Study on CA-CFAR Algorithm Based on Normalization Processing of Background Noise for HI of Optical Fiber

Abstract

Optical fiber pre-warning system (OFPS) is often used to monitor the occurrence of disasters such as the leakage of oil and natural gas pipeline. It analyzes the collected vibration signals to judge whether there is any harmful intrusion (HI) events. At present, the research in this field is mainly focused on the constant false alarm rate (CFAR) methods and derivative algorithms to detect intrusion signals. However, the performance of CFAR is often limited to the actual collected signals distribution. It is found that the background noise usually obeys non-independent and identically distribution (Non-IID) through the statistical analysis of acquisition signals. In view of the actual signal distribution characteristics, this paper presents a CFAR detection method based on the normalization processing for background noise. A high-pass filter is designed for the actual Non-IID background noise data to obtain the characterization characteristic. Then, the background noise is converted to independent and identically distribution (IID) by using the data characteristic. Next, the collected data after normalization is processed with efficient cell average constant false alarm rate (CA-CFAR) method for detection. Finally, the results of experiments both show that the intrusion signals can be effectively detected, and the effectiveness of the algorithm is verified.

Keywords

OFPS / HI / CA-CFAR / normalization / Non-IID

References

[1] Liang W., Lu L. L., Zhang L. B.. Coupling relations and early-warning for ‘equipment chain’ in long-distance pipeline. Mechanical Systems and Signal Processing, 2013, 41(1–2): 335-347.

[2] Qiu J. W., Liang W., Zhang L. B., Yu X. H., Zhang M.. The early-warning model of equipment chain in gas pipeline based on DNN-HNM. Journal of Natural Gas Science & Engineering, 2015, 27, 1710-1722.

[3] Jing K., Zou Z. H.. Time prediction model for pipeline leakage based on grey relational analysis. Physics Procedia, 2012, 25(2): 2019-2024.

[4] Zhang Y. X., Xu Y. M., Shan Y. Y., Sun Z. H., Zhu F., Zhang X. P.. Polarization dependence of phase-sensitive optical time-domain reflectometry and its suppression method based on orthogonal-state. Optical Engineering, 2016, 55(7): 074109.

[5] Liang S., Sheng X. Z., Lou S. Q., Feng Y., Zhang K. N.. Combination of phase-sensitive OTDR and Michchelson interferometer for nuisance alarm rate reduction. IEEE Photonics Journal, 2016, 8(2): 1-12.

[6] Wu H. J., Xiao S. K., Li X. Y., Wang Z. N., Xu J. W., Rao Y. J.. Separation and determination of the disturbing signals in phase-sensitive optical time domain reflectometry (Φ-OTDR). Journal of Lightwave Technology, 2015, 33(15): 3156-3162.

[7] Xie S. R., Zhang M.. Ultra long distance distributed fiber-optic system for intrusion detection. Advanced Sensor Systems & Applications V, 2012, 8561(3): 85611W.

[8] Finn H. M., Johnson R. S.. Adaptive detection mode with threshold control as a function of spatially sampled clutter-level estimates. RCA Review, 1968

[9] Bi F. K., Feng C., Qu H. Q., Zheng T.. Harmful intrusion detection algorithm of optical fiber pre-warning system based on correlation of orthogonal polarization signals. Photonic Sensors, 2017, 7(3): 226-233.

[10] Qiu Z., Zheng T., Qu H. Q., Pang L. P.. A new method based on CFAR and DE for OFPS. Photonic Sensors, 2016, 6(3): 261-267.

[11] Bi F. K., Ren X. C., Qu H. Q., Jiang R. Q.. A two-level detection algorithm for optical fiber vibration. Photonic Sensors, 2015, 5(3): 284-288.

[12] Qu H., Ren X., Li G., Li Y., Zhang C.. Study on the algorithm of vibration source identification based on the optical fiber vibration pre-warning system. Photonic Sensors, 2015, 5(2): 180-188.

[13] Zaimbashi A.. An adaptive cell averaging-based CFAR detector for interfering targets and clutter-edge situations. Digital Signal Processing, 2014, 31(5): 59-68.

[14] Qu H. Q., Zheng T., Pang L. P., Li X. L.. A new two-dimensional method to detect harmful intrusion vibrations for optical fiber pre-warning system. Optik, 2016, 127(10): 4461-4469.