[1]余修武,周利兴,范飞生,等.基于新内点测试与Grid-SCAN的铀尾矿库监测定位算法[J].中国安全生产科学技术,2016,12(5):5-9.[doi:10.11731/j.issn.1673-193x.2016.05.001]
YU Xiuwu,ZHOU Lixing,FAN Feisheng,et al.A localization algorithm for uranium tailings monitoring based
on new interior point test and Grid-SCAN[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2016,12(5):5-9.[doi:10.11731/j.issn.1673-193x.2016.05.001]
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基于新内点测试与Grid-SCAN的铀尾矿库监测定位算法
YU Xiuwu,ZHOU Lixing,FAN Feisheng,et al.A localization algorithm for uranium tailings monitoring based on new interior point test and Grid-SCAN[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2016,12(5):5-9.[doi:10.11731/j.issn.1673-193x.2016.05.001]
《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]
- 卷:
- 12
- 期数:
- 2016年5期
- 页码:
- 5-9
- 栏目:
- 学术论著
- 出版日期:
- 2016-05-30
文章信息/Info
- Title:
- A localization algorithm for uranium tailings monitoring based on new interior point test and Grid-SCAN
- Keywords:
- WSN; approximate triangle interior point test (APIT); Grid-SCAN; RSSI; probability model; monitoring localization
- 分类号:
- X936; TP301.6
- 文献标志码:
- A
- 摘要:
- 面向铀尾矿库放射性核素污染WSN监测中，由于监测环境制约，针对该条件下节点密度低、带状分布网络连通性差等问题，为保证一定定位精度，提出一种新的定位算法。新内点测试利用RSSI值与海伦公式判断是否在三角形内外，无需未知节点周围其他节点信息，并采用Grid-SCAN寻找概率模型选取点，使该算法满足低密度条件的定位并减少其计算量。约束范围内计算网格内各点RSSI值的概率，并以最大概率坐标为定位结果。经过仿真，新算法较APIT算法在定位精度上提高了55%~69%。
- Abstract:
- For radionuclide pollution monitoring by WSN in uranium tailings, in order to solve the problems of low node density and poor connectivity in zonal distribution network caused by the restrict of monitoring environment, a new localization algorithm was proposed to ensure the accuracy of localization. For the new interior point test, the RSSI value and Heron's formula were used to judge whether in the triangle or not without the information of other nodes around the unknown node. The Grid-SCAN was applied to search the selection points of probabilistic model, which made the algorithm satisfy the localization under low density condition and reduced its amount of calculation. The probability of RSSI value for each point in the grid were calculated in the constraint range, and the maximum probability coordinates were taken as the localization results. The simulation results showed that the localization accuracy of new algorithm increased by 55%~69% than that of APIT algorithm.
参考文献/References:
［1］谢水波, 陈泽昂, 张晓健,等. 铀尾矿库区浅层地下水中U（Ⅵ）迁移的模拟［J］原子能科学技术, 2007, 41(1):58-64.
XIE Shuibo,CHEN Zeang,ZHANG Xiaojian,et al.Simulation of U（Ⅵ） migration in shallow groundwater at uranium Mill-Tailing site［J］.Atomic Energy Science and Technology， 2007, 41(1):58-64.
［2］余修武, 范飞生, 李睿,等. 基于接收信号强度分区矿山无线定位算法［J］. 中国安全生产科学技术, 2015，11(9):70-75.
YU Xiuwu, FAN Feisheng, LI Rui, et al.Study on wireless positioning algorithm in mine based on received signal strength paritition［J］.Journal of Safety Science and Technology, 2015，11(9):70-75.
［3］Mehrabi A, Kim K. Maximizing data collection throughput on a path in energy harvesting sensor networks using a mobile sink［J］. IEEE Transactions on Mobile Computing, 2016:690-704.
［4］Ng C K, Wu C H, Wang L, et al. An RFID-Enabled Wireless Sensor Network (WSN) Monitoring System for Biological and Pharmaceutical Products［C］// 2014 International Symposium on Computer, Consumer and Control (IS3C). 2014:757 - 760.
［5］Han S, Gong Z, Meng W, et al. Automatic Precision Control Positioning for Wireless Sensor Network［J］. Sensors Journal IEEE, 2016, 16(7):2140-2150.
［6］Liu J, Wang Z, Yao M, et al. VN-APIT: virtual nodes-based range-free APIT localization scheme for WSN［J］. Wireless Networks, 2015:1-12.
［7］Hu Y, Li X. An improvement of DV-Hop localization algorithm for wireless sensor networks［J］. Telecommunication Systems, 2013, 53(1):13-18.
［8］Yang G X, Jing B. Localization Algorithm for Wireless Sensor Network Based on Energy Threshold［C］// Information Technology, Computer Engineering and Management Sciences, International Conference of. IEEE, 2011:193-197.
［9］Xiong X, Yan C. Three-Dimensional Localization Algorithm of APIT Based on Fermat-Point Divided for Wireless Sensor Networks［C］// Computational Intelligence and Design (ISCID), 2014 Seventh International Symposium on. IEEE, 2014.
［10］Peng L, Zhang W. Based on the cyclic refinement APIT localization algorithm for wireless sensor networks［C］// Control Conference (CCC), 2010 29th Chinese. IEEE, 2010:4753-4756.
［11］Betta G, Capriglione D, Casinelli D, et al. Experimental analysis of the frequency diversity to improve localization in WSNs［C］// XVIII AISEM Annual Conference. 2015:1-4.
［12］Rankine C J, Sanchez-Azofeifa G A, Macgregor M H. Seasonal wireless sensor network link performance in boreal forest phenology monitoring［C］// Sensing, Communication, and Networking (SECON), 2014 Eleventh Annual IEEE International Conference on. IEEE, 2014:302-310.
［13］张原.基于高斯混合模型的无线传感器网络节点定位算法的研究［D］.长春：吉林大学，2010.
［14］陆娴, 彭勇. 一种改进的APIT定位算法［J］. 计算机工程与应用, 2015, 51(3):74-78.
LU Xian,PENG Yong. Improved APIT localization algorithm［J］. Computer Engineering and Applications, 2015, 51（3）：74-78.
相似文献/References:
[1]余修武,胡沐芳,周利兴,等.基于阶次序列与凸规划的铀尾矿库监测定位算法[J].中国安全生产科学技术,2016,12(12):86.[doi:10.11731/j.issn.1673-193x.2016.12.015]
YU Xiuwu,HU Mufang,ZHOU Lixing,et al.A localization algorithm of uranium tailings monitoring based on rank sequence and convex programming[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2016,12(5):86.[doi:10.11731/j.issn.1673-193x.2016.12.015]
备注/Memo
- 备注/Memo:
- 湖南省重点研发项目(2015SK2005);湖南省教育厅科研重点项目(15A161);江西省自然科学基金项目(20122BAB201050);江西省科技厅科技支撑项目(20121BBG70065);江西省教育厅科技项目(GJJ12667);南华大学博士科研基金项目(2013XQD12)
