Application of Adaptive Kalman Filtering Algorithm in IMU/GPS Integrated Navigation System

The IMU(inertial measurement unit) error equations in the earth fixed coordinates are introduced firstly. A fading Kalman filtering is simply introduced and its shortcomings are analyzed, then an adaptive filtering is applied in IMU/GPS integrated navigation system, in which the adaptive factor is replaced by the fading factor. A practical example is given. The results prove that the adaptive filter combined with the fading factor is valid and reliable when applied in IMU/GPS integrated navigation system.     

Calibration for CHAMP Accelerometer Data Based on Crossover Points of the Satellite

The German CHAlleging Minisatellite Payload （CHAMP） was launched in July 2000. It is the first satellite that provides us with position and accelerometer measurements, with which the gravity field model can be determined. One of the most popular methods for geopotential recovery using the position and accelerometer measurements of CHAMP is the energy conservation method, The main aim of this paper is to determine the scale and bias parameters of CHAMP accelerometer data using the energy conservation method. The basic principle and mathematical model using the crossover points of CHAMP orbit to calibrate the accelerometer data are given based on the energy balance method. The rigorous integral formula as well as its discrete form of the observational equation is presented, This method can be used to estimate only one of the scale and bias parameters or both of them. In order to control the influence of outliers, the robust estimator for the calibration parameters is given. The results of the numerical computations and comparisons using the CHAMP accelerometer data show the validity of the method.     

Numerical prediction methods for clock deviation based on two-way satellite time and frequency transfer data

Three functional models, polynomial, spectral analysis, and modified AR model, are studied and compared in fitting and predicting clock deviation based on the data sequence derived from two-way satellite time and frequency transfer. A robust equivalent weight is applied, which controls the significant influence of outlying observations. Some conclusions show that the prediction precision of robust estimation is better than that of LS. The prediction precision calculated from smoothed observations is higher than that calculated from sampling observations. As a count of the obvious period variations in the clock deviation sequence, the predicted values of polynomial model are implausible. The prediction precision of spectral analysis model is very low, but the principal periods can be determined. The prediction RMS of 6-hour extrapolation interval is Ins or so, when modified AR model is used.     

Pattern detection in airborne LiDAR data using Laplacian of Gaussian filter

Methods for feature detection in laser scanning data have been studied for decades ever since the emergence of the technology.However,it is still one of the unsolved problems in LiDAR data processing due to difficulty of texture and structure information extraction in unevenly sampled points.The paper analyzes the characteristics of Laplacian of Gaussian(LoG) Filter and its potential use for structure detection in LiDAR data.A feature detection method based on LoG filtering is presented and ex-perimented on the unstructured points.The method filters the elevation value(namely,z coordinate value) of each point by convo-lution using LoG kernel within its local area and derives patterns suggesting the existence of certain types of ground ob-jects/features.The experiments are carried on a point cloud dataset acquired from a neighborhood area.The results demonstrate patterns detected at different scales and the relationship between standard deviation that defines LoG kernel and neighborhood size,which specifies the local area that is analyzed.     

Analysis of systematic error influences on accuracy of airborne laser scanning altimetry

The error sources related to the laser rangefinder, GPS and INS are analyzed in details. Several coordinates systems used in airborne laser scanning are set up, and then the basic formula of system is given.This paper emphasizes on discussing the kinematic offset correction between GPS antenna phase center and laser fired point. And kinematic time delay influence on laser footprint position, the ranging errors, positioning errors, attitude errors and integration errors of the system are also explored. Finally, the result shows that thekinematic time delay can be neglected as compared with other error sources. The accuracy of the coordinates is not only influenced by the amplitude of the error, but also controlled by the operation parameters such as flight height, scanning angle amplitude and attitude magnitude of the platform.     

Analysis and Representation of Changes in Change Detection

In this paper,factors lead to changes ande what changes should be considered are firstly discussed.then changes to be represented by set theory is given.Twelve basic change types are described in detail.At last the paper points out that the change between geoobjects and pixels in images is not all corresponging and it causes the difficulty of accurate and robust change detection techniques.     

Filter Method and Its Consistency of Double-Star Position/SINS Integrated System

According to the characteristic of Beidou Double-star positing system (for short: Double-star position), the optimal predication model of Double-star position/SINS integrated system is put forward, which can make use of the delayed position in-formation from Double-star positioning system to predicate optimally for the integrated system, and then to correct SINS, and af-fords integrated results of some navigation parameters. In order to validate the consistency of the filter, the criteria for consistency of a filter is also studied, and the tested statistics are given, the experiment based on practical measured data shows that the filtering method is consistent with the integrated system.     

Distribution of Large Volume Image Data Using the Mixed Mode of Java Servlet and COM on Web

This paper reports some researches on distribution of large volume image data using techniques of the Mixed Mode of Java Servlet and COM on Web. The architecture and key technologies are discussed in detail. The web distribution system of image is implemented and the system is tested by the application instances. At last, the advantages and disadvantages for this web image distribution mode are analyzed.     

武汉地区GPS气象网试验研究 (英文)

There are three aspects in the study of GPS meteorology network in the Wuhan region. The first is the comparison of the GPS precipitable water vapor between final ephemeris and ultra-rapid ephemeris for which the relative coefficient is 99.97 and the root mean squares is 0.048 mm. It can be concluded that ultra-rapid ephemeris can be used to get the GPS precipitable water vapor for the real-time prediction. The second is the comparison of precipitable water vapor of GPS stations and the distribution of water vapor in the Wuhan region is acquired. The change of GPS precipitable water vapor and rainfall in a rainfall process are compared and analyzed. The change of GPS precipitable water vapor can reflect and predict the process of rainfall.     

