Abstract
In this paper, a new millimeter-wave (MMW) radar target classification approach has been proposed using polarimetric information to obtain stable amplitudes of range profiles, using neural learning to extract angle invariant features of range profiles. The means of the polarimetric processing for reducing the speckle can enhance ability to discriminate targets. Comparing with conventional approaches, subclass features obtained have carried more information by the neural learning and thus make the correctness of target classification higher. The simulation results have verified the validity of this approach.
| Original language | English |
|---|---|
| Pages | 147-150 |
| Number of pages | 4 |
| State | Published - 1996 |
| Event | Proceedings of the 1996 CIE International Conference of Radar Proceedings, ICR'96 - Beijing, China Duration: 8 Oct 1996 → 10 Oct 1996 |
Conference
| Conference | Proceedings of the 1996 CIE International Conference of Radar Proceedings, ICR'96 |
|---|---|
| City | Beijing, China |
| Period | 8/10/96 → 10/10/96 |
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