一种导航传感器试飞基准获取方法研究

A Method for Obtaining Navigation Sensor Flight Testing Benchmark

在简要分析导航传感器试飞现状的基础上,提出了利用数据融合算法获取导航传感器数据基准的实现方案,在方案中充分考虑了不同导航传感器的性能特性,提出了基于集中Kalman滤波的试飞导航数据初步融合和在Kalman滤波基础上利用固定区间平滑滤波实现全局信息优化融合的导航传感器基准获取方法,并利用试飞数据对融合算法进行了验证。结果表明:该方法有效利用了不同传感器的特性和事后数据处理的优势,融合输出精度较融合前有明显提高,为导航传感器的试飞评估提供了新的思路和方法。

The current situation of navigation sensor flight test was briefly analyzed, a method using data fusion algorithm to obtain navigation sensor benchmark was proposed. In this scheme, the performance characteristics of different types of navigation sensors were taken into full consideration. A preliminary test flight navigation data fusion based on centralized Kalman filter was carried out. On the basis of Kalman filtering, fixed-internal smooth filtering was used to achieve global information optimization. The data fusion algorithms were verified by the flight test data. The result shows that, the method makes full advantage of different types of sensors on their characteristics and post data processing capability, and the precision of fusion output is significantly improved. The method supplies a new idea for navigation sensor flight test evaluation.