Man-Made Target Detection in Urban Areas Based on a New Azimuth Stationarity Extraction Method

Abstract

Urban areas are the primary living environments of human beings, and a frequent focus in Earth observation based analyses. Chances for advancement in this field especially exist in the detection of man-made targets in urban area using synthetic aperture radar (SAR) images. Especially stationarity is a useful parameter in SAR image information extraction that has begun to attract attention in recent years. However, the theory and analytical methods of stationarity in the SAR processing domain are still in the initial stage. In this paper, six types of stationarity in SAR imagery are discussed, and stationarity in azimuth direction is utilized to separate man-made and natural targets in urban areas. Furthermore, a new azimuth stationarity extraction method based on Rician distribution is proposed to adapt to the complex situation in urban areas and to achieve an effective detection result. According to our analyses, the result obtained by the new method proposed shows a 10%-20% higher accuracy than the result based on traditional stationarity extraction methods, and the overall detection accuracy for the method proposed exceeds 80%, which indicates a good performance.