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936 JOURNAL OF SOFTWARE, VOL. 6, NO. 5, MAY 2011 unified service interfaces to access different resources. The main workload for a USP user willing to deploy Grid resources is realizing the native methods and configuring the resource database. The resources under USP can be deloyed/undeployed dynamically. Besides the common client stub which can directly invoke the unified service published by USP, users can also achieve the proxy client through resource query&deploy service. The proxy client and proxy notifier could greatly facilitate the service users. The final experiment proofs that the service performance under USP is acceptable for Grid applications and development workload reduce a lot. This paper only proposes a prototype. The future works include management of the third-party resources used by RR, GUI for USP users, high QoS of USP, and so on. ACKNOWLEDGMENT The authors wish to thank Dr. Xianguo Meng from Dept.2 of Mechanical Engineering College. REFERENCE [1] http://www.globus.org/toolkit/.(2010-10-11) [2] �� http://gdp.globus.org/gt4-tutorial/.(2010-2-5) [3] http://tomcat.apache.org. (2010-2-5) [4] Ken Arnold, Jams Gosling, David Holmes. The Java TM Programming Language, Fourth Edition. Pearson Education, Inc. 2006 [5] http://mage.uni-marburg.de/trac/gdt/wiki. (2009-12-3) [6] T. Friese, M. Smith, and B. Freisleben. GDT:A Toolkit for Grid Service Development. In Proc. of the 3rd International Conference on Grid Service Engineering and Management, pages 131-148, 2006 [7] M. Smith, T. Friese, and B. Freisleben. Intra-Engine Service Security for Grids Based on WSRF. In Proceedings of the 2005 IEEE International Symposium on Cluster Computing and Grid ��s 644-653, 2005. [8] Kay Dornemann and Bernd Freisleben. Discovering Grid Resources and Deploying Grid Services Using Peer-to-Peer Technologies. In Proceedings of the 2009 International Conference on Advanced Information Networking and Applications Workshops, pages 292-297, 2009 [9] Eun-Kyu Byunt, Jae-Wan Jangt, Wook Jungt et al. A Dynamic Grid Services Deployment Mechanism for On-Demand Resource © 2011 ACADEMY PUBLISHER Provisioning. In Proceedings of the 2005 IEEE International Symposium on Cluster Computing and the Grid, pages 863-870, 2005 [10] Jon B. Weissman, Seonho Kim, and Darin England, Supporting the Grid Service Dynamic Lifecycle. In Proceedings of the 2005 IEEE International on Cluster Symposium and Computing the Grid, pages 808- 815,2005 [11] Fu Qiang Li, Bin Gong, Cheng Xing. Dynamic Visualization Service Deployment in Grid Scientific Workflow. In Proceedings of the 2008 Seventh International Conference on Grid and Cooperative Computing, pages 201-205, 2008 [12] Pu Liu, Michael J. Lewis. Unified Dynamic Deployment of Web and Grid Services. In the Proceedings of 2007 IEEE Conference on Web Service, pages 26-34, 2007 [13] L. Qi, H. Jin, I. Foster, and J. Gawor. HAND: Highly Available Dynamic Deployment Infrastructure for Globus Toolkit 4. In the Proceedings of 15th EUROMICRO International Conference on Parallel, Distributed and Network-Based Processing, pages155-162, 2007 [14] Shaochong Feng, Yanqiang Di, Yuanchang Zhu, et al. Developing WSRF-Based Web Service RTI Using GT4. In Proceedings of 2009 First International Workshop on Education Technology and Computer Science, pages 1066-1069, 2009 [15] Feriese,Thomas.��-�� [Doctoral dissertation], Fachbereich Mathmatik und Informatik Universit Marburg ,2006 Shaochong Feng was born in Hebei, China. He receives his Master�s degree in Guidance, Navigation and Control from Mechanical Engineering College in 2007. His technical interests include distributed modeling and simulation, Grid computing and Cloud computing. Yuanchang Zhu was born in Heilongjiang, China. He received the B.A., M.A., and Ph.D in 1982, 1988 and 2005. He is a professor at Mechanical Engineering College. His study interests include M&S, Cloud Computing and so on. Yanqiang Di was born in Hebei, China. He received the B.A., M.A., and Ph.D in 1995, 1998 and 2009. He is a teacher at Mechanical Engineering College. His study interests include M&S, Grid Computing and database system.
