一种基于脉冲压缩的漏缆传感器定位新方法  被引量:4

A New Location Method of Leaky Coaxial Cable Sensor Based on Pulse Compression

在线阅读下载全文

作  者:刘洋[1] 官乔 路宏敏[1] 谭康伯[1] 蓝燕锐 LIU Yang;GUAN Qiao;LU Hong-min;TAN Kang-bo;LAN Yan-rui(School of Electronics Engineering, Xidian University, Xi'an 710071, China;Zhongtian RF Cable Co. Ltd. , Nantong 226010, China)

机构地区:[1]西安电子科技大学电子工程学院,西安710071 [2]中天射频电缆有限公司,南通226010

出  处:《微波学报》2018年第3期79-83,共5页Journal of Microwaves

摘  要:漏缆传感器的入侵探测定位系统已广泛应用于国防设施、银行、监狱等重要区域,为提高这种系统的定位精度,提出了一种基于脉冲压缩的漏缆传感器探测定位新方法。该方法将巴克码调制的二进制相移键控信号引入系统作为发射信号,并对接收信号进行滤波相减、相干解调、抽样判决和自相关运算等一系列信号处理,以获得含有入侵位置信息的特征信号。应用MATLAB和电磁仿真软件CST对该系统进行了协同仿真分析,并搭建了实验系统进行测试。仿真结果与实测结果吻合良好,验证了新方法探测定位的有效性。新方法的定位精度约为0.9 m,优于目前已报道的同类探测定位系统的定位精度。The intrusion detection and location system based on leaky coaxial cable sensor has been widely used in the monitoring of important areas such as national defense facilities, banks and prisons. To improve the positioning accuracy of this system, a new detection and location method of leaky coaxial cable sensor based on pulse compression technology is pro- posed. This method introduces the binary phase shift keying (2PSK) pulse signal modulated by the Barker code into the system as a transmitted signal, and the characteristic signal with intrusion position information can be obtained from the received signal by a series of signal processing as filtering, subtraction, coherent demodulation, sampling judgement and delay auto-correlation. The system is simulated by MATLAB and the electromagnetic simulation software CST, and an experimental system is established for test. The results of field test are in good agreement with the simulation results, which proves the validity of the new method. The positioning accuracy of the new method is about 0.9 m, which is superior than that of the similar detection and location system which have been reported.

关 键 词:漏缆传感器 巴克码 脉冲压缩 探测定位 

分 类 号:TP212[自动化与计算机技术—检测技术与自动化装置]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象