[1] JUAREZ J C, TAYLOR H F. Field test of a distributed fiber-optic intrusion sensor system for long perimeters[J]. Applied Optics, 46, 1968-1971(2007).

[2] QIN Z G, CHEN L, BAO X Y. Continuous wavelet transform for non-stationary vibration detection with phase-OTDR[C], 8421, 8421-0(2012).

[3] JUAREZ J C, MAIER E W, CHOI K N et al. Distributed fiber-optic intrusion sensor system[J]. Journal of Lightwave Technology, 23, 2081-2087(2005).

[4] JUAREZ J C, TAYLOR H F. Polarization discrimination in a phase-sensitive optical time-domain reflectometer intrusion-sensor system[J]. Optics Letters, 30, 3284-3286(2005).

[5] QIN Z G, CHEN L, BAO X Y. Wavelet denoising method for improving detection performance of distributed vibration sensor[J]. IEEE Photonics Technology Letters, 24, 542-544(2012).

[6] CHOI K N, TAYLOR H F. Spectrally stable Er-fiber laser for application in phase-sensitive optical time-domain reflectometry[J]. IEEE Photonics Technology Letters, 15, 386-388(2003).

[7] RAO Y J, LUO J, RAN Z L et al. ［C］[C](2009).

[8] MARTINS H F, MARTÍN-LÓPEZ S, CORREDERA P et al. Phase-sensitive optical time domain reflectometer assisted by first-order Raman amplification for distributed vibration sensing over>100 km[J]. Journal of Lightwave Technology, 32, 1510-1518(2014).

[9] PENG F, WU H, JIA X H et al. Ultra-long high-sensitivity Φ-OTDR for high spatial resolution intrusion detection of pipelines[J]. Optics Express, 22, 13804-13810(2014).

[10] MARTINS H F, MARTIN-LOPEZ S, FILOGRANO M L et al. Comparison of the use of first and second-order Raman amplification to assist a phase-sensitive optical time domain reflectometer in distributed vibration sensing over 125 km[C], 9157, 91576K(2014).

[11] LU Y L, ZHU T, CHEN L et al. Distributed vibration sensor based on coherent detection of phase-OTDR[J]. Journal of Lightwave Technology, 28, 3243-3249(2010).

[12] WANG Z N, LI J, FAN M Q et al. Phase-sensitive optical time-domain reflectometry with Brillouin amplification[J]. Optics Letters, 39, 4313-4316(2014).

[13] WANG Z N, ZENG J J, LI J et al. Ultra-long phase-sensitive OTDR with hybrid distributed amplification[J]. Optics Letters, 39, 5866-5869(2014).

[14] PAN Z Q, LIANG K Z, YE Q et al. Phase-sensitive OTDR system based on digital coherent detection[C], 1-6(2011).

[15] HE H J, SHAO L Y, LUO B et al. Multiple vibrations measurement using phase-sensitive OTDR merged with Mach-Zehnder interferometer based on frequency division multiplexing[J]. Optics Express, 24, 4842-4855(2016).

[16] HE Q, ZHU T, XIAO X H et al. All fiber distributed vibration sensing using modulated time-difference pulses[J]. IEEE Photonics Technology Letters, 25, 1955-1957(2013).

[17] SHAN Y Y, DONG J Y, ZENG J et al. A broadband distributed vibration sensing system assisted by a distributed feedback interferometer[J]. IEEE Photonics Journal, 10, 1-10(2018).

[18] ZHU T, HE Q, XIAO X H et al. Modulated pulses based distributed vibration sensing with high frequency response and spatial resolution[J]. Optics Express, 21, 2953-2963(2013).

[19] [19] 19曲洪权， 夏雨， 毕福昆. 一种基于改进型SVM算法的光纤入侵信号识别研究［J］. 北方工业大学学报， 2017， 29（2）： 33-38. doi: 10.3969/j.issn.1001-5477.2017.02.006QUH Q， XIAY， BIF K. An improved SVM method to recognize harmful intrusion signal for optical fiber pre-warning system［J］. Journal of North China University of Technology， 2017， 29（2）： 33-38.（in Chinese）. doi: 10.3969/j.issn.1001-5477.2017.02.006

[20] WU H J, XIAO S K, LI X Y et al. Separation and determination of the disturbing signals in phase-sensitive optical time domain reflectometry （Φ-OTDR）[J]. Journal of Lightwave Technology, 33, 3156-3162(2015).

[21] QIAN Y, WU H J, ZHANG W et al. Feature extraction with WD and WPD in distributed optical-fiber vibration sensing system for oil pipeline safety monitoring[C](2016).