Reparameterization of single difference and undifferenced kinematic GPS positioning models

A series of advantages of single difference(SD)and undifferenced(ZD)models are given as compared with the double difference(DD)model.However,rank defects exist in SD and ZD models.The reparameterization method is provided to resolve this rank defect problem by estimating some combinations of the unknowns rather than the unknowns themselves.The reparameterization of SD and ZD functional models is discussed in detail with their stochastic models.The theoretical confirmation of the equivalence of undifferenced and differenced models is described in a straightforward way.The relationship between SD and ZD residuals is given and verified for some special purposes,e.g.research on the stochastical properties of GPS observations.     

两种渐消滤波与自适应抗差滤波的综合比较分析

给出了两种渐消滤波解及其相应的原则，介绍了自适应抗差滤波原理和相应的解，分别从原理和解的表达式上分析了两种渐消滤波和自适应抗差滤波解算的基本性能。利用一个实际算例比较了渐消滤波与自适应抗差滤波解在控制状态异常影响方面的能力。     

Comparison of Two Fading Filters anc Adaptively Robust Filter

Two kinds of fading filters and their principles are introduced. An adaptive robust filter is given with corresponding principle. The basic abilities of the fading filters and adaptively robust filter in controlling the influences of the kinematic model errors are analyzed. A practical example is given. The results of the fading filter and adaptively robust filter are compared and analyzed.     

Comparison of two fading filters and adaptively robust filter

Two kinds of fading filters and their principles are introduced. An adaptive robust filter is given with corresponding principle. The basic abilities of the fading filters and adaptively robust filter in controlling the influences of the kinematic model errors are analyzed. A practical example is given. The results of the fading filter and adaptively robust filter are compared and analyzed.     

IMU/GPS组合导航系统自适应Kalman滤波算法

给出了IMU在地固坐标系中的误差方程，介绍并分析了自适应滤波和渐消Kalman滤波算法原理，然后将渐消因子引入到自适应滤波算法中。并将其应用到IMU／GPS松组合导航系统中，最后利用一个实际算例证明了该组合导航系统的有效性。     

多种有色噪声自适应滤波算法的比较

将控制有色噪声影响的自适应滤波算法分为函数模型补偿滤波和随机模型补偿滤波两类。在介绍各种自适应滤波理论和模型的基础上，重点分析了各种自适应滤波算法的优缺点，并用实际算例进行了验证。     

多源传感器动、静态滤波融合导航

首先给出联邦滤波各局部输出量之间的相关协方差矩阵，进而给出了基于各传感器独立观测信息的动、静态滤波解法，这种解法避免了重复使用载体状态方程信息的问题，保证了多传感器数据融合的最优性，而且很容易扩展到抗差滤波和自适应滤波融合。     

中国大地测量数据处理60年重要进展 第二部分:大地测量参数估计理论与方法的主要进展

大地测量参数估计原理是大地测量数据处理的重要基础。中国学者经过60年不懈努力,在自由网平差、拟稳平差、半参数估计、不适定问题解算方法、抗差估计、自适应滤波等领域做出了重要贡献,建立了许多新的理论、模型和方法,推进了大地测量数据处理理论的进展。这一部分重点介绍建国60年来中国学者在大地测量数据处理原理、方法方面取得的成就。     

Adaptive estimation of multiple fading factors in Kalman filter for navigation applications

Kalman filter is the most frequently used algorithm in navigation applications. A conventional Kalman filter (CKF) assumes that the statistics of the system noise are given. As long as the noise characteristics are correctly known, the filter will produce optimal estimates for system states. However, the system noise characteristics are not always exactly known, leading to degradation in filter performance. Under some extreme conditions, incorrectly specified system noise characteristics may even cause instability and divergence. Many researchers have proposed to introduce a fading factor into the Kalman filtering to keep the filter stable. Accordingly various adaptive Kalman filters are developed to estimate the fading factor. However, the estimation of multiple fading factors is a very complicated, and yet still open problem. A new approach to adaptive estimation of multiple fading factors in the Kalman filter for navigation applications is presented in this paper. The proposed approach is based on the assumption that, under optimal estimation conditions, the residuals of the Kalman filter are Gaussian white noises with a zero mean. The fading factors are computed and then applied to the predicted covariance matrix, along with the statistical evaluation of the filter residuals using a Chi-square test. The approach is tested using both GPS standalone and integrated GPS/INS navigation systems. The results show that the proposed approach can significantly improve the filter performance and has the ability to restrain the filtering divergence even when system noise attributes are inaccurate.     

Real-time estimation of satellite clock offset using adaptively robust Kalman filter with classified adaptive factors

In order to estimate the satellite clock offset in a real-time mode, a new algorithm of adaptively robust Kalman filter with classified adaptive factors for clock offset estimation is proposed. Compared with standard Kalman filter clock offset model, the new method can detect and control outliers and clock jumps automatically in real-time. Moreover, the clock model parameters, which contain the clock offset, clock speed and clock shift, are classified to decide the adaptive factors in the new model. Thus, clock jumps with different characteristics can be distinguished more effectively. Meanwhile, the dynamic noise characteristics of clock offset series are used for stochastic modeling. An actual numerical example is presented, which shows that the proposed filter can give a better performance than other commonly used filters.