JOURNAL OF SOFTWARE, VOL. 6, NO. 5, MAY 2011 937 Research on an Improved Terrain Aided Positioning Model Li Shidan Dept. Electronic Engineering, Tsinghua University, Beijing, China Email: lisd06@mails.tsinghua.edu.cn Sun Liguo, Li Xin, Wang Desheng Dept. Electronic Engineering, Tsinghua University, Beijing, China Email: {slg00, xinli05, wangdsh_ee}@mails.tsinghua.edu.cn Abstract—Terrain aided positioning (TAP) is a kind of positioning method which acquires position information from the terrain elevation datum underneath the vehicle. This method has the characteristics of autonomy, allweather, anti-interference, strong stealthiness and high accuracy. It is widely used in the navigation system for various aircrafts, cruise missiles and underwater vehicles. The fundamentals of TAP is that it firstly measures the terrain elevation underneath the vehicle using relevant sensors, then compares these datum with the referenced Digital Elevation Map (DEM) and acquires the position information through matching algorithm. The system model for TAP currently used totally depends on the referenced DEM and the position acquired is the position referenced to the map rather than the true position. Due to the DEM error which is introduced during production procedure, the position on the map is not the real position. In order to overcome the problem, the paper proposes an improved TAP model which introduces the map error into the system model and gets the recursive solution based on the Bayesian framework which is numerically solved by RPF particle filter. From the simulation results, the new model has extraordinary performance for handling the error of DEM and the algorithm can estimate the map error and acquire the accurate position. Index Terms—Terrain Aided Positioning, non-linear estimation, Bayesian iteration, Particle Filter, RPF I. INTRODUCTION Positioning and navigation system plays an important role on any vehicle no mater aerial, surface or underwater. The positioning system widely used nowadays can be divided into two categories: non-autonomy system and autonomy system. Non-autonomy system, represented by the satellite based systems, such as GPS and GNSS can give accurate position information by receiving signals from external devices. These satellite based systems can easily be jammed by electromagnetic interference and even the Manuscript received December 4, 2010; revised January 15, 2011; accepted January 26, 2011. © 2011 ACADEMY PUBLISHER doi:10.4304/jsw.6.5.937-943 satellite itself may be attacked during war time. Meanwhile, due to the rapid attenuation of electromagnetic wave through sea water, such satellite based systems are not suitable for underwater vehicles. Autonomy system, include inertial navigation system (INS) and terrain aided navigation system (TAN), does not need external devices for positioning and has the characteristics of all-weather, anti-interference, strong stealthiness and so on. They are widely used in many kinds of military vehicles for main or backup positioning system. Although INS can give high accurate positioning information during short time period, it has time accumulated errors which should be corrected by other systems, such as TAN or GPS, during work time, while the positioning error of TAN system mainly depends on the complexity and similarity of the terrain. TAN can also give high accurate position information from rugged terrain. For example, the TERPROM system widely used on NATO’s military aircrafts has horizontal position accuracy of 10~25 meters [1]. From the introduction above, it can be inferred that the autonomy poisoning system, especially TAN system, plays an important role on military usage during war time and may be the only choice for underwater vehicles. However the terrain aided positioning system currently used severely depends on the accuracy of the referenced Digital Elevation Map (DEM) which can be introduced with errors during producing [2] and finally leads to large differences between true position and estimated position. The paper just focuses on such problem and proposes an improved system model which introduces the map error components to the system model. The paper gives feasibility proof for the new model based on Bayesian theory and uses RPF particle filter for numerically getting the result. The simulation results confirm that the new model can estimate the map error and give more accurate position information compared to the basic model. II. SYSTEM MODEL The paper mainly discusses the terrain aided positioning system for aircrafts, but it can be easily extended to the underwater systems.
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