A Novel Approach of Using Selected Unconventional Geodesic Methods of Estimation on VTS Areas

Abstract

The Vessel Traffic Service (VTS) systems belong to the fundamental tools used in ensuring a high level of safety across sea basins with heavy traffic, where the presence of navigational hazards poses a great risk of collision or a ship running aground. In order to determine the mutual location of ships, VTS systems obtain information from different facilities, such as coastal radar stations, AIS, and vision systems. Fixing a ship’s position is always accompanied by a degree of error, but the degree of error depends on the specific position fixing system used. In order to increase the accuracy of position fixing in VTS systems, the authors propose the use of contemporary geodetic methods. The article presents the theoretical fundamentals of two unconventional geodesic methods of estimation: M estimation and M_split(q)estimation and the authors’ own proposal of their application in VTS systems. The article concludes with a test verifying theoretical assumptions, performed with the use of a computer application allowing position fixing with the use of selected robust adjustment methods. Furthermore, an example is presented of M_split(q)estimation as used for the acquisition of low-signal radar echoes, which in VTS systems are not automatically identified for tracking. The level of the echo signal makes it difficult for a VTS controller to separate these objects from typical radar noise and interference.     

Solution of the inverse geodetic problem for navigation

Abstract

Simplified geodetic formulas for very long and medium geodesies used in the sea and air navigation as well as methodology and formulas for investigating errors involved in these simplifictions for any hyperbolic system are presented.     

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Vision-based system of AUV for an underwater pipeline tracker

This paper describes a new framework for detection and tracking of underwater pipeline,which includes software system and hardware system.It is designed for vision system of AUV based on monocular CCD camera.First,the real-time data flow from image capture card is pre-processed and pipeline features are extracted for navigation.The region saturation degree is advanced to remove false edge point group after Sobel operation.An appropriate way is proposed to clear the disturbance around the peak point in the process of Hough transform.Second,the continuity of pipeline layout is taken into account to improve the efficiency of line extraction.Once the line information has been obtained,the reference zone is predicted by Kalman filter.It denotes the possible appearance position of the pipeline in the image.Kalman filter is used to estimate this position in next frame so that the information of pipeline of each frame can be known in advance.Results obtained on real optic vision data in tank experiment are displayed and discussed.They show that the proposed system can detect and track the underwater pipeline online,and is effective and feasible.     

广东吴川吴阳古沉船为明代古船文献考析

广东吴川吴阳镇是国家级的历史文化名镇,境内历史文物众多.因濒临南海,自古为雷州半岛与外界交往的海洋通道.据考察研究及文物普查,该镇存在着一处古沉船遗址.沉船年代未明,一说为唐宋船,一说为近代外国船.通过民俗、历史地理遗迹调查,结合相关历史文献,论证吴阳古沉船为明代古船的可能性,甚至为17世纪荷兰古沉船.古沉船的历史信息不仅丰富了雷州半岛与域外交往的历史,而且为今后进一步开展雷州半岛航海史考古特别是古沉船考古奠定了文献基础     

建设湛江海员人才强市问题探析

分析了建设湛江海员人才强市的战略意义和有利条件,以及建设过程中必须解决的问题,在此基础上分别从营造航海文化氛围、完善海员服务和管理体系、构建校企互动机制、加强航海专业师资建设和实施质量兴校战略等方面提出建设湛江海员强市应采取的对策     

基于地磁场的自主导航研究

研究了基于地磁场的自主导航,建立了以卫星轨道动力学方程为基础的系统状态方程,并详细推导了以地磁场大小和地磁场矢量为观测量时的观测方程.由于系统的非线性,传统的卡尔曼滤波无能为力,为了解决系统的非线性问题把常用来解决非线性问题的EKF引入到基于地磁场的自主导航系统中.最后用Matlab对基于地磁场的自主导航系统进行了仿真,仿真结果表明EKF有很好的收敛性和稳定性,以地磁场矢量为观测量的导航精度要远高于以地磁场大小为观测量的导航精度.     

基于相关分析的组合导航RAIM模型研究

探讨基于相关分析理论的组合导航RIAM方法,并给出单个和多个探测粗差的相关分析检验流程。通过模拟12颗GPS和Galileo组合导航卫星定位系统,分别给单颗和两颗正常卫星加入粗差。仿真结果表明：观测值的影响向量与残差的相关系数可以定位含粗差的卫星并将粗差卫星予以剔除。     

Acquisition of Directional Parameters in Aerial Images Based on DEM Data

1　Extraction of the steep curve mapThe steep curve is defined as connection linefrom zero cross points which are produced fromthe convolution of Laplace ( LOG) filtration toDEM. Firstly, the elevation data from DEM areprocessed with LOG convolution and zero cross.The sampling formula is 2G(i,j) =12πσ6(r2 -2σ2)e-r2/2σ2 (1)where -M≤i≤M,-M≤j≤M,r2=i2+j2; M isthe filtration radius, nearly equaling to 5.1σ2; pre diction errorσis set to 4. Suppose that e[i,j] is asmall …