| 注册
首页|期刊导航|林业工程学报|农林环境下RTK-UWB多传感器融合定位方法

农林环境下RTK-UWB多传感器融合定位方法

刘诚 李金阳 贾娜 花军

林业工程学报2024,Vol.9Issue(6):142-151,10.
林业工程学报2024,Vol.9Issue(6):142-151,10.DOI:10.13360/j.issn.2096-1359.202309040

农林环境下RTK-UWB多传感器融合定位方法

RTK-UWB multi-sensor fusion positioning method in agroforestry environment

刘诚 1李金阳 1贾娜 1花军1

作者信息

  • 1. 东北林业大学机电工程学院,哈尔滨 150040
  • 折叠

摘要

Abstract

This investigation sets out to devise an intricate,yet robust multi-sensor fusion positioning methodology explicitly tailored for the demanding terrains of agricultural and forestry landscapes.The primary objective revolved around countering the inherent uncertainties plaguing the stability of global navigation satellite system(GNSS)signals.Central to this endeavor is the development of a multi-sensor fusion positioning technique anchored on the bedrock of the unscented Kalman filter(UKF).This innovative approach intricately weaved together real-time motion dynamics models with data streams harnessed from an extensive array of sensors.These included,but are not limited to,real-time kinematic,ultra-wideband,inertial measurement units,and wheel encoders.The brilliance of employing UKF for state estimation lies in its ability to yield positioning precision that transcends the centimeter scale,navigating seamlessly through a spectrum of sensor amalgamations,and steadfastly maintaining stability even in the wake of erratic RTK signals.To validate the potency of this novel approach,a series of meticulously designed field experiments were meticulously conducted.Through a comprehensive comparative analysis against existing methodologies,the findings under optimal RTK signal conditions showcased a mere 3.0 cm maximum positioning error-a testament to the precision of this research methodology.More strikingly,the resilience of the proposed multi-sensor fusion technique revealed its capacity to sustain positioning accuracy in the absence of a functional RTK signal.It demonstrated a fusion positioning variance of 1.0 cm,a maximal divergence under 4.0 cm,and the conspicuous absence of any positioning oscillations or divergence phenomena.Relative to the inherent inaccuracies within signals,the proposed methodology presented a staggering reduction of nearly 96%,underscoring its exceptional stability and its robustness in mitigating the adversities stemming from RTK signal degradation.This bespoke multi-sensor fusion positioning technique stands as a beacon of reliability in the specific realms of agricultural and forestry applications.Its unwavering provision of positioning data,even in the face of faltering RTK signals,offers a pragmatic solution to the persistent challenges arising from the capricious nature of GNSS signal consistencies.Consequently,this pioneering approach heralds substantial promise across a multifaceted spectrum of applications,transcending the realms of agriculture and forestry to encompass diverse domains.Its potential to effectively navigate and neutralize the impediments posed by GNSS signal instability underscores its pivotal role in fortifying the continuous evolution of positioning technology.

关键词

农林环境/多传感器融合/定位/RTK/UWB

Key words

agroforestry environment/multi-sensor fusion/positioning/RTK/UWB

分类

信息技术与安全科学

引用本文复制引用

刘诚,李金阳,贾娜,花军..农林环境下RTK-UWB多传感器融合定位方法[J].林业工程学报,2024,9(6):142-151,10.

基金项目

国家重点研发计划(2022YFD2202105). (2022YFD2202105)

林业工程学报

OA北大核心CSTPCD

2096-1359

访问量0
|
下载量0
段落导航相关论文