基于小波变换与奇异值分解的飞鸟动态电磁散射特征提取

doi:10.16088/j.issn.1001-6600.2023062401

摘要/Abstract

摘要： 雷达探鸟是航空安全、环境生态等领域的热点问题。鸟类目标的雷达散射截面(RCS)较小,散射特征单一,给鸟类探测带来诸多挑战。为解决这些问题,本文提出一种基于小波变换与奇异值分解的飞鸟目标动态电磁散射特征提取方法。首先将飞鸟扑翼频率为2～20 Hz的动态RCS序列进行小波变换得到各分支小波系数,再对各分支小波系数进行重构,将小波系数组成的特征矩阵进行奇异值分解,用特征值对飞鸟动态电磁散射特征进行量化描述。为了验证该方法的有效性,本文在盘旋航迹和平飞航迹、水平极化和垂直极化下分别进行入射频率为0.5、1和3 GHz的数值实验对方法进行验证。结果表明特征值与飞鸟的扑翼频率呈现明显线性相关关系,能够有效反映飞鸟的运动特性,为鸟类目标的雷达探测与识别提供新的视角和思路。

关键词: 小波变换, 奇异值分解, 动态RCS, 扑翼频率, 特征提取

Abstract: Radar bird detection is a hot issue in the fields of aviation safety and environmental ecology. The radar scattering cross section (RCS) of bird targets is small and the scattering features are single, which brings many challenges to bird detection. To solve these problems, a dynamic electromagnetic scattering feature extraction method based on wavelet transform and singular value decomposition for flying bird targets is proposed. Firstly, the dynamic RCS sequence of the flying bird with flapping frequency of 2-20 Hz is wavelet transformed to obtain the wavelet coefficients of each branch, and then the wavelet coefficients of each branch are reconstructed. The feature matrix composed of wavelet coefficients is decomposed by singular value to quantitatively describe the dynamic electromagnetic scattering features of the flying bird with eigenvalues. To verify the validity of the method, numerical experiments with incident frequencies of 0.5, 1, and 3 GHz are conducted in this paper under circling and leveling trajectories, horizontal polarization, and vertical polarization, respectively. The results show that the eigenvalues show obvious linear correlation with the flapping frequency of the flying bird, which can effectively reflect the motion characteristics of the flying bird and provide new perspectives and ideas for the radar detection and identification of bird targets.

Key words: wavelet transform, singular value decomposition, dynamic radar cross section, flapping frequency, feature extraction

中图分类号: TN957.51

黄润琴, 苏珉, 刘佳, 王涛. 基于小波变换与奇异值分解的飞鸟动态电磁散射特征提取[J]. 广西师范大学学报（自然科学版）, 2024, 42(4): 74-89.

HUANG Runqin, SU Min, LIU Jia, WANG Tao. Avian Dynamic Electromagnetic Scattering Feature Extraction Based on Wavelet Transform and Singular Value Decomposition[J]. Journal of Guangxi Normal University(Natural Science Edition), 2024, 42(4): 74-89.

