S. Hayek, Joe Saroufim, M. Neinavaie, Sharbel E. Kozhaya, Z. M. Kassas
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The objective of the proposed differential framework is to mitigate the effects of poorly known LEO SVs’ ephemerides, unknown LEO SVs’ dynamic clock error states, and atmospheric delays. Simulation results are presented to assess the performance of the proposed differential framework compared to a non-differential STAN. The simulations assume an aerial vehicle equipped with a tactical-grade inertial measurement unit (IMU) and an altimeter, navigating for 28 km in 300 seconds, the last 23 km of which without GNSS, while receiving signals from 14 Starlink LEO SVs. It is shown that the non-differential STAN achieves a position root-mean squared error (RMSE) of 15.63 m, while the differential STAN with one, two, and three bases reduces the position RMSE to 5.26 m, 3.88 m, and 1.94 m, respectively. Experimental results are presented in which a stationary base and a stationary rover, located at a distance of 1 km apart, extract Doppler observables from 3 Starlink LEO SVs. The differential framework was able to estimate the rover’s three-dimensional (3-D) and 2-D position with an error of 33.4 m and 5.6 m, respectively","PeriodicalId":261056,"journal":{"name":"Proceedings of the 2023 International Technical Meeting of The Institute of Navigation","volume":"112 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessment of Differential Doppler Navigation with Starlink LEO Satellite Signals of Opportunity\",\"authors\":\"S. Hayek, Joe Saroufim, M. Neinavaie, Sharbel E. Kozhaya, Z. M. Kassas\",\"doi\":\"10.33012/2023.18669\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A framework for differential Doppler navigation with Starlink low Earth orbit (LEO) space vehicle (SV) signals of opportunity is presented, and the framework’s performance is assessed. 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引用次数: 0
摘要
提出了一种基于星链低地球轨道飞行器(SV)机会信号的差分多普勒导航框架,并对该框架的性能进行了评估。差分框架假设漫游车(车辆)通过同步跟踪和导航(STAN)方法在没有全球导航卫星系统(GNSS)信号的情况下进行导航。在STAN中,车辆通过扩展卡尔曼滤波器(EKF)从LEO SVs中提取多普勒测量值来辅助其惯性导航系统(INS),同时估计车辆和LEO SVs的状态。此外,差分框架假设一个已知位置的固定基地,对相同的Starlink LEO sv进行多普勒测量,并将这些测量结果与漫游车进行通信。提出的差分框架的目的是减轻鲜为人知的LEO sv星历、未知的LEO sv动态时钟误差状态和大气延迟的影响。给出了仿真结果来评估所提出的差分框架与非差分STAN的性能。模拟假设一架配备战术级惯性测量单元(IMU)和高度计的飞行器,在300秒内导航28公里,其中最后23公里没有GNSS,同时接收来自14个Starlink LEO SVs的信号。结果表明,非差分STAN的位置均方根误差(RMSE)为15.63 m,而带有一个、两个和三个碱基的差分STAN的位置均方根误差分别为5.26 m、3.88 m和1.94 m。本文介绍了静止基地和静止漫游车在距离1 km处提取3颗Starlink LEO sv多普勒观测数据的实验结果。差分框架能够估计漫游车的三维(3-D)和二维位置,误差分别为33.4米和5.6米
Assessment of Differential Doppler Navigation with Starlink LEO Satellite Signals of Opportunity
A framework for differential Doppler navigation with Starlink low Earth orbit (LEO) space vehicle (SV) signals of opportunity is presented, and the framework’s performance is assessed. The differential framework assumes a rover (vehicle) navigating without global navigation satellite system (GNSS) signals, through the simultaneous tracking and navigation (STAN) approach. In STAN, the vehicle aids its inertial navigation system (INS) with Doppler measurements extracted from LEO SVs via an extended Kalman filter (EKF), simultaneously estimating the vehicle’s and LEO SVs’ states. In addition, the differential framework assumes a stationary base with a known position, making Doppler measurements to the same Starlink LEO SVs and communicating these measurements with the rover. The objective of the proposed differential framework is to mitigate the effects of poorly known LEO SVs’ ephemerides, unknown LEO SVs’ dynamic clock error states, and atmospheric delays. Simulation results are presented to assess the performance of the proposed differential framework compared to a non-differential STAN. The simulations assume an aerial vehicle equipped with a tactical-grade inertial measurement unit (IMU) and an altimeter, navigating for 28 km in 300 seconds, the last 23 km of which without GNSS, while receiving signals from 14 Starlink LEO SVs. It is shown that the non-differential STAN achieves a position root-mean squared error (RMSE) of 15.63 m, while the differential STAN with one, two, and three bases reduces the position RMSE to 5.26 m, 3.88 m, and 1.94 m, respectively. Experimental results are presented in which a stationary base and a stationary rover, located at a distance of 1 km apart, extract Doppler observables from 3 Starlink LEO SVs. The differential framework was able to estimate the rover’s three-dimensional (3-D) and 2-D position with an error of 33.4 m and 5.6 m, respectively