期刊文献+

多传感器集中式恒虚警率检测融合技术 被引量:2

Multi-sensor centralized CFAR detection fusion technique
下载PDF
导出
摘要 为提高传感器的检测性能,将一种经典的恒虚警率检测器CA-CFAR与多传感器集中式检测相结合。给出了多传感器集中式CA-CFAR检测器在均匀杂波环境中的虚警概率解析表达式。对两传感器集中式恒虚警率检测器和三传感器集中式恒虚警率检测器的检测概率进行了仿真,仿真结果表明,多传感器集中式恒虚警率检测器相对于单传感器恒虚警率检测器的检测概率有明显提高。 To improve the performance of sensor detection, one classic CFAR detector CA-CFAR is combined with multi-sensor centralized detection. The analytic expression of multi-sensor centralized CA-CFAR detector's false alarm probability in homogeneous clutter environment is derived. The detection probability of two-sensor centrali-zed CFAR detector and three-sensor centralized CFAR detector are simulated, the result of simulation indicates that the multi-sensor centralized CFAR detector is obviously advanced in terms of performance, compared with the single sensor CFAR detector.
出处 《计算机工程与设计》 CSCD 北大核心 2013年第11期3957-3960,共4页 Computer Engineering and Design
基金 国家863高技术研究发展计划基金项目(2012AA011804)
关键词 多传感器 集中式 恒虚警率 检测融合 单元平均 multi-sensor centralized CFAR detection fusion cell averaging
  • 相关文献

参考文献11

  • 1何友,关键,孟祥伟.雷达目标检测与恒虚警处理[M].北京:清华大学出版社,2011.
  • 2Cao T V. Constant false alarm rate algorithm based on test cell information [J]. IET Radar Sonar Navig, 2008, 2 (3): 200-213.
  • 3刘盼芝,韩崇昭.基于自动筛选技术的分布式CFAR检测算法[J].系统工程与电子技术,2008,30(6):1009-1014. 被引量:2
  • 4郝程鹏,刘斌,陈模江,侯朝焕.一种新的基于CA和OS的分布式模糊恒虚警检测系统[J].弹箭与制导学报,2008,28(6):219-221. 被引量:2
  • 5刘盼芝,韩崇昭.分布式自动删除平均恒虚警率检测技术[J].自动化学报,2009,35(7):903-910. 被引量:3
  • 6LIU Panzhi, DUAN Chendong. Distributed GOSCA-CFAR detection based on automatic censoring technique [C]//Kiev: 2nd International Conference on Information Technology and Computer Science, 2010: 154-157.
  • 7郝程鹏,张立军,蔡龙,侯朝焕.分布式模糊自动删除单元平均恒虚警检测[J].兵工学报,2010,31(9):1274-1278. 被引量:3
  • 8Meziani H A, Soltani F. Generalised decentralised fuzzy CA CFAR detector in pearson distributed clutter [C]//Beijing IEEE 10th International Conference on Signal Processing 2010: 1915-1918.
  • 9Cai Long, Ma Xiaoehuan, Yan Shefeng, et al. Some analysis of fuzzy CAGO/SO CFAR detector in non-Gaussian background [C] //Wuhan: 2nd International Workshop on Intelligent Sys terns and Applications, 2010: 1-4.
  • 10Cheikh K, Soltani F. Performance of the fuzzy VI-CFAR detector in non-homogeneous environments [C]//Kuala Lurepur: IEEE International Conference on Signal and Image Processing Applications, 2011: 100-103.

二级参考文献51

  • 1何友,Rohl.,H.一种具有自动筛选技术的恒虚警检测器及其在多目标情况下的性能[J].现代雷达,1995,17(2):85-93. 被引量:1
  • 2Tenney Robert R, Sandell, et al. Detection with distributed sensors[C]//Proceedings of the IEEE Conference on Decision and Control, 1980,1:433-437.
  • 3Sadjadi, E. Hypothesis in a distributed environment[J]. IEEE Trans. on Aerospace and Electronic Systems, 1986, 22:134 - 137.
  • 4Reibman Amy R, Nolte L W. Optimal detection and performance of distributed sensor systems[J]. IEEE Trans. on Aerospace and Electronic Systems, 1987, 23(1) : 24 - 30.
  • 5Chair Z, Varshney P K. Optima data fusion in multiple sensor detection systems[J]. IEEE Trans. on Aerospace and Electronic Systems, 1986, 22(1):98- 101.
  • 6Hoballah Imad Y, Varshney Pramod K. Distributed Bayesian signal detection [J]. IEEE Trans. on Information Theory, 1989, 35(5): 995-1000.
  • 7Hoballah I Y, Varshney P K. Neyman-pearson detection using multiple radars[C]//In Proceedings of the 25th IEEE Control and Decision Conference, 1986:237 - 241.
  • 8Srinivasan R. Distributed radar detection heory[C]//IEE Proceedings , Part F: Communications, Radar and Signal Processing, 1986, 133(1).- 55-60.
  • 9Thomopoulos S C A. Viswanathan R. Bougoulias D K. Optimal distributed decision fusion[J]. IEEE Trans. on Aerospace and Electronic Systems. 1989. 25(5): 761-765.
  • 10Eckchain L K. Tenney R K. Detection networks[C]//In Proceedings of the 21th IEEE Conference on Decision and Control. Dec. 1982.686 - 691.

共引文献11

同被引文献40

  • 1候媛彬,杜京义,汪梅.神经网络[M].西安:西安电子科技大学出版社,2007.
  • 2DLHall,JLlinas.多传感器数据融合手册[M].杨露菁,耿伯英,译.北京:电子工业出版社,2008.
  • 3L Wald. Some terms of reference in data fusion [ J ]. IEEE Transactions on Geoscience and Remote Sensing, 1999,37(31 ) :1190-1193.
  • 4郭磷.基于信息融合的交通信息采集研究[D].合肥:中国科技大学,2007.
  • 5J Liang, L Chen, X Y Cheng, et al. Multi- agent and driving behavior based rear-end collision alarm modeling and simulating [ J ]. Simulation Modelling Practice and Theory, 2010,18 ( 8 ) : 1092-1103.
  • 6SHaykin.自适应滤波器原理(第四版)[M].郑宝玉,译.北京:电子工业出版社,2006.
  • 7M Dawood, C Cappelle, M E El Naiiar, et al. Vehicle geo -localization based on IMM-UKF data fusion using a GPS receiver, a video camera and a 3D city model [ C ]// Intelligent Vehicles Symposium (IV). Piscataway: [ s. n. ] ,2011.
  • 8Q J Kong, Z Li, Y Chert, et al. An approach to urban traffic state estimation by fusing multisource information [ J ]. IEEE Transactions on Intelligent Transportation Systems, 2009,10 ( 3 ) : 499-511.
  • 9毛喆,严新平,张晖,吴超仲.驾驶模拟器校验实验方法的研究[J].武汉理工大学学报,2010,32(1):74-77. 被引量:7
  • 10张建明,张玲增,刘志强.一种结合多特征的前方车辆检测与跟踪方法[J].计算机工程与应用,2011,47(5):220-223. 被引量:11

引证文献2

二级引证文献14

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部