Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Classification Of Automotive Targets Using Inverse Synthetic Aperture
  Radar Images   We present a framework for simulating realistic inverse synthetic aperture
radar images of automotive targets at millimeter wave frequencies. The model
incorporates radar scattering phenomenology of commonly found vehicles along
with range-Doppler based clutter and receiver noise. These images provide
insights into the physical dimensions of the target, the number of wheels and
the trajectory undertaken by the target. The model is experimentally validated
with measurement data gathered from an automotive radar. The images from the
simulation database are subsequently classified using both traditional machine
learning techniques as well as deep neural networks based on transfer learning.
We show that the ISAR images offer a classification accuracy above 90% and are
robust to both noise and clutter.

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The categories of this paper are: math
31
The categories of this paper are: ao-sci
11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
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The categories of this paper are: physics
20
The categories of this paper are: acc-phys
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The categories of this paper are: patt-sol
18
The categories of this paper are: econ
5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph
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The categories of this paper are: hep-th
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The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
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The categories of this paper are: hep-ph
21
The categories of this paper are: adap-org
16
The categories of this paper are: stat