Integrated Navigation System and Experiment of a Low-Cost and Low-Accuracy SINS/GPS

When SINS (strap-down inertial navigation system) is combined with GPS, the observability of the course angle is weak. Although the course angle error is improved to some extent through Kalman filtering, the course angle still assumes a divergent trend. This trend is aggravated further when using low-cost and low-accuracy SINS. In order to restrain this trend, a method that uses AHRS to substitute for SINS course angle information is put forward aimed at the hardware component characteristic of the low-cost and low-accuracy SINS including AHRS (attitude and heading reference system) and IMU (inertial measurement unit). Real static and dynamic experiments show that the method can restrain the divergent trend of the navigation system angle effectively, and the positioning accuracy is high.     

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.     

A method to improve the alignment performance for GPS-IMU System

Zero velocity and zero east component of rotation rate relative to local geographic frame have been traditionally applied as measurements for fine alignment of a GPS-IMU system. The performance of the fine alignment, however, will be affected by several types of inertial sensor errors, which could cause part of the Kalman filter states to be unobservable. To overcome this problem, a new method that utilizes the total outputs of the gyro triad and the accelerometer triad as part of the measurements has been proposed by the authors. The initial results have confirmed the effectiveness of the method. In this paper, the observability for both traditional and new alignment methods will be first reviewed. The results from computer simulations will then be presented to compare the traditional and the new alignment methods for the purpose of evaluating the performance of the proposed new method. Data acquired from real inertial sensors will also be applied to assess the traditional and new alignment methods by analyzing their innovation sequences from the Klaman filter. Based on a paper presented at the 18th International Technical Meeting of the Satellite Division of the Institute of Navigation, Long Beach, California, September 2005.     

基于自适应Kalman滤波的BP神经网络及其在高程拟合中的应用

针对传统BP神经网络容易发散、泛化能力差等问题，采用自适应Kalman滤波方法训练神经网络的连接权。与Kalman滤波训练连接权和传统的BP算法相比，该方法提高了BP神经网络计算精度，增强了泛化能力。实测数据的计算结果证明了该方法的可行性与有效性。     

A filtering approach for estimating lake water quality from remote sensing data

In this paper we consider the estimation of lake water quality constituent distributions from hyperspectral remote sensing data. We present a computational approach that can be used to assimilate information from mathematical evolution models into data processing. The method is based on a reduced order iterated extended Kalman filter, and a convection–diffusion model is used to describe the movement of the water quality constituents. The performance of the technique is evaluated in a simulation study. The results show that the filter approach with an appropriate evolution model yields estimates that have better spatial and temporal resolutions than those obtained with conventional methods. Furthermore, the use of a feasible evolution model may make it possible to obtain information also on the concentrations in the lower parts of the lake.     

Robust biased estimation and its applications in geodetic adjustments

In this paper, a number of robust biased estimators (e.g. ordinary robust ridge estimator, robust principal components estimator, robust combined principal components estimator, robust single-parametric principal components estimator, robust root-root estimator) are established by means of a unified expression of biased estimators and based on the principle of equivalent weight. The most attractive advantage of these new estimators is that they can not only overcome the ill-conditioning of the normal equation but also have the ability to resist outliers. A numerical example is used to illustrate that these new estimators are much better than the least-squares estimator and various biased estimators even when both ill-conditioning and outliers exist. Received: 14 November 1995/Accepted: 11 February 1998     

随深度指数变化的视电阻率解

从横向均匀介质满足的基本方程出发,得到视电阻率核函数的一阶非线性微分方程,通过方程求解,并利用滤波系数法容易得到电阻率随深度任意变化的视电阻率问题。当各层介质电性结构随深度呈指数变化时,还可得到各层之间核函数的递推关系,这对实际介质的正反演问题都有重要意义和应用价值。     

A multiresolution hierarchical classification algorithm for filtering airborne LiDAR data

We presented a multiresolution hierarchical classification (MHC) algorithm for differentiating ground from non-ground LiDAR point cloud based on point residuals from the interpolated raster surface. MHC includes three levels of hierarchy, with the simultaneous increase of cell resolution and residual threshold from the low to the high level of the hierarchy. At each level, the surface is iteratively interpolated towards the ground using thin plate spline (TPS) until no ground points are classified, and the classified ground points are used to update the surface in the next iteration. 15 groups of benchmark dataset, provided by the International Society for Photogrammetry and Remote Sensing (ISPRS) commission, were used to compare the performance of MHC with those of the 17 other publicized filtering methods. Results indicated that MHC with the average total error and average Cohen’s kappa coefficient of 4.11% and 86.27% performs better than all other filtering methods.     

GAIM电离层同化方法进展

电离层是复杂的空间层结,其变化受太阳活动强度、地球磁场等因素影响。随着空间技术发展的需求,电离层天气变化成为目前空间天气预报最重要的内容之一。最近10年,人们利用卫星在电离层观测方面取得了重大进展,尤其引人注意的是:无线电掩星观测技术正走向应用的新阶段,加上已经建立的全球大量的地基GPS观测网,它们不仅为电离层动力学模式研究提供了丰富的电离层资料,而且为电离层预报提供了很好基础。因此,电离层天气预报成为当前重要的、前瞻性的研究方向,电离层资料同化是电离层预报最重要的研究内容之一。该文系统介绍这方面国际动态,重点是美国的USC/JPL和犹他州大学开展全球电离层同化模型研究、全球电离层同化研究的进展,以及在电离层天气预报中应用的初步成果。     

Reliability analysis of H-infinity control for a container ship in way-point tracking

Efficient control of ships in a designed trajectory is always a significant charge for ship maneuverings. The purpose of this paper is to design a robust H_∞ controller and a reliability analysis for a container ship in a way-point tracking. First, the H_∞ controller is designed for a container ship because of model parameters’ uncertainties and external disturbances such as waves, winds and ocean currents. Then, to evaluate the reliability of the designed controller, a well-known reliability analysis technique is employed to achieve the predefined heading angle overshoot (that is less than 20%) in way-point tracking. To do this, three random variables including wind speed, wind direction and wave direction are considered as the inputs due to their significant effect on overshoot, compared to other variables. The results demonstrate the capability of the designed H_∞ controller against modeling uncertainties and external disturbances in way point tracking control.