Journal of Jilin University(Engineering and Technology Edition) ›› 2023, Vol. 53 ›› Issue (4): 1187-1199.doi: 10.13229/j.cnki.jdxbgxb.20210811

Previous Articles    

Seismic sensing perimeter security system based on cat swarm algorithm

Qiu-zhan ZHOU1(),Ze-yu JI1,Cong WANG1(),Ji-kang HU1,Ming-ming LI2,Yu-zhu CHEN1,Xian-feng ZHOU3,4,Ping-ping LIU5   

  1. 1.College of Communication Engineering，Jilin University，Changchun 130012，China
    2.Big Data & Management Center，Jilin University，Changchun 130012，China
    3.Key Laboratory of Geoexploration Instrumentation of Ministry of Education，Jilin University，Changchun 130061，China
    4.College of Instrumentation & Electrical Engineering，Jilin University，Changchun 130061，China
    5.College of Computer Science and Technology，Jilin University，Changchun 130012，China
  • Received:2021-08-22 Online:2023-04-01 Published:2023-04-20
  • Contact: Cong WANG E-mail:13504465154@163.com;wangcong2020@jlu.edu.cn

RICH HTML

 6   

PDF (PC)

133

Abstract:

Traditional perimeter-security systems either suffer from low positioning accuracy of the target or cannot determine the optimal result generated by multiple groups of sensors in common TDOA. In response to the above issues， this paper designs an intelligent perimeter-security system， by means of seismic sensors and cat-swarm algorithm. First， moving coil seismic sensors are used for collecting the seismic signals generated by targets on shallow surfaces. Then， the collected signals are processed to obtain initial TDOA localization results of the target. Later， these initial results are further optimized via cat-swarm algorithm. Aiming at different application scenarios of the system， this paper designs two communication modes （i.e.， LoRa and Beidou short message） to ensure system communication in remote regions. In order to verify the effectiveness of the optimization algorithm， several experiments are conducted in real world under different parameter settings. According to the experimental results， when the error in propagation velocity of seismic wave is less 10%， the average localization error of the proposed system （i.e.， optimized by cat-swarm algorithm） is less 1 meter. In particular， compared with the initial TDOA localization results， the localization error is reduced by 46.9%.

Key words: communication and information system, perimeter-security, TDOA location, swarm intelligence, cat-swarm algorithm

CLC Number: 

  • TP274

Fig.1

Architecture of the proposed swarm intelligence perimeter-security system"

Fig.2

Swarm intelligence perimeter-security system"

Fig.3

Cat-swarm algorithm flow"

Fig.4

Real-world system composition"

Fig.5

Software for system configuration"

Fig.6

Sensor layout of system"

Fig.7

TDOA localization results before and afteroptimized by cat swarm-algorithm"

Table 1

Optimization results of simulated data indifferent locations"

目标位置TDOA横坐标TDOA纵坐标最优解与震源距离/m
优化前优化后
（7.5，2.5）6~71~20.83260.0272
（7.5，2.5）8~93~40.83060.0445
（7.5，2.5）6~73~40.87820.0309

Fig.8

Diamond layout of sensors"

Fig.9

Circular layout of sensors"

Table 2

Algorithm optimization results of simulated data in diamond layout of sensors"

目标位置TDOA横坐标范围TDOA纵坐标范围优化前最优解与震源距离/m优化后最优解与震源距离/m
（10，10）9~109~100.21680.0120
（10，10）9~1010~110.15630.1044
（10，10）10~119~100.39240.1562
（10，10）10~1110~110.16430.1518
（10，10）9~119~110.15590.0150

Table 3

Algorithm optimization results of simulated data in circular layout of sensors"

目标位置TDOA横坐标范围TDOA纵坐标范围优化前最优解与震源距离/m优化后最优解与震源距离/m
（10，10）9~109~100.13270.0073
（10，10）9~1010~110.30370.1315
（10，10）10~119~100.27490.0925
（10，10）10~1110~110.18460.1277
（10，10）9~119~110.08540.0036

Table 4

Algorithm optimization results of simulated data in random layout of sensors"

目标位置TDOA横坐标范围TDOA纵坐标范围优化前最优解与震源距离/m优化后最优解与震源距离/m
（10，10）9~109~100.13410.0182
（10，10）9~1010~110.30980.0972
（10，10）10~119~100.32540.1211
（10，10）10~1110~110.16910.1588
（10，10）9~119~110.40140.0435

Fig.10

Error analysis of cat-swarm algorithm under different speed errors"

Table 5

Error analysis of 50 positioning results underdifferent vibration wave velocity errors"

速度误差范围50次定位结果中误差最大值/m50次定位结果中误差最小值/m50次定位结果中误差均值/m
00.20510.000210.0437
5%1.05650.02130.3879
10%2.78610.00710.7610
20%5.66610.05931.9049

Fig.11

TDOA localization results before and afteroptimized by cat swarm-algorithm"

Table 6

Execution time of optimization algorithm under different iterations"

迭代次数算法执行时间/s
500.4992
1000.9318
5004.3264
10008.3203

Fig.12

Comparison of localization results before andafter optimized by cat swarm-algorithm"

