摘要
针对三七种植区树木遮挡引起的卫星导航信号弱和相位失锁等导致智能化设备定位精度差问题,提出了基于伪距及多普勒双差定位算法的三七联合收获机遮蔽环境改进全球卫星导航系统(Global navigation satellite system,GNSS)定位算法.由于伪距测量和多普勒频移测量受影响因素的不同,以伪距双差及多普勒频移双差为输入,载噪比为权重,通过卡尔曼滤波实现测量值融合,降低估计误差校正伪距和多普勒频移测量.采用贝叶斯信息准则选择正则化参数,并通过Lasso回归求解重加权最小二乘问题,实现模型稀疏化,得到改进定位结果.使用u-bloxZED-F9P高精度全球导航卫星系统接收机采集RINEX格式报文,并通过Matlab实现了数据提取与位置解算.在开阔环境、荫棚遮蔽和树荫遮蔽工况下进行了实车定位精度试验.试验结果与传统伪距定位算法相比,静态定位时,开阔环境、荫棚遮蔽环境和树荫遮蔽环境位置误差分别降低13.43％、56.08％和46.35％,定位偏差均方根误差分别减少75.64％、62.31％、50.21％;动态工况下定位误差分别降低36.97％、52.14％、62.37％,定位偏差均方根误差分别减少45.34％、60.24％、65.81％.所提方法有效降低了 GNSS卫星信号差、相位失锁带来的定位误差,有效提高了复杂工况下农机定位精度与定位可信度,可为丘陵山区因树木遮挡导致智能化设备定位精度差问题提供理论和技术支撑.
Abstract
Aiming at the problem of poor positioning accuracy of intelligent equipment,such as weak satellite navigation signal and phase locking caused by tree occlusion in Panax notoginseng planting area,a global navigation satellite system(GNSS)positioning algorithm for the shading environment of Panax notoginseng combine harvester based on pseudorange and Doppler double-difference positioning algorithm was proposed.Firstly,based on the difference of the influencing factors of pseudorange measurement and Doppler frequency shift measurement,the pseudorange double difference and Doppler frequency shift double difference were taken as inputs,and the carrier irritability ratio was used as the weight,and the measured values were fused through Kalman filter,so as to reduce the estimation error and correct the pseudorange and Doppler frequency shift measurement.Secondly,the Bayesian information criterion was used to select the regularization parameters,and the reweighted least squares problem was solved by Lasso regression to achieve the sparsity of the model and obtain the improved positioning results.Finally,the u-blox ZED-F9P high-precision GNSS receiver was used to collect the messages in RINEX format.Under three working conditions:open environment,shade shelter and tree shade shielding,the positioning accuracy test of the real vehicle was carried out.Compared with the traditional pseudo-distance positioning algorithm,open environment,shade shelter environment,and tree shade shade environment the position error was reduced by 13.43%,56.08% and 46.35%,respectively,and the root mean square error of the positioning deviation was reduced by 75.64%,62.31% and 50.21%,respectively.Under dynamic conditions,the positioning error was reduced by 36.97%,52.14% and 62.37%,respectively,and the root mean square error of positioning deviation was reduced by 45.34%,60.24% and 65.81%,respectively.The proposed method effectively reduced the positioning error caused by GNSS satellite signal difference and phase lock,and effectively improved the positioning accuracy and positioning credibility,The research result can provide theoretical and technical support for the problem of poor positioning accuracy of intelligent equipment due to tree shading in hilly and mountainous areas.
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