ABSTRACT
Synthetic aperture radar (SAR) image understanding and interpretation are essential for remote sensing of Earth environment and target detection [1-12]. In the development of aided target recognition and identi†cation system, the SAR image database with rich information content plays important roles. It is well recognized that these image base volumes are enormous and it is impractical to acquire them solely by in situ measurements. Hence, SAR simulation is one potential alternative to alleviating the problem. However, it is highly desirable to develop a full-blown SAR image simulation scheme with high verisimilitude including the sensor and target geolocation relative to the Earth, movement of the SAR sensor, SAR system parameters, radiometric and geometric characteristics of the target, and environment clutter. The simulation should at least include the computation of radar cross section (RCS) of targets, orbital parameters estimation, SAR echo signal generation, image focusing, and so on. Such a simulation scheme is also well suited for satellite SAR mission planning. Nevertheless, the simulation apparently is of high computational complexity and is heavy computational resource demanding. To release the heavy computational burden, a graphic processing unit (GPU)-based algorithm that explores and makes use of the graphic computation power is developed. As an application example of the simulated SAR images, the second part of this chapter deals with target recognition. Before doing so, feature enhancement and extraction are presented. It is well known that good feature enhancement is essential for target identi†cation and recognition of
12.1 Introduction .......................................................................................................................... 221 12.2 Satellite SAR Images Simulation ......................................................................................... 222
12.2.1 SAR Signal Model .................................................................................................... 223 12.2.2 RCS Computation .....................................................................................................224 12.2.3 Clutter Model ............................................................................................................225 12.2.4 Satellite Orbit Determination ...................................................................................226 12.2.5 Image Focusing .........................................................................................................228