Fig.13

Comparison of localization results afteroptimized by three algorithms"

Fig.14

Comparison of evolution curves of threealgorithms"

1 Filipiak J, Steczko G, Kostrzewa S, et al. Perimeter security system based on SAW vibration sensor[J]. Acta Physica Polonica A, 2015, 128(3): 408-413.
2 Ma P F, Liu K, Jiang J F, et al. Probabilistic event discrimination algorithm for fiber optic perimeter security systems[J]. Journal of Lightwave Technology, 2018, 11(1): 2069-2075.
3 Liu K, Miao T, Liu T, et al. A high-efficiency multiple events discrimination method in optical fiber perimeter security[J]. Journal of Lightwave Technology, 2015, 33(23): 4885-4890.
4 李克成. 基于MEMS传感器的周界安防系统研究与设计[D]. 沈阳:东北大学机械工程与自动化学院, 2016.
Li Ke-cheng. Research and design of perimeter-security System based on MEMS sensor[D]. Shenyang: School of Mechanical Engineering and Automation, Northeastern University, 2016.
5 周丹. 混合策略粒子群优化算法的研究及应用[D]. 无锡:江南大学人工智能与计算机学院, 2016.
Zhou Dan. Research and application of hybrid strategy particle swarm optimization algorithm[D]. Wuxi: School of Artificial Intelligence and Computer Science, Jiangnan University, 2016.
6 Wei Dong, Wang Zhong-bin, Si Lei, et al. Preaching inspired swarm intelligence algorithm and its applications[J]. Knowledge-Based Systems, 2021, 211: No. 106552.
7 吕辰. 基于MARG无人机姿态测量系统的实时融合算法研究[D]. 太原:中北大学电子测试技术科技重点实验室, 2018.
Lv Chen. Research on real-time fusion algorithm based on MARG UAV attitude measurement system[D]. Taiyuan: Key Laboratory of Electronic Testing Technology Science and Technology, North University of China, 2018.
8 Zhao L, Qu S C, Zhang W G. Design of multi-channel data collector for highway tunnel lighting based on STM32 and modbus protocol[J]. Optik International Journal for Light and Electron Optics, 2020, 213: No. 164388.
9 Zhu You-chan, Zhang Wen-hua. Design and implementation on of intelligent greenhouse system based on STM32[J]. International Core Journal of Engineering, 2020, 6(7): 340-345.
10 陈宇翔. LoRa应用关键技术研究[D]. 杭州:杭州电子科技大学计算机学院, 2019.
Chen Yu-xiang. Research on key technologies of LoRa application[D]. Hangzhou: School of Computer Science, Hangzhou Dianzi University, 2019.
11 Liu Chao-tao, Su Xuan-chao, Liu Tang-zhi, et al. Design and application of intelligent traffic guidance system for fog area based on LoRa[J]. Journal of Physics: Conference Series, 2019, 1168(2): No. 022088.
12 Zhang Li, Li Da, Liu Hui-xi, et al. Research on method of reducing alarm delay time of lora technology in laboratory monitoring system[J]. Application of Electronic Technique, 2019, 45(6): 135-140.
13 黄新源. 基于LoRa的城市环境室外定位方法研究与实现[D]. 成都:电子科技大学电子科学与工程学院, 2020.
Huang Xin-yuan. Research and implementation of outdoor location method of urban environment based on LoRa[D]. Chengdu: School of Electronic Science and Engineering, University of Electronic Science and Technology of China, 2020.
14 Yong Wu, Li Li, Li Min-zan, et al. Remote-control system for greenhouse based on open source hardware[J]. IFAC-PapersOnLine, 2019, 52(30): 178-183.
15 Chen Hai-sheng, Guo Xiao-yun, Wang Feng, et al. Fishery harvesting information compressing and transmitting method based on beidou short message[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(22): 155-160.
16 周志军,孙志敏,王政嘉,等.一种基于GPS/BD 组合系统的ETC收费方法、装置及计算机设备[P]. 中国 专利, CN202010747351.4, 2020.
17 信方硕. 基于北斗短报文的卫星远程教育系统资源订阅协议[D]. 呼和浩特:内蒙古大学电子信息工程学院, 2019.
Xin Fang-shuo. Resource subscription protocol of satellite distance education system based on BeiDou short message[D]. Hohhot: School of Electronic and Information Engineering, Inner Mongolia University, 2019.
18 刘飞, 林琳, 徐文江. 基于北斗RDSS的监视数据传输技术研究[J]. 信息技术, 2020, 44(1): 15-19, 25.
Liu Fei, Lin Lin, Xu Wen-jiang. Monitoring data transmission technology based on Beidou RDSS[J]. Information Technology, 2020, 44(1): 15-19, 25.
19 孙晋. 基于北斗短报文和RT-Thread的远程通信系统设计[D]. 南京:南京信息工程大学电子与信息工程学院, 2020.
Sun Jin. Design of telecommunication system based on BeiDou short message and RT-Thread[D]. Nanjing: School of Electronics and Information Engineering, Nanjing University of Information Science and Technology, 2020.
20 翁星. 群体智能在无线传感器网络定位中的研究与应用[D]. 南京: 南京邮电大学电子与光学工程学院, 2015.
Weng Xing. Research and application of swarm intelligence in wireless sensor network localization[D]. Nanjing: School of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, 2015.
