For the high-precision positioning requirements of UAV formation cooperative operation,a distributed control system based on RTK technology is proposed in this paper.By using the U-blox F9P GNSS module to build an RTK...For the high-precision positioning requirements of UAV formation cooperative operation,a distributed control system based on RTK technology is proposed in this paper.By using the U-blox F9P GNSS module to build an RTK base station/mobile terminal,combined with Pixhawk 6C flight control and MAVESP8266 communication module,centimeter-level(<2 cm)positioning accuracy is achieved.The system adopts the“centralized planning distributed execution”architecture,transmits RTCM differential data and MAVLink messages through the UDP protocol,and integrates ROS to realize status information subscription.Experiments show that the system can effectively support large area surveying and mapping and other complex tasks,and significantly improve the autonomy and reliability of formation operations.展开更多
在GNSS边坡监测中,基准站与监测站间的大高差会增加相对对流层延迟误差,严重制约实时动态差分(real time kinematic,RTK)垂向定位精度.为此,本文构建了一种顾及大高差改进的区域对流层模型.该模型基于基准站与监测站高精度天顶对流层延...在GNSS边坡监测中,基准站与监测站间的大高差会增加相对对流层延迟误差,严重制约实时动态差分(real time kinematic,RTK)垂向定位精度.为此,本文构建了一种顾及大高差改进的区域对流层模型.该模型基于基准站与监测站高精度天顶对流层延迟(zenith tropospheric delay,ZTD)模型数据,采用三次多项式函数建立ZTD与站间高程之间的函数关系,同时考虑了ZTD的季节变化特征,建立了区域对流层模型.为验证模型的有效性,以滨海某大高差边坡为研究对象,实验结果表明,本文提出的该模型有效提升了U方向的定位精度,较Saastamoinen模型、第三代全球气压和气温(Global Pressure and Temperature 3,GPT3)模型分别提升了约15%、8%.该模型有效提升站间大高差对流层误差改正效果,为GNSS大高差边坡监测提供了方案.展开更多
1背景近年来,随着自动驾驶技术的不断进步与发展,智能车辆在军事和民用领域的重要性逐渐凸显出来。而在复杂环境下的精确定位是智能化无人系统完成各类任务的前提,如何实现全局高精度定位一直都是当前研究的热点。目前融合卫星导航系统(...1背景近年来,随着自动驾驶技术的不断进步与发展,智能车辆在军事和民用领域的重要性逐渐凸显出来。而在复杂环境下的精确定位是智能化无人系统完成各类任务的前提,如何实现全局高精度定位一直都是当前研究的热点。目前融合卫星导航系统(Real Time Kinematic,即RTK)与惯性导航系统(Inertial Navigation System,即INS)是针对车载场景最广泛和可靠的方案之一。展开更多
基金The 2023 Scientific and Technological Project in Henan Province of China(Grant No.232102220098)。
文摘For the high-precision positioning requirements of UAV formation cooperative operation,a distributed control system based on RTK technology is proposed in this paper.By using the U-blox F9P GNSS module to build an RTK base station/mobile terminal,combined with Pixhawk 6C flight control and MAVESP8266 communication module,centimeter-level(<2 cm)positioning accuracy is achieved.The system adopts the“centralized planning distributed execution”architecture,transmits RTCM differential data and MAVLink messages through the UDP protocol,and integrates ROS to realize status information subscription.Experiments show that the system can effectively support large area surveying and mapping and other complex tasks,and significantly improve the autonomy and reliability of formation operations.
文摘在GNSS边坡监测中,基准站与监测站间的大高差会增加相对对流层延迟误差,严重制约实时动态差分(real time kinematic,RTK)垂向定位精度.为此,本文构建了一种顾及大高差改进的区域对流层模型.该模型基于基准站与监测站高精度天顶对流层延迟(zenith tropospheric delay,ZTD)模型数据,采用三次多项式函数建立ZTD与站间高程之间的函数关系,同时考虑了ZTD的季节变化特征,建立了区域对流层模型.为验证模型的有效性,以滨海某大高差边坡为研究对象,实验结果表明,本文提出的该模型有效提升了U方向的定位精度,较Saastamoinen模型、第三代全球气压和气温(Global Pressure and Temperature 3,GPT3)模型分别提升了约15%、8%.该模型有效提升站间大高差对流层误差改正效果,为GNSS大高差边坡监测提供了方案.
文摘1背景近年来,随着自动驾驶技术的不断进步与发展,智能车辆在军事和民用领域的重要性逐渐凸显出来。而在复杂环境下的精确定位是智能化无人系统完成各类任务的前提,如何实现全局高精度定位一直都是当前研究的热点。目前融合卫星导航系统(Real Time Kinematic,即RTK)与惯性导航系统(Inertial Navigation System,即INS)是针对车载场景最广泛和可靠的方案之一。