[22] TEJEDOR J, MACIAS-GUARASA J, MARTINS H et al. A novel fiber optic based surveillance system for prevention of pipeline integrity threats[J]. Sensors, 17, 355(2017).

[23] [23] 23徐铖晋. 分布式光纤传感系统的信号处理技术研究［D］. 杭州： 浙江大学， 2017.XUCH J. Research on Signal Processing Technology of Distributed Optical Fiber Sensing System［D］. Hangzhou： Zhejiang University， 2017. （in Chinese）

[24] [24] 24张俊楠， 娄淑琴， 梁生. 基于SVM算法的φ-OTDR分布式光纤扰动传感系统模式识别研究［J］. 红外与激光工程， 2017， 46（4）： 0422003. doi: 10.3788/irla201746.0422003ZHANGJ N， LOUSH Q， LIANGSH. Study of pattern recognition based on SVM algorithm for φ-OTDR distributed optical fiber disturbance sensing system［J］. Infrared and Laser Engineering， 2017， 46（4）： 0422003.（in Chinese）. doi: 10.3788/irla201746.0422003

[25] [25] 25付群健. 分布式光纤振动传感系统模式识别方法研究［D］. 长春： 吉林大学， 2019. doi: 10.1117/12.2548132FUQ J. Research on Pattern Recognition Method of Distributed Optical Fiber Vibration Sensing System［D］. Changchun： Jilin University， 2019. （in Chinese）. doi: 10.1117/12.2548132

[26] [26] 26张伟. 基于分布式光纤振动传感器的管道监测信号处理方法［D］. 成都： 电子科技大学， 2017.ZHANGW. Methods of Pipeline Monitoring Signal Processing Based on Distributed Optical Fiber Vibration Sensor［D］. Chengdu： University of Electronic Science and Technology of China， 2017. （in Chinese）

[27] JIA H Z, LIANG S, LOU S Q et al. A $k$ -nearest neighbor algorithm-based near category support vector machine method for event identification of phi-OTDR[J]. IEEE Sensors Journal, 19, 3683-3689(2019).

[28] [28] 28姚媛媛. 分布式光纤传感系统的振动信号识别研究［D］. 北京： 北京交通大学， 2020.YAOY Y. Research on Vibration Signal Recognition of Distributed Optical Fiber Sensing System［D］. Beijing： Beijing Jiaotong University， 2020. （in Chinese）

[29] SUN Q, FENG H, YAN X et al. Recognition of a phase-sensitivity OTDR sensing system based on morphologic feature extraction[J]. Sensors （Basel， Switzerland）, 15, 15179-15197(2015).

[30] WANG Y, WANG P F, DING K et al. Pattern recognition using relevant vector machine in optical fiber vibration sensing system[J]. IEEE Access, 7, 5886-5895(2019).

[31] XU C J, GUAN J J, BAO M et al. Pattern recognition based on time-frequency analysis and convolutional neural networks for vibrational events in φ-OTDR[J]. Optical Engineering, 57, 1(2018).

[32] JIANG F, LI H L, ZHANG Z H et al. An event recognition method for fiber distributed acoustic sensing systems based on the combination of MFCC and CNN[C], 1061, 1061804(2018).

[33] SHI Y, WANG Y Y, ZHAO L et al. An event recognition method for Φ-OTDR sensing system based on deep learning[J]. Sensors, 19, 3421(2019).

[34] CHEN J P, WU H J, LIU X R et al. A real-time distributed deep learning approach for intelligent event recognition in long distance pipeline monitoring with DOFS[C], 290-296(2018).

[35] [35] 35吴俊， 管鲁阳， 鲍明， 等. 基于多尺度一维卷积神经网络的光纤振动事件识别［J］. 光电工程， 2019， 46（5）： 79-86.WUJ， GUANL Y， BAOM， et al. Vibration events recognition of optical fiber based on multi-scale 1-D CNN［J］. Opto-Electronic Engineering， 2019， 46（5）： 79-86.（in Chinese）

[36] [36] 36于淼. 基于双重同源外差相干检测的Φ-OTDR系统的研究及应用［D］. 长春： 吉林大学， 2017. doi: 10.1364/ao.56.004058YUM. Research and Application of Phase-sensitive Optical Time-domain Reflectometric System Based on Single-source Dual Heterodyne Detection Scheme［D］. Changchun： Jilin University， 2017. （in Chinese）. doi: 10.1364/ao.56.004058

[37] XU C J, GUAN J J, BAO M et al. Pattern recognition based on enhanced multifeature parameters for vibration events in φ-OTDR distributed optical fiber sensing system[J]. Microwave and Optical Technology Letters, 59, 3134-3141(2017).

