Abstract:

In order to precisely locate and track space targets, and construct targets’ kinematic trajectories, a space target detection algorithm in star image based on motion information is researched. Firstly, target’s SNR is increased based on spatial energy accumulation, and the faint targets can be easily segmented from the background. Then, according to the invariance of stars’ relative position in two neighboring frames, the control points of star images are extracted. And the global motion parameters can be calculated with the control points in succession. Then, according to the relative position between star points and the control points, stars and potential targets are classified. And then, targets are grossly detected utilizing the 3-frames nearest neighboring correlation method, and false targets are filtered with the multiframe back and forth searching method. In the end, all targets in star image sequence are numbered, and targets’ trajectories are constructed. Experimental results about four groups of real photographed star images are as follows: All targets’ kinematic trajectories are constructed. The average SNR detected is 2.99. The least mean motion velocity is 2.47 pixel/frame. The most mean motion velocity is 12.72 pixel/frame. The algorithm in this paper can satisfy the space target detection requirements, which include high detection probability, few false alarms and high trajectory locating accuracy, etc.