参考文献

[1] Federal Aviation Administration. Reporting wildlife aircraft strikes: AC 150/5200-32B[R]. Washington, D.C.: Federal Aviation Administration, 2013.
[2] 陈唯实,刘佳,陈小龙,等.基于运动模型的低空非合作无人机目标识别[J].北京航空航天大学学报,2019,45(4):687-694.DOI: 10.13700/j.bh.1001-5965.2018.0447.
[3] 陈唯实,黄毅峰,陈小龙,等.机场探鸟雷达技术发展与应用综述[J].航空学报,2022,43(1):024758.DOI: 10.7527/S1000-6893.2020.24758.
[4] 黄培康,殷红成,许小剑.雷达目标特性[M].北京:电子工业出版社,2005:10-12.
[5] 黄小红,马云,陈曾平.利用RCS序列估计空间目标尺寸的方法研究[J].信号处理,2005,21(6):639-641.DOI: 10.3969/j.issn.1003-0530.2005.06.016.
[6] 戴崇,徐振海,肖顺平.雷达目标动静态RCS特性差异分析[J].信号处理,2013,29(9):1256-1263.DOI: 10.3969/j.issn.1003-0530.2013.09.025.
[7] FLOCK W L, GREEN J L. The detection and identification of birds in flight, using coherent and noncoherent radars[J]. Proceedings of the IEEE, 1974, 62(6): 745-753. DOI: 10.1109/PROC.1974.9513.
[8] LIU J, FANG N, WANG B F, et al. A novel dynamic RCS simulation and analysis method considering attitude perturbation[J]. Journal of Electromagnetic Waves and Applications, 2015, 29(14): 1841-1858. DOI: 10.1080/09205071.2015.1051189.
[9] TORVIK B, KNAPSKOG A, LIE-SVENDSEN Ø, et al. Amplitude modulation on echoes from large birds[C] //2014 11th European Radar Conference. Piscataway, NJ: IEEE Press, 2014: 177-180. DOI: 10.1109/EuRAD.2014.6991236.
[10] WALHEIM J, GOTSCHY A, KOZERKE S. On the limitations of partial Fourier acquisition in phase-contrast MRI of turbulent kinetic energy[J]. Magnetic Resonance in Medicine, 2019, 81(1): 514-523. DOI: 10.1002/mrm.27397.
[11] 何炜琨,张鑫蕴,王晓亮,等.阵列雷达鸟类回波信号精细建模与特征分析[J].仪器仪表学报,2021,42(9):262-270.DOI: 10.19650/j.cnki.cjsi.J2107972.
[12] WEI M H, YANG J W, YAO D C, et al. Fault diagnosis of bearings in multiple working conditions based on adaptive time-varying parameters short-time Fourier synchronous squeeze transform[J]. Measurement Science and Technology, 2022, 33(12): 124002. DOI: 10.1088/1361-6501/ac8abf.
[13] HU C, LANG T J, WANG R, et al. Electromagnetic scattering characteristics of flapping bird and experimental validation[J]. The Journal of Engineering, 2019, 2019(19): 5860-5863. DOI: 10.1049/joe.2019.0460.
[14] YU Y L, LI W, SHENG D R, et al. A novel sensor fault diagnosis method based on Modified Ensemble Empirical Mode Decomposition and Probabilistic Neural Network[J]. Measurement, 2015, 68: 328-336. DOI: 10.1016/j.measurement.2015.03.003.
[15] 刘凯越,张晨新,刘刚,等.基于扑翼模型的鸟类目标动态RCS的仿真研究[J].微波学报,2016,32(4):15-20.DOI: 10.14183/j.cnki.1005-6122.201604004.
[16] 梁镇锋,夏海英.一种面向无人机航拍图像的快速拼接算法[J].广西师范大学学报(自然科学版),2023,41(3):41-52.DOI: 10.16088/j.issn.1001-6600.2022060202.
[17] 梁钰婷,罗玉玲,张顺生.基于压缩感知的混沌图像加密研究综述[J].广西师范大学学报(自然科学版),2022,40(5):49-58.DOI: 10.16088/j.issn.1001-6600.2022012003.
[18] 李威京,蒋俊正.一种改进雅可比算法的频域临界采样图滤波器组[J].桂林电子科技大学学报,2023,43(3):202-209.DOI: 10.16725/j.cnki.cn45-1351/tn.2023.03.005.
[19] 文刚,马仪,周仿荣,等.基于WAResNet和GS+ATPRK的多光谱和全色影像融合[J].桂林理工大学学报,2023,43(2):326-332.
[20] 李志茹,陈元枝,姜文英,等.基于彩色QR码的信息无损提取隐藏算法[J].桂林电子科技大学学报,2023,43(1):56-62.DOI: 10.16725/j.cnki.cn45-1351/tn.2023.01.006.
[21] WALDSPURGER I. Phase retrieval for wavelet transforms[J]. IEEE Transactions on Information Theory, 2017, 63(5): 2993-3009. DOI: 10.1109/TIT.2017.2672727.
