星座构型筛选的改进几何定位方法

Improved geometric positioning method with constellation configuration screening

该文针对在轨卫星量测信息源的远距离定位问题,提出一种利用星座空间构型特性的n点透视(perspective-n-point,PnP)问题改进定位方法:从选取定位数据源出发,分析卫星几何构型对定位误差的影响,提取影响构型的主要参数,建立几何构型评价函数,评价星座构型的可用度。该文提出的PnP方法利用视场内构型筛选的星座卫星角度量测信息进行定位解算,筛选出受图像噪声影响较小的构型,提高定位解算精度,并通过仿真试验验证了筛选方法的有效性。该文研究结果可为远距离光学导航定位问题提供参考。

[Objective] As the number of low earth orbit(LEO) satellites increases,the applicability of optical navigation technology,which uses these satellites as optical information sources,is continually improving.When three or more satellites are simultaneously observed within the optical field of view,the perspective-n-point(PnP) positioning method can be used for pose estimation and positioning.The PnP problem was initially used primarily for camera calibration.Currently the applications of the PnP problem have expanded to various engineering tasks,including simultaneous visual localization and mapping,spatial noncooperative target pose estimation,and the critical stages of rendezvous and docking.However,the PnP algorithm struggles with low positioning accuracy over long distances.Therefore,it is necessary to study the spatial geometric positioning problem when observing satellites at relative distances exceeding hundreds of kilometers.[Methods] This study begins by selecting positioning data sources and statistically investigating the impact of constellation configuration within the optical field of view on positioning errors.The relationships between the constellation area and positioning errors,the geometric angle and positioning errors,and the relationship between the orbit height distribution and positioning errors are analyzed.Through this analysis,the primary influencing indicators are identified as the area,angle,and distance indicators.The distance indicator,in particular,represents the three-dimensional information of the configuration,which cannot be characterized by position dilution of precision(PDOP).To unify the measurement space of each indicator,the indicators are normalized,and the entropy weight method is used to calculate the weight of each indicator.An evaluation function for the constellation configuration is established to assess the configuration availability.The availability distribution is statistically analyzed to determine the evaluation criteria.Finally,using the calculated availability,configurations that are less affected by image noise are selected for the PnP pose calculation.In addition,the difference between the PDOP and positioning error is presented,and the PnP pose is estimated after the configuration is evaluated.[Results] Taking the P3P problem as an example,the positioning error was smaller when the distribution area of the three satellites was larger and more dispersed.According to the proposed screening method,positioning accuracy was improved by more than 50% compared with the situation without screening.Additionally,the configuration positioning accuracy was improved by approximately 37% compared with that of the PDOP-optimized configuration.[Conclusions] Constellation satellites enhance space navigation information sources.Configuration screening effectively improves the accuracy of PnP geometric positioning over long distances,thereby introducing a new concept for long-distance optical navigation.