On orbit flying spacecraft detection in near range is of great significance to space based surveillance and the final stage of rendezvous & docking. In this paper, we propose an effective flying spacecraft detection algorithm with the earth as the cluttered dynamic background based on superpixels clustering. Labeled point trajectories are used as the motion cue, and both color and texture features are extracted from generated superpixels for clustering. Experimental results show that our proposed method performs well on real world videos recorded by cameras onboard the International Space Station.

In terms of the motion planning problem of spacecraft proximity operations with obstacle avoidance under low uncertainty, the improved equal-collision-probability-curve and improved linear quadratic regulator (IECPC-ILQR) strategy is proposed. Firstly, the novel function of the IECPC algorithm is developed to generate the avoidance control impulse. Subsequently, the ILQR is designed to track the reference trajectory. Furthermore, combining the improved ECPC algorithm with the ILQR controller, the composite controller of the IECPC-ILQR strategy is obtained and is implemented on the chaser spacecraft. Compared with the traditional ECPC algorithm, the IECPC-ILQR strategy can avoid collision in the presence of low uncertainty. Furthermore, the proposed avoidance strategy can obtain higher control precision while requiring the same fuel. Finally, numerical simulations verify the effectiveness of the proposed IECPC-ILQR strategy.

This study is mainly focusing on the problem of spacecraft close-range proximity with obstacle avoidance in the presence of complex shape. A novel Gaussian mixture model–based nonsingular terminal sliding mode control (GMM-NTSMC) is proposed. This is achieved by developing GMM-based potential function with a switching surface of NTSMC. It is theoretically proved that the closed-loop system is globally stable. The main contribution of this study is that the GMM-based avoiding strategies, which include the GMM-based terminal sliding mode control (GMM-TSMC) and GMM-NTSMC, can solve the collision avoidance problem considering complex shape while the artificial potential function–based terminal sliding model control (APF-TSMC) fails. Moreover, the GMM-NTSMC and the GMM-TSMC require less energy with respect to the APF-TSMC. Furthermore, the GMM-NTSMC retains the advantage of the NTSMC and can avoid singularity problem while GMM-TSMC cannot. Finally, numerical simulations are performed to verify the effectiveness and superiority of the proposed GMM-NTSMC.

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