Position and velocity reliability testing in degraded GPS signal environments

Reliability testing, namely receiver autonomous integrity monitoring (RAIM), consists of statistical testing of least-squares residuals of observations, e.g., on an epoch-by-epoch basis aiming towards reliable navigation fault detection and exclusion (FDE). In this paper, classic RAIM and FDE methods are extended with testing of range-rate residuals to find inconsistent velocity solutions in order to contribute to the reliability of the system with special focus on degraded signal environments. Reliability enhancement efforts discussed include a Backward-FDE scheme based on statistical outlier detection and an iteratively reweighted robust estimation technique, a modified Danish method. In addition, measurement weighting assigned to code and Doppler observations is assessed in the paper in order to allow fitting a priori variance models to the estimation processes. The schemes discussed are also suitable in terms of computational convenience for a combined GPS/Galileo system. The objective of this paper is to assess position and velocity reliability testing and enhancement in urban and indoor conditions and to analyze the navigation accuracy conditions with high sensitivity GPS (HSGPS) tests. The results show the necessity of weighted estimation and FDE for reliability enhancement in degraded signal-environment navigation.     

Reliability checking for GNSS baseline and network processing

Reliability analysis is inseparably connected with the formulation of failure scenarios, and common test statistics are based on specific assumptions. This is easily overlooked when processing observation differences. Poor failure identification performance and misleading pre-analysis results, mainly meaningless minimum detectable biases and external reliability measures, are the consequence. A reasonable failure scenario for use with differenced GNSS observations is formulated which takes into account that individual outliers in the original data affect more than one processed observation. The proper test statistics and reliability indicators are given for use with correlated observations and both batch processing and Kalman filtering. It is also shown that standardized residuals and redundancy numbers fail completely when used with double differenced observations.

地面地下空间信息采集车及试验结果

介绍地面地下空间信息采集车的原理和结构,给出了利用GPS-RTK辅以全站仪和地下管线探测仪实现地下管线勘、测、管一体化的原理,以及获取管线三维坐标的数学模型。通过试验验证了地面地下空间信息采集车的可行性,其精度满足《城市地下管线探测技术规程》的要求。     

无控制DEM表面差异探测研究

本文提出了一个新的无控制DEM差异探测算法。它可以将不同时期获取的DEM纳入到统一坐标系中,这样就可以根据匹配后的DEM来定量探测地表变化情况。该方法通过差分模型考虑了观测量的数值及其相互关系。与目前差异探测能力最强的LMS-LZD方法相比,新方法具有更好的差异能力和更高的匹配精度。普歪沟泥石流沟多时相DEM差异探测实例验证了新方法的优越性。     

基于MODIS 250m遥感影像的变化检测

本文采用分辨率为250m的MODIS遥感影像对土地利用类型进行动态监测,其目的是探讨在MODIS影像上,能够快速准确地获取在不同时期的变化信息,并且为进一步分析提供参考。本文主要讨论运用MODIS影像进行变化检测的几个方面:一是相对辐射校正;二是变化区域的确定,采用基于像素的阈值分割和基于区域的松弛法进来确认变化/非变化像元,并提出一种基于缓冲区方法来消除部分伪变化信息;三是精度评价,根据MO-DIS高时相的特点,本文提出了基于缺少实地观测数据情况下的精度评价。     

TM影像的变化检测方法探究

变化检测是遥感应用中的一项重要内容。随着遥感技术的发展,变化检测技术也有了很大的进步,出现了很多的研究方法和研究成果。本文在总结前人研究的基础上,提出了TM影像变化检测的基本流程,并简单介绍了各个流程,包括数据预处理、变化信息的提取以及变化区域的确定,重点介绍了变化检测的方法尤其是目前最新的研究方法,最后对变化检测的前景提出了展望。     

GNSS周跳探测与修复方法研究

在GNSS载波相位测量中,周跳的探测与修复一直是个重要问题。主要研究了GPS和GNONASS周跳的探测方法,针对相位减伪距法、电离层残差法和M—W组合法三种周跳探测与修复的方法,展开了系统的研究,利用Matlab编程分别予以实现。并利用实测数据进行分析比较,详细探讨和验证了三种方法的优缺点,为三种方法的实际应用提供有力的科学依据。     

雷达CFAR检测的仿真研究

杂波背景中区分出有用目标回波的恒虚警(CFAR)检测技术,是直接影响雷达性能的关键技术之一。主要研究了CFAR检测的基本理论,重点研究了ML类CFAR算法中的邻近单元平均恒虚警(CA-CFAR)的检测算法,推导了其检测概率和虚警概率表达式,通过计算机仿真比较了在不同窗长情况下的检测门限。     

利用二维恒虚警进行非均匀噪声背景下的目标检测

针对高频地波雷达中的非均匀噪声环境及各种干扰源时变的特点,提出构建一种时变白化滤波器。先对非均匀噪声环境进行白化处理,然后在一维恒虚警的基础上,采用一种基于多普勒频率和距离的二维恒虚警处理算法。实验结果表明,利用时变白化滤波进行处理后,再在距离和多普勒频率维同时进行恒虚警检测,可以得到较好的检测结果。