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Design and analysis of a knowledge-based radar detector

In this paper we introduce and assess a knowledge-based (KB) radar detector composed of three elements: a geographical information system-based (GIS-based) data selector, which eliminates static outliers from the secondary data exploiting the a-priori information concerning the topography of the observed scene, a data-adaptive training selector which removes dynamic outliers from the training data, and an adaptive radar detector which performs the final decision about the target presence. The performance of the new algorithm is analyzed on real radar data collected by the McMaster University IPIX radar. The results show that the new KB system achieves a satisfactory performance level and can outperform some previously proposed adaptive detection schemes.