针对葡萄采摘机器人在采摘作业中受果园环境干扰,难以准确识别与分割葡萄果梗及定位采摘点的问题,该研究根据葡萄生长的特点提出一种基于深度学习的葡萄果梗识别与最优采摘定位方法。首先通过改进掩膜区域卷积神经网络(Mask Region with...针对葡萄采摘机器人在采摘作业中受果园环境干扰,难以准确识别与分割葡萄果梗及定位采摘点的问题,该研究根据葡萄生长的特点提出一种基于深度学习的葡萄果梗识别与最优采摘定位方法。首先通过改进掩膜区域卷积神经网络(Mask Region with Convolutional Neural Network,Mask R-CNN)模型对果梗进行识别与粗分割;然后结合阈值分割思想对果梗的色调、饱和度、亮度(Hue Saturation Value,HSV)色彩空间进行分段式提取,取每段色彩平均值作为该段果梗基准颜色阈值,利用区域生长算法对果梗进行精细化分割;最后计算果梗图像区域的质心,并以临质心点最近的果梗水平两侧中心作为最终采摘点。试验结果表明,在不同天气光照下该方法对葡萄果梗的检测精确率平均值为88%;在果梗成功识别后最优采摘点定位准确率达99.43%,单幅图像的果梗采摘定位平均耗时为4.90 s,对比改进前Mask R-CNN检测耗时减少了0.99 s,F1-得分提高了3.24%,检测效率明显提升,该研究为葡萄采摘机器人提供了一种采摘点定位方法。展开更多
Starting from 2016,the raw Global Navigation Satellite System(GNSS)measurements can be extracted from the Android Nougat(or later)operating systems.Since then,GNSS smartphone positioning has been given much attention....Starting from 2016,the raw Global Navigation Satellite System(GNSS)measurements can be extracted from the Android Nougat(or later)operating systems.Since then,GNSS smartphone positioning has been given much attention.A high number of related publications indicates the importance of the research in this field,as it has been doing in recent years.Due to the cost-effectiveness of the GNSS smartphones,they can be employed in a wide variety of applications such as cadastral surveys,mapping surveying applications,vehicle and pedestrian navigation and etc.However,there are still some challenges regarding the noisy smartphone GNSS observations,the environment effect and smartphone holding modes and the algorithm development part which restrict the users to achieve high-precision smartphone positioning.In this review paper,we overview the research works carried out in this field with a focus on the following aspects:first,to provide a review of fundamental work on raw smartphone observations and quality assessment of GNSS observations from major smart devices including Google Pixel 4,Google Pixel 5,Xiaomi Mi 8 and Samsung Ultra S20 in terms of their signal strengths and carrier-phase continuities,second,to describe the current state of smartphone positioning research field until most recently in 2021 and,last,to summarize major challenges and opportunities in this filed.Finally,the paper is concluded with some remarks as well as future research perspectives.展开更多
A long-term analysis of signal-in-space range error (SISRE) is presented for all healthy Galileo satellites, and the first pair of full operational capability satellites in wrong elliptical orbits. Both orbit and cloc...A long-term analysis of signal-in-space range error (SISRE) is presented for all healthy Galileo satellites, and the first pair of full operational capability satellites in wrong elliptical orbits. Both orbit and clock errors for Galileo show an obvious convergence trend over time. The annual statistical analyses show that the average root mean squares (RMSs) of SISRE for the Galileo constellation are 0.58 m (2015), 0.29 m (2016), 0.23 m (2017), and 0.22 m (2018). Currently, the accuracy of the Galileo signal-in-space is superior to that of the global positioning system (GPS) Block IIF (0.35 m). In addition, the orbit error accounts for the majority of Galileo SISRE, while the clock error accounts for approximately one-third of SISRE due to the high stability of the onboard atomic clock. Single point positioning results show that Galileo achieves an accuracy of 2-3 m, which is comparable to that of GPS despite the smaller number of satellites and worse geometry. Interestingly, the vertical accuracy of Galileo, which uses the NeQuick ionospheric model, is higher than that of GPS. Positioning with single frequency E1 and E5 show a higher precision than E5a and E5b signals. Regarding precise point positioning (PPP), the results indicate that a comparable positioning accuracy can be achieved among different stations with the current Galileo constellation. For static PPP, the RMS values of Galileo-only solutions are within 1 cm horizontally, and the vertical RMSs are mostly within 2 cm horizontally. For kinematic PPP, the RMSs of Galileo-only solutions are mostly within 4 cm horizontally and 6 cm vertically.展开更多
Precise Point Positioning(PPP),initially developed for the analysis of the Global Positing System(GPS)data from a large geodetic network,gradually becomes an effective tool for positioning,timing,remote sensing of atm...Precise Point Positioning(PPP),initially developed for the analysis of the Global Positing System(GPS)data from a large geodetic network,gradually becomes an effective tool for positioning,timing,remote sensing of atmospheric water vapor,and monitoring of Earth’s ionospheric Total Electron Content(TEC).The previous studies implicitly assumed that the receiver code biases stay constant over time in formulating the functional model of PPP.In this contribution,it is shown this assumption is not always valid and can lead to the degradation of PPP performance,especially for Slant TEC(STEC)retrieval and timing.For this reason,the PPP functional model is modified by taking into account the time-varying receiver code biases of the two frequencies.It is different from the Modified Carrier-to-Code Leveling(MCCL)method which can only obtain the variations of Receiver Differential Code Biases(RDCBs),i.e.,the difference between the two frequencies’code biases.In the Modified PPP(MPPP)model,the temporal variations of the receiver code biases become estimable and their adverse impacts on PPP parameters,such as ambiguity parameters,receiver clock offsets,and ionospheric delays,are mitigated.This is confirmed by undertaking numerical tests based on the real dual-frequency GPS data from a set of global continuously operating reference stations.The results imply that the variations of receiver code biases exhibit a correlation with the ambient temperature.With the modified functional model,an improvement by 42%to 96%is achieved in the Differences of STEC(DSTEC)compared to the original PPP model with regard to the reference values of those derived from the Geometry-Free(GF)carrier phase observations.The medium and long term(1×10^(4) to 1.5×10^(4) s)frequency stability of receiver clocks are also signifi-cantly improved.展开更多
基金Natural Sciences and Engineering Research Council of Canada(NSERC).
