모노스태틱/바이스태틱 ISAR 영상 융합을 통한 편대비행 표적 식별

Abstract

inverse synthetic aperture radar (ISAR) images are 2-dimensional RCS distributions that can be generated through radar reflection signals and provide very effective radar signature for target recognition using radar. For target approaching along radar’s line of sight(LOS), the bistatic ISAR can compensate for the weakness of the monostatic ISAR which can not obtain the vertical resolution of the image. However, bistatic ISAR have longer processing times and variability in scattering mechanisms than monostatic ISAR, so target identification using only bistatic ISAR images can be inefficient. In case of targets in formation flight, when there are many targets in the single radar beam, ISAR images are generated in real time by the type and the number of targets, real time projection, and scale factor according to variance of radar beam. In addition, since it is impossible to predict the above parameters in advance, unlike the single target identification problem, it is difficult to perform the multiple targets identification using the previously trained database. Therefore, this paper analyzes targets in formation flight identification performance using monostatic and bistatic ISAR images of targets approaching along radar’s LOS and proposes a method of target identification through fusion of two radars. also, to identify targets in formation flight, ISAR images of a single target that have been trained previously are combined using 2-D fourier transform property and then a real time database is constructed to perform multiple targets classification. The projection position and the scale factor are optimized and combined through particle swarm optimization (PSO), and the process is repeated according to the type and number of targets to construct a real time database. Simulation results demonstrate that identification performance through fusion is more efficient than identification performance using only monostatic, bistatic ISAR images.