论文信息 - Trajectory Processing Under Incomplete Measurement Situation Using a Sparse Representation Model

Trajectory Processing Under Incomplete Measurement Situation Using a Sparse Representation Model

Under the incomplete measurement situation, how to get a smoothing trajectory with high precision is an important problem. In this article, a fusion method based on the Error Model Best Estimate of Trajectory (EMBET) algorithm is proposed to handle the incomplete measurement problem by using a sparse representation model for trajectory of reentry target. And the sparse representation model of trajectory is built by analyzing the dynamic characteristics of launch vehicles. Simulations show the effectiveness of the proposed method.

Wang Jiang | Jubo Zhu | Zenghui Zhang

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