
In this report, we propose a new method of feature
extraction that could automatically identify flying targets with
a simple Random Forest machine learning model.
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IEEE/ICACT20220272 Slide.03
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