[38] CHEN X, XU C J. Disturbance pattern recognition based on an ALSTM in a long-distance φ-OTDR sensing system[J]. Microwave and Optical Technology Letters, 62, 168-175(2020).

[39] QIN Z G, CHEN L, BAO X Y. Wavelet denoising method for improving detection performance of distributed vibration sensor[J]. IEEE Photonics Technology Letters, 24, 542-544(2012).

[40] CHEN W, MA X H, MA Q L et al. Denoising method of the Φ-OTDR system based on EMD-PCC[J]. IEEE Sensors Journal, 21, 12113-12118(2021).

[41] QU S, CHANG J, CONG Z H et al. Data compression and SNR enhancement with compressive sensing method in phase-sensitive OTDR[J]. Optics Communications, 433, 97-103(2019).

[42] ZHU T, XIAO X H, HE Q et al. Enhancement of SNR and spatial resolution in phi-OTDR system by using two-dimensional edge detection method[J]. Journal of Lightwave Technology, 31, 2851-2856(2013).

[43] WANG Y, JIN B Q, WANG Y C et al. Real-time distributed vibration monitoring system using $\Phi$ -OTDR[J]. IEEE Sensors Journal, 17, 1333-1341(2017).

[44] HE H J, SHAO L Y, LI H C et al. SNR enhancement in phase-sensitive OTDR with adaptive 2-D bilateral filtering algorithm[J]. IEEE Photonics Journal, 9, 1-10(2017).

[45] ÖLÇER İ, ÖNCÜ A. Adaptive temporal matched filtering for noise suppression in fiber optic distributed acoustic sensing[J]. Sensors, 17, 1288(2017).

[46] LIEHR S, BORCHARDT C, MÜNZENBERGER S. Long-distance fiber optic vibration sensing using convolutional neural networks as real-time denoisers[J]. Optics Express, 28, 39311-39325(2020).

[47] BOLL S. Suppression of acoustic noise in speech using spectral subtraction[J]. IEEE Transactions on Acoustics， Speech， and Signal Processing, 27, 113-120(1979).

[48] TROPP J A, GILBERT A C. Signal recovery from random measurements via orthogonal matching pursuit[J]. IEEE Transactions on Information Theory, 53, 4655-4666(2007).

[49] ROBERTS， G L, ROBERTS， G L[M]. Machine Perception of Three-dimensional Solids(1965).

[50] ELAD M. On the origin of the bilateral filter and ways to improve it[J]. IEEE Transactions on Image Processing, 11, 1141-1151(2002).

[51] SOBEL I E. Camera Models and Machine Perception[D](1970).

[52] PREWITT. Object enhancement and extraction[J]. Picture Processing and Psychopictorics(1971).

[53] ZHU Q D, JING L Q, BI R S. Exploration and improvement of Ostu threshold segmentation algorithm[C], 6183-6188(2010).

[54] ZHANG M, GUNTURK B K. Multiresolution bilateral filtering for image denoising[J]. IEEE Transactions on Image Processing, 17, 2324-2333(2008).

[55] SHAO L Y, LIU S Q, BANDYOPADHYAY S et al. Data-driven distributed optical vibration sensors： a review[J]. IEEE Sensors Journal, 20, 6224-6239(2019).

[56] TEJEDOR J, MACIAS-GUARASA J, MARTINS H F et al. Towards detection of pipeline integrity threats using a smart fiber optic surveillance system： PIT-STOP project blind field test results[C](2017).

[57] JIA H Z, LOU S Q, LIANG S et al. Event identification by F-ELM model for phi-OTDR fiber-optic distributed disturbance sensor[J]. IEEE Sensors Journal, 20, 1297-1305(2020).

[58] WANG X, LIU Y, LIANG S et al. Event identification based on random forest classifier for Φ-OTDR fiber-optic distributed disturbance sensor[J]. Infrared Physics & Technology, 97, 319-325(2019).

[59] WANG J, HU Y Z, SHAO Y C. The digging signal identification by the random forest algorithm in the phase-OTDR technology[J]. IOP Conference Series： Materials Science and Engineering, 394(2018).

[60] ZHANG M J, LI Y C, CHEN J et al. Event detection method comparison for distributed acoustic sensors using φ-OTDR[J]. Optical Fiber Technology, 52, 101980(2019).

