Riegl VZ-400三维激光扫描仪数据的建模的研究

三维激光扫描技术是近年来发展起来的一门新技术,其在众多领域中有非常广阔的应用前景。本文介绍了三维激光扫描仪目前的应用现状,以及原理和数据后处理方法。最后通过青海玉树山体建模实例叙述了Riegl VZ-400扫描仪如何获取数据、点云数据的拼接及三维模型的建立。     

基于网站群理念和架构的国家土地督察网站群建设实践

随着政府网站的建设和发展,网站群已成为电子政务发展的一种新模式。本文对立足于网站群理念和架构的国家土地督察网站群的建设实践进行了介绍,详解了国家土地督察网站群建设思想、建设原则、总体框架、技术路线、信息分类和栏目规划等。国家土地督察网站群为政府网站群的建设积累了有益经验。     

三频精密单点定位观测模型初探

三频观测值为导航定位提供了更多的观测值组合选择。在利用载波相位三频线性组合消除一阶电离层误差的基础上,对组合模糊度为实数和整数两种情况下的二阶电离层误差及观测噪声水平进行了分析,获得了几种适用于精密单点定位的三频观测值组合。     

遥感影像快速纠正系统的设计与实现

深入分析了传统遥感影像纠正处理工作中存在的问题,提出了以基础地理信息数据库为基础、基于网络环境的协同作业模式,解决了传统遥感影像纠正处理工作中资料准备工作量大、控制点采集效率低以及数据安全等问题。介绍了系统技术架构、设计与技术实现,为实现遥感影像快速纠正提出了切实可行的技术方案。     

Robust Kalman filtering based on Mahalanobis distance as outlier judging criterion

A robust Kalman filter scheme is proposed to resist the influence of the outliers in the observations. Two kinds of observation error are studied, i.e., the outliers in the actual observations and the heavy-tailed distribution of the observation noise. Either of the two kinds of errors can seriously degrade the performance of the standard Kalman filter. In the proposed method, a judging index is defined as the square of the Mahalanobis distance from the observation to its prediction. By assuming that the observation is Gaussian distributed with the mean and covariance being the observation prediction and its associate covariance, the judging index should be Chi-square distributed with the dimension of the observation vector as the degree of freedom. Hypothesis test is performed to the actual observation by treating the above Gaussian distribution as the null hypothesis and the judging index as the test statistic. If the null hypothesis should be rejected, it is concluded that outliers exist in the observations. In the presence of outliers scaling factors can be introduced to rescale the covariance of the observation noise or of the innovation vector, both resulting in a decreased filter gain. And the scaling factors can be solved using the Newton’s iterative method or in an analytical manner. The harmful influence of either of the two kinds of errors can be effectively resisted in the proposed method, so robustness can be achieved. Moreover, as the number of iterations needed in the iterative method may be rather large, the analytically calculated scaling factor should be preferred.     

A GNSS interference identification using an adaptive cascading IIR notch filter

A low-complexity time-domain approach for global navigation satellite systems is proposed to detect and identify single-tone, multi-tone, swept continuous wave interference (CWI) and band-limited white Gaussian noise (BLWN). An adaptive notch filter and adaptive cascading filter structure are employed to identify the type of interference signals. The number of the cascading stages is selected by comparing the total power in receiver bandpass, and after, passing the adaptive notch filter. For this reason, the proposed filter structure is more efficient in identifying and mitigating interference signals than the conventional filter structure. In addition, the automatic gain control gain is used to detect the existence of continuous wave interference. The performance of the interference detection and identification method is evaluated for the cases of GPS signal in the presence of single-tone, multi-tone, swept CWI and BLWN.     

基于GEOWAY CIPS大比例尺正射影像快速生产的方法研究

面对经济社会发展急需大量影像数据支撑的现状,本文提出了基于GEOWAY CIPS大比例尺正射影像快速生产的方法,分析了基于GEOWAY CIPS影像处理的关键技术流程,总结了该生产流程的优势与不足,并通过实际项目,验证了本文生产方法的高效性与可靠性。     

Error analysis of the 3D similarity coordinate transformation

The 3D similarity coordinate transformation with the Gauss–Helmert error model is investigated. The first-order error analysis of an analytical least-squares solution to this problem is developed in detail. While additive errors are assumed in the translation and scale estimates, a 3 × 1 multiplicative error vector is defined to effectively parameterize the rotation matrix estimation error. The propagation of the errors in the coordinate measurements to the errors in the estimated transformation parameters is derived step-by-step, and the formulae for calculating the variance–covariance matrix of the estimated parameters are presented.