Space Target Recognition Method Based on Adaptive Spatial Filtering Multistage Hypothesis Testing

Considering that the current space target detection technology has some problems in target recognition,which are high false alarm rate and low algorithm efficiency,a space target recognition method based on Adaptive Spatial Filtering Multistage Hypothesis Testing(ASMHT) algorithm was proposed, which is used to extract space targets from star image in the sidereal tracking mode in photoelectric observation system. The method includes two processes of target coarse screening and target fine screening. Target coarse screening uses Gaussian difference function based on the scale space to get the scale value of each candidate target in the preprocessed image. The scale value is also set to the size of the spatial filtering window,and the gray correlation criterion is replaced by the gray distribution characteristics as the accordance of different kinds of targets in the spatial filtering window. The background stars without image motion and random noise are removed,and the suspected moving targets are screened out. The improved multistage hypothesis testing method is used in target fine screening,in order to greatly improve the efficiency of the algorithm,the speed window of candidate targets are established and the space targets are selected according to the trajectory characteristics. The experimental results of space target in simulation image show that,compared with the existing space target recognition methods,the ASMHT algorithm has the ability of target detection under the condition of space targets in low SNR,and the comprehensive detection performance is the best,which can also obtain higher detection rate under the same false alarm rate. Real star image test results show that the ASMHT algorithm has lower computational complexity and achieves more accurate space target recognition.