基于PDOP贡献度的分步式迭代优化选星算法

Two⁃Step Iterative Optimization of Satellite Selection Algorithm Based on PDOP Contribution

全球导航卫星系统(Global navigation satellite system,GNSS)是民航所需导航性能(Required navigation performance,RNP)程序的重要导航传感器。GNSS的定位精度决定了民用飞机是否能够满足RNP飞行要求。由于飞机上接收机的计算能力有限,计算延迟可能会降低定位精度。为了满足高精度要求,计算延迟引起的误差不能再被忽视。本文提出了一种基于位置精度因子(Position dilution of precision,PDOP)贡献的两步迭代卫星选星算法优化,可以有效减小计算延迟并提高RNP程序下的定位精度。仿真结果表明,该方法在实时性方面优于传统算法,对确保民用飞机飞行安全具有重要意义。

Global navigation satellite system(GNSS)is an important navigation sensor for the required navigation performance(RNP)operation.The positioning accuracy of GNSS determines whether the civil aircraft can meet the RNP flight requirements.Due to the limited computing power of airborne receivers,the calculation delay may reduce the positioning accuracy.To meet the high precision requirements,this error caused by calculation delay can no longer be ignored.This paper proposes a two-step iterative optimization of satellite selection algorithm based on the position dilution of precision(PDOP)contribution.It can effectively reduce the calculation delay and improve the positioning accuracy under the RNP operation.The simulation shows that the method has better real-time performance than the traditional algorithm,which is of great significance for ensuring the flight safety of civil aircraft.