Performance evaluation of model-based pose determination and tracking in sparse range data

在本项目中，我们将研究稀疏距离数据下基于模型的卫星姿态确定和跟踪。这个项目建立在以前工作的基础上，在这些工作中，我们已经成功地在均匀随机稀疏范围数据序列中演示了这些功能。在这个项目中，我们将从两个方面扩展这项工作，首先将其应用于非均匀稀疏范围数据，这更能代表天基系统可以收集的数据。第二个扩展将是调查性能评估问题，这将使我们能够在各种条件下评估和比较跟踪算法。我们还将开发一种在线性能监控器，它将持续自动评估跟踪系统的性能，并在必要时采取纠正措施。

In this project we will investigate the model-based pose determination and tracking of satellites in sparse range data. This project builds upon previous work where we have successfully demonstrated these capabilities in uniform random sparse range data sequences. In this project, we will extend this work in two ways, first by applying it to non-uniform sparse range data, which is more representative of the data that could be collected by a space-based system. The second extension will be to investigate issues of performance evaluation, which will allow us to assess and compare tracking algorithms under various conditions. We will also develop an on-line performance monitor that will continuously automatically assess the performance of a tracking system, invoking corrective action when necessary.