21 李昂, 付敬奇, 沈华明, 等. 基于模糊聚类和猫群算法的室内定位算法[J]. 仪器仪表学报, 2020, 41(1): 185-194.
Li Ang, Fu Jing-qi, Shen Hua-ming, et al. Indoor location algorithm based on fuzzy clustering and cat swarm algorithm[J]. Chinese Journal of Scientific Instrument, 2020, 41(1): 185-194.
22 Ahmedaram M, Rashidtarik A, Saeedsoran A M. Cat swarm optimization algorithm: a survey and performance evaluation[J]. Computational Intelligence and Neuroscience, 2020, 2020(1): 1-21.
23 Katsaragakis I, Tassopoulos I, Beligiannis G N. Solving the urban transit routing problem using a cat swarm optimization-based algorithm[J]. Algorithms, 2020, 13(9): 223.
24 Tsai P W, Istanda V. Review on cat swarm optimization algorithms[C]//The 3rd International Conference on Consumer Electronics, Communications and Networks, Xianning, China, 2013: 564-567.
25 Sharafi Y, Khanesar M A, Teshnehlab M. Discrete binary cat swarm optimization algorithm[C]//The 3rd IEEE International Conference on Computer, Control and Communication, Karachi, Pakistan, 2013: 1-6.
26 Tsai P W, Kong L, Vaclav S, et al. Utilizing cat swarm optimization in allocating the sink node in the w-ireless sensor network environment[C]//Third International Conference on Computing Measurement Control and Sensor Network, Matsue, Japan, 2017: 166-169.
27 Broderick C, Ricardo S, Natalia B, et al. A binary cat swarm optimization algorithm for the non-unicost set covering problem[J]. Mathematical Problems in Engineering, 2015, 2015(2): 1-8.
28 朱旭芳, 颜冰, 马剑飞. 基于序列相关检测法的地震波传播速度测量方法[J]. 海军工程大学学报, 2017, 29(3): 87-91.
Zhu Xu-fang, Yan Bing, Ma Jian-fei. Seismic wave velocity measurement method based on sequence correlation detection method[J]. Journal of Naval University of Engineering, 2017, 29(3): 87-91.
29 彭琨. 光纤周界安防系统模式识别体系的研究与实现[D]. 北京:北京邮电大学自动化学院, 2017.
Peng Kun. Research and realization of pattern recognition system for fiber perimeter security system[D]. Beijing: School of Automation, Beijing University of Posts and Telecommunications, 2017.
[1] Hong-yang PAN,Zhao LIU,Bo YANG,Geng SUN,Yan-heng LIU. Overview of swarm intelligence methods for unmanned aerial vehicle systems based on new⁃generation information technology [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 629-642.
[2] Ren-chu GUAN,Bao-run HE,Yan-chun LIANG,Xiao-hu SHI. Particle swarm optimization algorithm based on kinship selection [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(8): 1842-1849.
[3] Hong-liang SUN,Wei-da SHEN,Ling-ling CHEN. Bandwidth compensation algorithm for mixed services under delay quality of service constraint [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(8): 1912-1917.
[4] Jian CHEN,Fan YU,Lin LIN,Ming⁃hui SUN. Local ultrasound array focusing method based on multiarray synthetic aperture [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(10): 2447-2455.
[5] Song-mei TANG. Key technology of face recognition system based on swarm intelligence in library [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(6): 2216-2224.
[6] Chun-ping HOU,Chun-yue ZHAO,Zhi-peng WANG,Hai-rui TIAN. Video anomaly detection algorithm based on effective anomaly sample construction [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(5): 1823-1829.
[7] Yi-jun WANG,You-xu ZHANG,Rui-xin MIAO,Jia-min DOU. D2D resource allocation algorithm based on system outage probability in 5G [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(1): 331-339.
[8] Zhao-zheng HU,Zhao-kang LI,Qian-wen TAO. Indoor pedestrian detection and tracking from distributed two⁃dimensional laser range finders [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(2): 719-729.
[9] Peng ZHAO,Yu-zhong JIANG,Bin CHEN,Chun-teng LI,Yang-yong ZHANG. SLF channel noise suppression method based on adaptive blanking in local variance domain [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(5): 1696-1705.
[10] YANG Mao, LI Cheng-Feng, TIAN Yan-Chao. Social foraging swarm control energybased under uniform environment [J]. 吉林大学学报(工学版), 2010, 40(增刊): 349-0353.
[11] YANG Yong-ming，TIAN Yan-tao . Mathematical analysis of heterogeneous swarm robots foraging based on region division mechanism [J]. 吉林大学学报(工学版), 2008, 38(06): 1396-1401.
[12] Jiang Hai-ming，Xie Kang，Wang Ya-fei . Modified particle swarm optimization via probabilistic leap [J]. 吉林大学学报(工学版), 2007, 37(01): 141-145.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd