A closed-loop EKF and multi-failure diagnosis approach for cooperative GNSS positioning

Current cooperative positioning with global navigation satellite system (GNSS) for connected vehicle application mainly uses pseudorange measurements. However, the positioning accuracy offered cannot meet the requirements for lane-level positioning, collision avoidance and future automatic driving, which needs real-time positioning accuracy of better than 0.5 m. Furthermore, there is an apparent lack of research into the integrity issue for these new applications under emerging driverless vehicle applications. In order to overcome those problems, a new extended Kalman filter (EKF) and a multi-failure diagnosis algorithm are developed to process both GNSS pseudorange and carrier phase measurements. We first introduce a new closed-loop EKF with partial ambiguity resolution as feedback to address the low accuracy issue. Then a multi-failure diagnosis algorithm is proposed to improve integrity and reliability. The core of this new algorithm includes using Carrier phase-based Receiver Autonomous Integrity Monitoring method for failure detection, and the double extended w test detectors to identify failure. A cooperative positioning experiment was carried out to validate the proposed method. The results show that the proposed closed-loop EKF can provide highly accurate positioning, and the multi-failure diagnosis method is effective in detecting and identifying failures for both code and carrier phase measurements.     

Assessing Performance of Tomo-SAR and Backscattering Coefficient for Hemi-Boreal Forest Aboveground Biomass Estimation

Tomo-SAR technique has been used for hemi-boreal forest height and further forest biomass estimation through allometric equation. Backscattering coefficient especially in longer wavelength (L- or P-band) is thought as a useful parameter for hemi-boreal forest biomass retrieval. The aim of this paper is to assess the performance of vertical backscattering power and backscattering coefficient for hemi-boreal forest aboveground biomass (AGB) estimation with airborne P-band data. The test site locates in southern Sweden called Remningstorp test site, and the in-situ forest AGB ranges from 14 t/ha to 245 t/ha at stand level. Multi-baseline P-band Pol-InSAR data in repeat-path mode collected during March and May in 2007 at Remningstorp test site was used. We found that the correlation coefficient (R) between backscattering coefficient of P-band HH polarization and the in-situ forest biomass reached 0.87. The R for P-band VV backscattering power at 5 m is 0.71 and 10 m is 0.72. Backscattering coefficient in HH polarization and vertical backscattering power at 5 m and 10 m were applied to construct a model for hemi-boreal forest AGB estimation by backward step-wise regression and cross-validation approach. The results showed that the estimated forest AGB ranges from 19 to 240 t/ha, and the constructed model obtained a higher R and smaller RMSE, the value of R is 0.91, RMSE is 30.43 t/ha at Remningstorp test site.     

联系测量在地铁工程中的应用研究

城市地铁施工通常采用联系测量将平面位置、高程引入地下,常用一井定向与两井定向,本文结合工程实例在一井定向过程中采用连接三角形方法进行平面坐标系的传递,一方面在内业数据处理方中采用闭合导线约束平差的思想及方法进行处理,从而提高定向点点位精度;另一方面利用陀螺全站仪来加测地下导线边方位角的方法来提高井下定向边的定向精度.本...     

基于微信二维码的地图编码服务方法

针对当前微信二维码定位、导航和地图服务需要网络在线的问题,本文提出了基于微信二维码的地图编码服务方法,该方法直接将局部地图通过特征抽取和QR编码转换成微信二维码,实现了离线二维码地图服务。试验结果表明,该方法技术可行,地图编码效率能够满足大型楼宇、地下空间及交通枢纽等离线二维码地图应用服务,具有很好的应用前景。     

改进特征金字塔网络的遥感影像崩滑体提取

针对大多数网络存在精度低,特征冗余,计算量大,训练时间长等问题,提出密集连接特征金字塔网络(DCFPN),将特征提取网络得到的特征图通过一组并行深度可分离空洞卷积进一步计算其全局语义信息,并搭建解码上采样网络,加入连接组合特征层的结构,对遥感影像进行语义分割实现崩滑体提取,较好地解决了参数量过多,计算时间较长和精度较低等问题.通过特征金字塔网络(FPN)和DCFPN在崩滑体数据集上的大量对比实验表明,DCFPN在崩滑体语义分割方面有更高的精度并且计算量更少,训练时间更短,能够更好地为应急抢险工作.     

语素关联约束的动态环境视觉定位优化

在自动驾驶场景中,视觉相机能够实现低成本的定位与环境感知,但是场景中的动态目标会影响视觉定位的轨迹。对此,本文提出了语素关联约束的动态环境视觉定位优化方法。首先,利用目标检测和语义分割提取环境中的语义实体;然后,通过语素关联模型识别出动态语素;最后,建立动态语素的特征掩膜,用于特征匹配过程中的动态目标特征点过滤,从而提高视觉定位效果。本文基于视觉机器人平台在校园道路开展了试验,发现了动态目标通过关键点影响视觉定位结果的规律——在转弯时或者目标在视野中横向移动时影响较大。试验结果表明,本文方法的动态语义要素识别的平均精度F₁约为87%,并且在语素关联优化前后,局部区域最大轨迹距离差为2.463 m,与真值对比RMSE降低了38%。     

双目视觉与惯导融合的移动机器人定位方法

为了提高移动机器人的定位精度,提出一种双目视觉与惯导融合的视觉SLAM算法.在视觉SLAM前端部分,为了保持直接法计算速度快及特征法精度高的特点,提出一种融合直接法和特征法的半直接法双目视觉里程计.在后端优化阶段,将视觉数据与IMU数据相互融合,在滑动窗口中以非线性优化的方式构建误差函数,优化位姿计算精度.在EuRoc数据集中对本文提出的算法进行试验验证.结果表明,与开源的视觉惯导融合的SLAM系统OKVIS、ROVIO和VINS-Mono相比,本文系统在Machine Hal l与Vi con Room两个场景中的定位精度均得到了明显的提升,同时可以保持较高的运行效率.     

珞珈一号夜间灯光影像在建设用地提取中的应用:以武汉市为例

城市建设用地能够反映城市建设发展在地域空间上的分布形态,是规划主管部门监测城市建设和扩张的关键指标.2018-06-02发射的珞珈一号卫星可提供130 m分辨率的夜间灯光数据,在城市建设用地的提取方面具有较大潜力.首先整合珞珈一号夜间灯光影像与Landsat 8多光谱影像以及网络地图兴趣点数据;然后分别采用人类居住合成...     

房产测绘平面图系统的实现研究

随着城市规划管理的不断发展．使得城市房产测绘单位采用大型空间数据库管理测绘平面图资料成为必然。通过建立房产测绘平面图系统，可以有效地解决数据标准不一致．图数不能互访，测绘各部门无法协调一致等问题，充分发挥网络功能，提升整个城市的房产管理水平．达到房产管理和房产服务一体化的目标。本文详细论述了房产测绘平面图系统的概念、设计原则和系统功能．在南京数字房产共享平台的建设中得到了实现．并取得了良好的效果。     

FORMOSAT-3/COSMIC science mission update

The FORMOSAT-3/COSMIC mission is a microsatellite mission for weather forecast, climate monitoring, and atmospheric, ionospheric and geodesy research. This mission is a collaborative Taiwan-USA science experiment to deploy a constellation of six microsatellites in low Earth orbits. The mission life is 2 years with a goal of 5 years. The final mission orbit has an altitude of 750–800 km. Each satellite consists of three science payloads: global positioning system (GPS) occultation experiment (GOX) payload, tiny ionospheric photometer (TIP) and tri-band beacon (TBB). The GOX will collect the GPS signals for the study on atmosphere, ionosphere, and geodesy. The TIP and TBB can provide the electron distribution information for ionospheric research. The deployment of the FORMOSAT-3 constellation and the resulting influence on the occultation sounding distributions are reported. Details are also given on GOX, TIP, and TBB payload operations and the contributions of the Taiwan Science Team.