Abstract
The normalized central moments are widely used in pattern recognition because of scale and translation invariance. The moduli of normalized central moments of the 1-dimensional complex range profiles are used here as feature vector for radar target recognition. The common feature extraction method for high resolution range profile obtained by using Fourier-modified direct Mellin transform is inefficient and unsatisfactory in recognition rate. And. generally speaking, the automatic target recognition method based on inverse synthetic aperture radar 2-dimensional imaging is not competent for real time object identification task because it needs complicated motion compensation which is sometimes too difficult to carry out. While the method applied here is competent for real-time recognition because of its computational efficiency. The result of processing experimental data indicates that this method is good at recognition.
| Original language | English |
|---|---|
| Pages (from-to) | 17-20 |
| Number of pages | 4 |
| Journal | Journal of Beijing Institute of Technology (English Edition) |
| Volume | 13 |
| Issue number | SUPPL. |
| Publication status | Published - Dec 2004 |
Keywords
- Automatic target recognition
- Clustering analysis
- Nearest neighbor classifier
- Normalized central moment
- Radar range profile