基于MapX的阵列功能的设计与实现

首先讨论了在直角坐标系和地理坐标系下阵列功能的算法原理,详细介绍了基于Delphi和MapX的地理坐标系下阵列功能的设计和算法实现过程。此功能扩展了MapInfo的数字化功能,在一定程度上提高了数字化的效率和精度。     

压缩型抗差估计

讨论了测量平差中粗差和病态性同时存在时的参数估计问题。针对抗差估计不能抗拒病态性干扰的缺点,运用有偏然计的压缩变换方法,提出了一种新的估计－压缩型抗差估计,理论分析和模拟计算表明,新估计不但能有效的减免粗差的影响,而且能显著的作病态性的干扰,是一种性能良好的估计。     

Stationary spatially modulated fourier transform spectro-radiometer

Journal of the Indian Society of Remote Sensing - A stationary, compact, spatially modulated Fourier Transform spectro-radiometer based on triangular, common path Sagnac interferometer has been...     

Performance of rate detector algorithms for an integrated GPS/INS system in the presence of slowly growing error

In the Global Positioning System, there is no provision for real-time integrity information within the Standard Positioning Service, by design. However, in safety critical sectors like aviation, stringent integrity performance requirements must be met. This can be achieved using the special augmentation systems or RAIM (Receiver Autonomous Integrity Monitoring) or both. RAIM, the most cost-effective method relies on data consistency, and therefore requires redundant measurements for its operation. An external aid to provide this redundancy can be in the form of an Inertial Navigation system. This should enable continued performance even when no redundant satellite measurements are available. An algorithm presented in previous papers by the authors detects the rate of slowly growing errors. The algorithm was shown to be effective for early detection of slowly growing errors that belong to the class of most difficult to detect errors. Firstly, rate detector is tested for varying faults. Secondly, real data are used to validate the rate detector algorithm. The data are extensively analyzed to ascertain whether it is suitable for integrity and fault diagnostics. A modification to the original rate detector algorithm is suggested by addition of a bias state to the dynamic model. The performance is then compared with the existing techniques and substantial improvement is shown.     

Modelling and Remote Sensing of Land Surface Temperature in Turkey

This study introduces artificial neural networks (ANNs) for the estimation of land surface temperature (LST) using meteorological and geographical data in Turkey (26?C45°E and 36?C42°N). A generalized regression neural network (GRNN) was used in the network. In order to train the neural network, meteorological and geographical data for the period from January 2002 to December 2002 for 10 stations (Adana, Afyon, Ankara, Eski?ehir, ?stanbul, ?zmir, Konya, Malatya, Rize, Sivas) spread over Turkey were used as training (six stations) and testing (four stations) data. Latitude, longitude, elevation and mean air temperature are used in the input layer of the network. Land surface temperature is the output. However, land surface temperature has been estimated as monthly mean by using NOAA-AVHRR satellite data in the thermal range over 10 stations in Turkey. The RMSE between the estimated and ground values for monthly mean with ANN temperature(LST_ANN) and Becker and Li temperature(LST_B-L) method values have been found as 0.077?K and 0.091?K (training stations), 0.045?K and 0.003?K (testing stations), respectively.     

实时精密单点定位中的数据预处理研究

提出了适用于实时环境的一套数据预处理方案,包括钟跳修复、联合使用Geometry-Free和Melbourne-Wübbena组合进行周跳探测。通过丰富的实验算例,说明了对观测值进行钟跳修复的必要性;证明了联合使用GF与MW组合能够准确有效地探测出实际数据中存在的以及手工模拟加入的周跳。     

观测有效性的度量方法

基于Hilbert空间理论,通过对观测方程的系数阵实施格拉姆-施密特(Gram-Schmidt,G-S)正交化过程,分析观测的两个特性,从一个新的角度论证了参数估计的必要观测问题,以及多余观测与必要观测的关系;用欧氏范数‖·‖2和Frobenius‖·‖_F范数作为基本度量工具对观测提供参数估计的信息量进行度量分析,研究观测的有效性和参数估计的可靠性。采用观测空间分析方法研究了测绘学科中必要观测、多余观测等基本概念;提出了观测信息量、观测有效性的概念和相应的度量方法;从观测的空间结构出发分析参数估计系统的可靠性,从一个侧面扩展和丰富了测绘学中的可靠性理论;丰富了研究测绘学中一些基本问题的分析方法,也为信息学中的数据挖掘问题提供了一种分析思路。     

HD-STGPS超站仪数据通信的实现

介绍了HD－STGPS超站仪的数据电台和GSM两种数据通信的设计，讨论了GPS数据通信的协议和程序实现方法。     

Use of the L2C signal for inversions of GPS radio occultation data in the neutral atmosphere

Results from processing FORMOSAT-3/COSMIC radio occultations (RO) with the new GPS L2C signal acquired both in phase locked loop (PLL) and open loop (OL) modes are presented. Analysis of L2P, L2C, and L1CA signals acquired in PLL mode shows that in the presence of strong ionospheric scintillation not only L2P tracking, but also L1CA tracking often fails, while L2C tracking is most stable. The use of L2C improves current RO processing in the neutral atmosphere mainly by increasing the number of processed occultations (due to significant reduction in the number of L2 tracking failures) and marginally by a reduction in noise in statistics. The latter is due to the combination of reduced L2C noise (compared to L2P) and increased L1CA noise in those occultations where L2P would have failed. This result suggests application of OL tracking for L1CA and L2C signals throughout an entire occultation to optimally acquire RO data. Two methods of concurrent processing of L1CA and L2C RO signals are considered. Based on testing of individual occultations, these methods allow: (1) reduction in uncertainty of bending angles retrieved by wave optics in the lower troposphere and (2) reduction in small-scale residual errors of the ionospheric correction in the stratosphere.