Space target extraction and detection for wide-field surveillance

Abstract

Abstract A wide-field surveillance system with a long exposure time has a stronger capability of space target detection. However, it also produces some complicated situations that make it difficult to detect space targets; some stars appear as streak-like sources, countless object points, and possible discontinuous or nonlinear target trajectories. We present a space target detection method with high detection probability and low computational cost to overcome these obstacles. Firstly, the improved adaptive threshold method and the omnidirectional morphological filtering method are implemented to remove stars and noise. Secondly, the relative inter frame motion distance can be used as the basis for predicting the valid state transition region in each image. Finally, a state transition multistage hypothesis testing method is proposed to detect targets with linear, nonlinear, continuous or discontinuous trajectories. As demonstrated by the experimental results in simulated image sequences and real image sequences, the proposed algorithm can effectively detect space targets in wide-field surveillance with long exposure time, and has a high detection probability and low computational cost.