Abstract
The performance of traditional clutter suppression methods including moving target indication (MTI), moving target detection (MTD) and constant false alarm rate (CFAR) are limited under the background of strong clutter. In order to effectively eliminate false alarm plots caused by clutter, a radar false alarm plots elimination method based on multi-feature evaluation is proposed. Firstly, the density based spatial clustering of applications with noise (DBSCAN) algorithm is used to cluster the radar echo data processed by CFAR. The multi-features including the scale features, time domain features and transform domain features are extracted. Secondly, features evaluation methods are used to evaluate interrelation among features, effective feature combinations are selected as inputs of the classifier. Finally, False alarm plots classified as clutters are eliminated. The experimental results show that proposed method can eliminate about 93% false alarm plots with less target loss rate.
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