文摘Starting from 2016,the raw Global Navigation Satellite System(GNSS)measurements can be extracted from the Android Nougat(or later)operating systems.Since then,GNSS smartphone positioning has been given much attention.A high number of related publications indicates the importance of the research in this field,as it has been doing in recent years.Due to the cost-effectiveness of the GNSS smartphones,they can be employed in a wide variety of applications such as cadastral surveys,mapping surveying applications,vehicle and pedestrian navigation and etc.However,there are still some challenges regarding the noisy smartphone GNSS observations,the environment effect and smartphone holding modes and the algorithm development part which restrict the users to achieve high-precision smartphone positioning.In this review paper,we overview the research works carried out in this field with a focus on the following aspects:first,to provide a review of fundamental work on raw smartphone observations and quality assessment of GNSS observations from major smart devices including Google Pixel 4,Google Pixel 5,Xiaomi Mi 8 and Samsung Ultra S20 in terms of their signal strengths and carrier-phase continuities,second,to describe the current state of smartphone positioning research field until most recently in 2021 and,last,to summarize major challenges and opportunities in this filed.Finally,the paper is concluded with some remarks as well as future research perspectives.
基金the National Natural Science Foundation of China(No.41774034)the National Key Research and Development Program of China(No.2016YFB0501803,No.2017YFB0503402).
文摘A long-term analysis of signal-in-space range error (SISRE) is presented for all healthy Galileo satellites, and the first pair of full operational capability satellites in wrong elliptical orbits. Both orbit and clock errors for Galileo show an obvious convergence trend over time. The annual statistical analyses show that the average root mean squares (RMSs) of SISRE for the Galileo constellation are 0.58 m (2015), 0.29 m (2016), 0.23 m (2017), and 0.22 m (2018). Currently, the accuracy of the Galileo signal-in-space is superior to that of the global positioning system (GPS) Block IIF (0.35 m). In addition, the orbit error accounts for the majority of Galileo SISRE, while the clock error accounts for approximately one-third of SISRE due to the high stability of the onboard atomic clock. Single point positioning results show that Galileo achieves an accuracy of 2-3 m, which is comparable to that of GPS despite the smaller number of satellites and worse geometry. Interestingly, the vertical accuracy of Galileo, which uses the NeQuick ionospheric model, is higher than that of GPS. Positioning with single frequency E1 and E5 show a higher precision than E5a and E5b signals. Regarding precise point positioning (PPP), the results indicate that a comparable positioning accuracy can be achieved among different stations with the current Galileo constellation. For static PPP, the RMS values of Galileo-only solutions are within 1 cm horizontally, and the vertical RMSs are mostly within 2 cm horizontally. For kinematic PPP, the RMSs of Galileo-only solutions are mostly within 4 cm horizontally and 6 cm vertically.
基金the National Natural Science Foundation of China(Grant No.41774042)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(Grant No.YJKYYQ20190063)The first author is supported by the Chinese Academy of Sciences(CAS)Pioneer Hundred Talents Program.
文摘Precise Point Positioning(PPP),initially developed for the analysis of the Global Positing System(GPS)data from a large geodetic network,gradually becomes an effective tool for positioning,timing,remote sensing of atmospheric water vapor,and monitoring of Earth’s ionospheric Total Electron Content(TEC).The previous studies implicitly assumed that the receiver code biases stay constant over time in formulating the functional model of PPP.In this contribution,it is shown this assumption is not always valid and can lead to the degradation of PPP performance,especially for Slant TEC(STEC)retrieval and timing.For this reason,the PPP functional model is modified by taking into account the time-varying receiver code biases of the two frequencies.It is different from the Modified Carrier-to-Code Leveling(MCCL)method which can only obtain the variations of Receiver Differential Code Biases(RDCBs),i.e.,the difference between the two frequencies’code biases.In the Modified PPP(MPPP)model,the temporal variations of the receiver code biases become estimable and their adverse impacts on PPP parameters,such as ambiguity parameters,receiver clock offsets,and ionospheric delays,are mitigated.This is confirmed by undertaking numerical tests based on the real dual-frequency GPS data from a set of global continuously operating reference stations.The results imply that the variations of receiver code biases exhibit a correlation with the ambient temperature.With the modified functional model,an improvement by 42%to 96%is achieved in the Differences of STEC(DSTEC)compared to the original PPP model with regard to the reference values of those derived from the Geometry-Free(GF)carrier phase observations.The medium and long term(1×10^(4) to 1.5×10^(4) s)frequency stability of receiver clocks are also signifi-cantly improved.