[22] YAN L J, LIU Y S, LIU Y. Application of discrete wavelet transform in shapelet-based classification[J]. Mathematical Problems in Engineering, 2020, 2020: 6523872. DOI: 10.1155/2020/6523872.
[23] DE WIT JJ M, HARMANNY R I A, MOLCHANOV P. Radar micro-Doppler feature extraction using the Singular Value Decomposition[C] //2014 International Radar Conference. Piscataway, NJ: IEEE Press, 2014: 1-6. DOI: 10.1109/RADAR.2014.7060268.
[24] ZHANG G, XU B B, ZHANG K S, et al. Research on a noise reduction method based on multi-resolution singular value decomposition[J]. Applied Sciences, 2020, 10(4): 1409. DOI: 10.3390/app10041409.
[25] ZHANG X, ZHANG C C, WEI Z Q. Carbon price forecasting based on multi-resolution singular value decomposition and extreme learning machine optimized by the moth-flame optimization algorithm considering energy and economic factors[J]. Energies, 2019, 12(22): 4283. DOI: 10.3390/en12224283.
[26] FUHRMANN L, BIALLAWONS O, KLARE J, et al. Micro-Doppler analysis and classification of UAVs at Ka band[C] //2017 18th International Radar Symposium (IRS). Piscataway, NJ: IEEE Press, 2017: 1-9. DOI: 10.23919/IRS.2017.8008142.
[27] 何炜琨,柳振明,王晓亮.微动特征和运动特征融合处理的鸟与旋翼无人机目标辨别方法[J].电子测量与仪器学报,2022,36(7):33-43.DOI: 10.13382/j.jemi.B2205540.
[28] 刘东,王昕,黄建荧,等.基于小波变换与SVD的水电机组振动信号特征提取研究[J].中国农村水利水电,2018(12):169-172.DOI: 10.3969/j.issn.1007-2284.2018.12.034.
[29] TSAI M J, LIU J, YIN J S, et al. A visible wavelet watermarking technique based on exploiting the contrast sensitivity function and noise reduction of human vision system[J]. Multimedia Tools and Applications, 2014, 72(2): 1311-1340. DOI: 10.1007/s11042-013-1423-y.
[30] 顾秀秀,朱明亮,王璐,等.基于小波变换的心电信号特征提取[J].软件导刊,2021,20(5):77-81.DOI: 10.11907/rjdk.201987.
[31] FAZLI S, MOEINI M. A robust image watermarking method based on DWT, DCT, and SVD using a new technique for correction of main geometric attacks[J]. Optik, 2016, 127(2): 964-972. DOI: 10.1016/j.ijleo.2015.09.205.
[32] FEKO 7.0, Altair, 2005-2014 EM software & systems-S.A. (Pty) Ltd.[EB/OL].[2023-06-20]. https://www.altair.com/feko/.
[33] MOON J R. Effects of birds on radar tracking systems[C] //RADAR 2002. Edinburgh, UK: IET, 2002: 300-304. DOI: 10.1109/RADAR.2002.1174701.
[34] POLLACCO D A, FARINA L, WISMAYER P S, et al. Characterization of the dielectric properties of biological tissues and their correlation to tissue hydration[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2018, 25(6): 2191-2197. DOI: 10.1109/TDEI.2018.007346.
[35] 周超,张小宽,吴国成.基于坐标转换目标动态RCS时间序列研究[J].火力与指挥控制,2014,39(3):56-59.DOI: 10.3969/j.issn.1002-0640.2014.03.015.
[36] JIANG H M, CHEN J, DONG G M, et al. Study on Hankel matrix-based SVD and its application in rolling element bearing fault diagnosis[J]. Mechanical Systems and Signal Processing, 2015, 52/53: 338-359. DOI: 10.1016/j.ymssp.2014.07.019.
[37] 张继龙,刘玮,郑向理,等.鸟群类自然干扰目标的雷达探测与识别[J].电子信息对抗技术,2019,34(3):24-27,33.DOI: 10.3969/j.issn.1674-2230.2019.03.006.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed