Signal Recognition Technology of Sky Screen Based on Neural Network

doi:10.3969/j.issn.1000-1093.2014.10.011

Abstract

Abstract: The effects of interference factors, such as shock wave of warhead blasting, projectile base shock, aerial birds, insects, vibration, etc.,on sky screen system are analyzed to improve its test accuracy and reliability. The approach of Hopfield auto-associative neural network is used to identify and eliminate the typical interference. The accuracy and reliability of sky screen systemthe is fully validated by analyzing the data from live firing. The results show that, compared with the level signal recognition, Hopfield auto-associative neural network recognition rate can be increased by 17.2% in sky screen test with the 5 bursts in RF/min; Hopfield auto-associative neural network recognition rate is increased by 46.7% in sky screens test of 23 mm caliber armor-piercing shells; under the test condition of firing frequency of 7 500 rounds / minute, the correct signal recognition rate reaches to 93%. In a complex environment, the recognition rate Hopfield neural network algorithm is far higher than traditional level recognition rate，which improve the signal recognition rate and be able to adapt to the complex environmental factors within a region.

Key words: information processing technology, sky screen, interference noise, Hopfield auto-associative neural network, recognition rate

CLC Number:

TN911.7

LOU Yan, ZHAO Yi-wu, SONG Yu-gui, ZHANG Wei-fang. Signal Recognition Technology of Sky Screen Based on Neural Network[J]. Acta Armamentarii, 2014, 35(10): 1587-1594.

References

［1］ Cnapp C H I, Carter G C. The generalized correlation method for estimation of time delay[J]. IEEE Trans Acoust Speech Signal Processing,1976,24(8):320-327.
[2］宋玉贵, 倪晋平, 王铁岭, 等. 多光幕交汇法测量目标飞行坐标的原理与精度分析［J］. 西安工业大学学报, 2007, 27(1): 19-25.
SONG Yu-gui, NI Jin-ping, WANG Tie-ling,et al. Principle of six screens target measuring system for bullet location and its error analysis[J].Journal of Xi’an Technological University,2007, 27(1): 19-25.(in Chinese)
[3］董涛,倪晋平,宋玉贵，等.高射频武器弹丸连发速度测量系统[J].弹道学报,2010,22(1):34-36.
DONG Tao, NI Jin-ping, SONG Yu-gui, et al. Velocity measurement system of high-frequency string firing bullet[J]. Journal of Ballistics,2010,22(1):34-36.(in Chinese)
[4］宋玉贵,王铁岭.天幕靶抗蚊虫干扰数字滤波电路设计[J].西安工业大学学报,1998,18(2):130-133.
SONG Yu-gui, WANG Tie-ling. Digital-filter used in sky screen to resist the interference caused by insects[J]. Journal of Xi’an Institute of Technology, 1998,18(2):130-133.（in Chinese）
[5］倪晋平,田会.斜入射弹丸着靶位置立靶测试原理[J].光学技术,2006,32(4):493-495.
NI Jin-ping，TIAN Hui. The principle of measuring position of bullet at any direction incidence[J]. Optical Technique，2006，32(4)： 493-495. （in Chinese）
[6］宋玉贵,倪晋平,王铁岭.多光幕交汇法测量目标飞行坐标的原理与精度分析[J].光学仪器,2007,29(8):11-26.
SONG Yu-gui, NI Jin-ping, WANG Tie-ling. Principle of six screens target measuring system for bullet location and its error analysis[J]. Optical Instrument,2007,29(8):11-26.（in Chinese）
[7］张军英,许进.一类离散Hopfield网络的吸引特性研究[J].电子与信息学报,2001,23(9):879-889.
ZHANG Jun-Ying, XU Jin. Approaches on attraction charactoristics of a kind of discrete Hopfield net works[J].Journal of Electronics & Information Technology, 2001, 23(9):879-889. （in Chinese）
[8］黄德双.神经网络模式识别系统理论[M].北京:电子工业出版社，1996.
HUANG De-shuang. Theory of neural network pattern recognition system[M].Beijing: Publishing House of Electronics Industry，1996. （in Chinese）
[9］ Hartati R S，EI-Hawary M E. A summary of application of Hopfield neural network to economic load dispatch[J]. Conferenceon Electrical and Computer Engineering,2000(2): 707-711.
[10］ Yalcinoz T, Altum H, Hasan U. Constrained economic dispatch with prohibited operating zones a hopfield neural network approach[C]∥ 10th Mediterranean Electro technical Conference. Cyprus：IEEE, 2000: 570-573.
[11］倪晋平，侯宏录,孙建，等. 基于六天幕靶弹丸弹道末端飞行速度的测试[J].测试技术学报，2007, 21(2):117-120.
NI Jin-ping,HOU Hong-lu, SUN Jian, et al.The velocity measurement of projectile in end trajectory with six sky-screen system[J]. Journal of Test and Measurement Technology, 2007, 21(2): 117-120. （in Chinese）

[1]	LIU Yong-qing， JIANG Shuo， YU Dong， SHAO Xiao-tian. Effect of Narrowband Interference Suppression on Pseudorandom Code Zero Value [J]. Acta Armamentarii, 2016, 37(2): 293-298.
[2]	GUAN Si-hai， LI Zhi, HUANG Hui, WANG Zhe. Modified Zero-Attracting l₀-NLMS Algorithm [J]. Acta Armamentarii, 2016, 37(11): 2170-2176.
[3]	JIAO Chuan-hai, LI Yong-cheng, XIE Kai, YANG Yun-fu. Wideband Compressed Blind Sensing without Reconstruction Based on Expectation Deviation and Generalized Likelihood RatioTest [J]. Acta Armamentarii, 2016, 37(10): 1837-1843.
[4]	GUO Ye-cai, WU Hua-peng, WANG Hui, ZHANG Miao-qing. DNA Genetic Bat Algorithm Based Fractionally Spaced Multi-modulus Algorithm [J]. Acta Armamentarii, 2015, 36(8): 1502-1507.
[5]	LIU Kun, MA Wen-ping, LIU Hong-ying. Speckle Suppression of Polarimetric Synthetic Aperture Radar Images Based on Sublook Data Correlation [J]. Acta Armamentarii, 2015, 36(7): 1288-1294.
[6]	GUO Ye-cai， ZHANG Miao-qing. A Multi-modulus Blind Equalization Algorithm Based on Shuffled Frog Leaping Algorithm [J]. Acta Armamentarii, 2015, 36(7): 1280-1287.
[7]	LI Zheng-zhou, HOU Qian, DAI Zhen, FU Hong-xia, GE Feng-zeng, JIN Gang. Dim Moving Target Detection Algorithm Based on Spatial-temporal Sparse Representation [J]. Acta Armamentarii, 2015, 36(7): 1273-1279.
[8]	ZHU Ming-qiang， HOU Jian-jun, LIU Ying ， LI Xu, TIAN Hong-juan. An Time Delay Difference Estimation Algorithm Based on Improved Unscented Particle Filter Suitable for Target Tracking inWireless Sensor Network [J]. Acta Armamentarii, 2015, 36(7): 1266-1272.
[9]	DENG Bing, LUAN Jun-bao. Study of Reconnaissance Reception Algorithm of Wide-band Channelization in the Fractional Fourier Domain [J]. Acta Armamentarii, 2015, 36(6): 1040-1045.
[10]	ZHU Xia, CHEN Ren-wen, XIA Hua-kang, ZHANG Piao-yan. A Novel Image Registration Based on Cultural Particle Swarm Optimization Algorithm [J]. Acta Armamentarii, 2015, 36(6): 1033-1039.
[11]	ZHANG Liang-jun, YANG Jie, LU Kai-wang, SUN Ya-dong. Underdetermined Blind Source Separation Based on Time-frequency Method Using Cyclostationary Characteristic [J]. Acta Armamentarii, 2015, 36(4): 703-709.
[12]	WU Yi-quan， SONG Yu. Background Suppression of Small Infrared Target Image Based on Nonsubsampled Complex Contourlet Transform and GaussianWavelet Support Vector Regression [J]. Acta Armamentarii, 2015, 36(4): 687-695.
[13]	JIANG Run-xiang， LIN Chun-sheng， GONG Shen-guang. Electrostatic Electric Field Inversion Method for Ship Based on Point Charge Source Model [J]. Acta Armamentarii, 2015, 36(3): 545-551.
[14]	WU Zhen， DAI Ji-sheng， ZHU Xiang-lin， ZHAO De-an. A Real-valued Sparse Representation Method for DOA Estimation with Unknown Mutual Coupling [J]. Acta Armamentarii, 2015, 36(2): 294-298.
[15]	ZHANG Dai, ZHANG Yu, YANG Xiao-jing, FAN Bin-bin. An Algorithm for Convolutional Codes Recognition Based on Sectionally Extracting Soft-decision Weighted Walsh HadamardTransform [J]. Acta Armamentarii, 2015, 36(12): 2298-2305.