迭代法分析稳定性的改进

用一简便的方法统一处理廖晓昕的用迭代法分析系统稳定性的一系列结果,不仅简化了征明,而且减轻了条件,文中所用的方法说明用迭代法分析系统稳定性本质上是向量比较定理的应用。

无人机集群多构型融合相对定位性能分析

针对大规模集群无人机相对定位问题,采用随机择机策略,基于载波相位观测,提出了一种非线性迭代求解方法。在传统精度因子的基础上,推导并构建了精度评估准则,随机选取多架主机进行观测定位,实现观测时段内多构型融合解算无人机状态信息。同时,利用扩展卡尔曼滤波给出位姿估计结果。仿真结果表明:随机择机策略实现了观测时段内的多构型融合,解决了单一构型限制,且主机数量增多可有效抑制精度因子过大,显著提高了定位精度。此外,扩展卡尔曼滤波可获得高精度位姿信息,迭代估值方法可用于滤波估计前的预处理阶段,进一步提高定位精度。为集群无人机在复杂环境中飞行提供了一种相对定位手段。

Motion estimation based feature selection for visual SLAM

Feature selection is always an important issue in the visual SLAM （simultaneous location and mapping） literature. Considering that the location estimation can be improved by tracking features with larger value of visible time, a new feature selection method based on motion estimation is proposed. First, a k-step iteration algorithm is presented for visible time estimation using an affme motion model; then a delayed feature detection method is introduced for efficiently detecting features with the maximum visible time. As a means of validation for the proposed method, both simulation and real data experiments are carded out. Results show that the proposed method can improve both the estimation performance and the computational performance compared with the existing random feature selection method.