[61] WANG Z D, LOU S Q, LIANG S et al. Multi-class disturbance events recognition based on EMD and XGBoost in φ-OTDR[J]. IEEE Access, 8, 63551-63558(2020).

[62] CREMERS D, ROUSSON M, DERICHE R. A review of statistical approaches to level set segmentation： integrating color， texture， motion and shape[J]. International Journal of Computer Vision, 72, 195-215(2007).

[63] SANKUR B. Survey over image thresholding techniques and quantitative performance evaluation[J]. Journal of Electronic Imaging, 13, 146-168(2004).

[64] BIANCO A, BOENTE G, PIRES A M et al. Robust discrimination under a hierarchy on the scatter matrices[J]. Journal of Multivariate Analysis, 99, 1332-1357(2008).

[65] JIANG L H, LIU X M, YANG R Y. Application of the HHT method to the airport fiber fence warning[C], 1337-1340(2011).

[66] TIPPING M E. Sparse Bayesian learning and relevance vector machine[J]. Journal of Machine Learning Research, 1, 211-244(2001).

[67] [67] 67赵发林， 张涛， 李康. 基于遗传算法的随机森林模型在特征基因筛选中的应用［J］. 中国卫生统计， 2016， 33（4）： 559-562， 566.ZHAOF L， ZHANGT， LIK. An optimized random forest based on genetic algorithm and its application to feature selection for gene data［J］. Chinese Journal of Health Statistics， 2016， 33（4）： 559-562， 566.（in Chinese）

[68] FRIEDMAN J H. Greedy function approximation： a gradient boosting machine[J]. The Annals of Statistics, 29, 1189-1232(2001).

[69] LECUN Y, BOTTOU L, BENGIO Y et al. Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 86, 2278-2324(1998).

[70] KRIZHEVSKY A, SUTSKEVER I, HINTON G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90(2017).

[71] SZEGEDY C, LIU W, JIA Y Q et al. Going deeper with convolutions[C], 1-9(2015).

[72] SIMONYAN K, ZISSERMAN A. Very Deep Convolutional Networks for Large-scale Image Recongnition[J]. Computer Science(2014).

[73] LI H L, ZHANG Z H, JIANG F et al. An event recognition method for fiber distributed acoustic sensing systems based on the combination of MFCC and CNN[C], 28, 1061804(2018).

[74] SHI Y, WANG Y Y, WANG L Y et al. Multi-event classification for Φ-OTDR distributed optical fiber sensing system using deep learning and support vector machine[J]. Optik, 221, 165373(2020).

[75] SUN Q, LI Q J, CHEN L et al. Pattern recognition based on pulse scanning imaging and convolutional neural network for vibrational events in Φ-OTDR[J]. Optik, 219, 165205(2020).

[76] RUAN S S, MO J Q, XU L et al. Use AF-CNN for end-to-end fiber vibration signal recognition[J]. IEEE Access, 9, 6713-6720(2021).

[77] HUO Z Q, LIU Y G et al. Robust intrusion events recognition methodology for distributed optical fiber sensing perimeter security system[J]. IEEE Transactions on Instrumentation and Measurement, 70, 1-9(2021).

[78] GIRAUD-CARRIER C, VILALTA R, BRAZDIL P. Introduction to the special issue on meta-learning[J]. Machine Learning, 54, 187-193(2004).

[79] HOCHREITER S, SCHMIDHUBER J. Long short-term memory[J]. Neural Computation, 9, 1735-1780(1997).

[80] BAI Y, XING J C, XIE F et al. Detection and identification of external intrusion signals from 33 km optical fiber sensing system based on deep learning[J]. Optical Fiber Technology, 53, 102060(2019).

[81] LI Z Q, ZHANG J W, WANG M N et al. Fiber distributed acoustic sensing using convolutional long short-term memory network： a field test on high-speed railway intrusion detection[J]. Optics Express, 28, 2925-2938(2020).

[82] LI Z Q, ZHANG J W, WANG M N et al. An anti-noise ϕ-OTDR based distributed acoustic sensing system for high-speed railway intrusion detection[J]. Laser Physics, 30(2020).

[83] WANG Z D, LOU S Q, WANG X et al. Multi-branch long short-time memory convolution neural network for event identification in fiber-optic distributed disturbance sensor based on φ-OTDR[J]. Infrared Physics & Technology, 109, 103414(2020).

[84] WU H J, YANG M R, YANG S Q et al. A novel DAS signal recognition method based on spatiotemporal information extraction with 1DCNNs-BiLSTM network[J]. IEEE Access, 8, 119448-119457(2020).