LING Rongqiao,LU Huiguo,JIANG Juanping,et al.Optimization Study of Wind Measurement based on Meteorological Drone Observation[J].Journal of Chengdu University of Information Technology,2023,38(03):271-276.[doi:10.16836/j.cnki.jcuit.2023.03.004]
基于气象无人机观测的测风优化研究
- Title:
- Optimization Study of Wind Measurement based on Meteorological Drone Observation
- 文章编号:
- 2096-1618(2023)03-0271-06
- Keywords:
- UAV; Pitot-Static tube; wind measurement; air density
- 分类号:
- TP79
- 文献标志码:
- A
- 摘要:
- 气象无人机测风主要依托于皮托-静压管法,通过皮托管和静压管的气压差测得空速,通过GPS等设备测得地速,根据地速、空速和风速的三角矢量关系间接测得空速。现有的测空速模型采用标准大气压下的空气密度,不考虑无人机在飞行时的空气密度,这与标准大气不相符。本文通过2021年12月11日在四川省都江堰市的无人机飞行数据来分析空速和地速的变化。将原始空速和风速与考虑空气密度得到后的修正空速和风速对比发现:在不考虑空气密度的情况下,空速的绝对误差在-1.35~-1.25 m/s,相对误差在-6%左右; 然而,传递给风速的平均相对误差却达到20%左右,最大达到40%。而引入空气密度可以消除这部分误差,从而提高测风精度。
- Abstract:
- Meteorological UAV wind measurement is mainly based on the Pitot-Static tube method, which measures the air speed through the Pitot tube and static tube air pressure difference. According to the triangular vector relationship of ground speed measured by GPS and other equipments, air speed and wind speed, air speedcan be measuredindirectly. The existing airspeed measurement model uses the air density at standard atmospheric pressure, and does not consider the air density of the UAV during flight. In this paper, we analyze the variation of airspeed and ground speed by the flight data in Dujiangyan, Sichuan Province on December 11, 2021. Comparing the original airspeed and wind speed with the corrected airspeed and wind speed considering the air density, it is found that: the absolute error of airspeed which ignores the influence of air density is between -1.35 - -1.25 m/s and the relative error is around -6%; however, the average relative error passed to the wind speed reaches around 20% and the maximum reaches 40%. And the introduction of air density can eliminate this part of error, thus improving the wind measurement accuracy.
参考文献/References:
[1] 朱嘉慧,王海江,李静,等.Meteo-particle模型在ADS-B风场反演中的性能研究[J].成都信息工程大学学报,2021,36(5):479-484.
[2] Alaoui-Sosse S,Durand P,Medina P,et al.BOREAL—A Fixed-Wing Unmanned Aerial System for the Measurement of Wind and Turbulence in the Atmospheric Boundary Layer[J].Journal of Atmospheric and Oceanic Technology,2022,39(3):387-402.
[3] 宁志远,刘厚凤.大气边界层的国内外研究现状[J].中国环境管理干部学院学报,2017,27(2):22-25.
[4] Roseman C A,Argrow B M.Weather Hazard Risk Quantification for sUAS Safety Risk Management[J].Journal of Atmospheric and Oceanic Technology,2020,37(7):1251-1268.
[5] 何建新,张福贵,周红根,等.龙卷风探测雷达研制及业务化应用研究[J].气象科技进展,2021,11(4):54.
[6] 沈怀荣,邵琼玲,王盛军等编著.无人机气象探测技术[M].北京:清华大学出版社,2010.
[7] 祁月皎,何建新,王旭.多普勒天气雷达二维理想均匀风场的数值模拟[J].成都信息工程学院学报,2014,29(2):127-132.
[8] Pinto J O,O’Sullivan D,Taylor S,et al.The Status and Future of Small Uncrewed Aircraft Systems(UAS)in Operational Meteorology[J].Bulletin of the American Meteorological Society,2021,102(11):2121-2136.
[9] 董天天.基于无人机的大气边界层气象要素探测平台设计[D].南京:南京信息工程大学,2017.
[10] 马舒庆,汪改,潘毅.微型无人驾驶飞机探空初步试验研究[J].南京气象学院学报,1997(2):30-36.
[11] 屈耀红,凌琼,闫建国,等.无人机DR/GPS/RP导航中风场估计仿真[J].系统仿真学报,2009,21(7):1822-1825.
[12] Holland GJ.The Aerosonde robotic aircraft:A new paradigm for environmental observations[J].Bulletin of the American Meteorological Society,2001,82(5):889-901.
[13] 胡昊辉.基于六旋翼无人机的测风系统研究[D].长沙:湖南大学,2020.
[14] 任金彬,沈怀荣.无人机皮托-静压管测风误差分析[J].装备指挥技术学院学报,2004(4):45-48.
[15] 周伟静,沈怀荣.磁偏角对无人机皮托-静压管测风的影响分析[J].装备指挥技术学院学报,2006(4):97-101.
[16] 王彦杰,司长彬.基于气象无人机飞行角度的优化测风模型研究[J].传感器世界,2012,(8):16-20.
[17] 金永奇,周树道,卫克晶,等.引入加速度的无人机皮托-静压管法测风模型[J].探测与控制学报,2012,34(6):72-75.
[18] Borup,Kasper T,Fossen,et al.A Nonlinear Model-Based Wind VelocityObserver for Unmanned Aerial Vehicles[J].IFAC-PapersOnLine,2011,49(18):276-283.
[19] 周伟静,沈怀荣.一种基于小型无人机的风场测量方法[J].测试技术学报,2009,23(4):297-302.
[20] 李天文.GPS原理及应用[M].北京:科学出版社,2003.
[21] 程春龙,潘晓春.空气密度时序变化特征及其对风压计算的影响[J].黑龙江科学,2019,10(22):1-3.
[22] 王川.电子测量技术与仪器[M].北京:北京理工大学出版社,2019.
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备注/Memo
收稿日期:2022-06-06
基金项目:国家自然科学基金资助项目(42075129)