ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Micro-motion feature and shape parameters extraction based on hybrid-scheme radar network for ballistic targets
Received date: 2015-07-13
Revised date: 2016-02-29
Online published: 2016-03-04
Supported by
National Natural Science Foundation of China ( 61372166, 61501495): The Project Supported by Natural Science Basic Research Plan in Shaanxi Province of China (2014JM8308)
Aiming at the complexity of recognition and resolution on ballistic mid-course target, a method for three-dimensional reconstruction of ballistic target based on hybrid-scheme radar network combined low-resolution radar with high-resolution radar is proposed. Based on the separable model of nonlinear signal parameter, the amplitude-phase parameters of each scattering center on the ballistic target group with empennages are calculated by nonlinear least squares estimation method. Combined with the relationship of micro-motion features between radars, various scattering centers are separated by association processing between scattering centers. Ultimately, the three-Dimensional micro-motion features and the three-Dimensional position vectors are reconstructed by utilizing both the micro-Doppler characteristics and the relative position relation of each scattering center of ballistic target, and then the precession feature and structural parameters are estimated. Simulation results validate that the reconstruction precision of three-dimensional features has been maintained at about 92% when the signal noise ratio (SNR) is 5 dB.
LI Jingqing , FENG Cunqian , SUN Hongwei , HE Sisan . Micro-motion feature and shape parameters extraction based on hybrid-scheme radar network for ballistic targets[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2016 , 37(6) : 1963 -1973 . DOI: 10.7527/S1000-6893.2016.0054
[1] CHEN V C. Advances in applications of radar micro-Doppler signatures[C]//Proceeding of IEE Antenna Measurements & Application, 2014:1-4.
[2] LIU Z, WEI X Z, LI X. Aliasing-free micro-Doppler analysis based on short-time compressed sensing[J]. IET Signal Processing, 2014, 8(2):176-187.
[3] CHEN V C. The micro-Doppler effect in radar[M]. London:Artech House, 2011:24-33.
[4] SMITH G E, WOODBRIDGE K, BAKER C J, et al. Multistatic micro-Doppler radar signatures of personnel targets[J]. IET Signal Processing, 2010, 4(3):224-233.
[5] VESPE M, BAKER C, GRIFFITHS H. Radar target classification using multiple perspectives[J]. IET Radar, Sonar & Navigation, 2007, 1(4):300-307.
[6] 韩勋, 杜兰, 刘宏伟. 基于窄带雷达组网的空间锥体目标特征提取方法[J]. 电子与信息学报, 2014, 36(12):2956-2962. HAN X, DU L, LIU H W. Feature extraction of space cone-shaped target based on narrow-band radar network[J]. Journal of Electronics & Information Technology, 2014, 36(12):2956-2962(in Chinese).
[7] 向道朴. 微多普勒回波模拟与微动特征提取技术研究[D]. 长沙:国防科学技术大学, 2010:95-111. XIANG D P. Research on micro-Doppler echo simulation and micro-motion signature extraction technology[D]. Changsha:National University of Defense Technology, 2010:95-111(in Chinese).
[8] 张栋, 冯存前, 贺思三, 等. 组网雷达弹道目标三维进动特征提取[J]. 西安电子科技大学学报, 2015, 42(2):146-151. ZHANG D, FENG C Q, HE S S, et al. Extraction of three-dimensional precession features of ballistic targets in netted radar[J]. Journal of Xidian University, 2015, 42(2):146-151(in Chinese).
[9] LUO Y, ZHANG Q, YUAN N, et al. Three-dimensional precession feature extraction of space targets[J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(2):1313-1329.
[10] AI X F, HUANG Y, ZHAO F, et al. Imaging of spinning targets via narrow-band T/R-R bistatic radars[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(2):362-366.
[11] PAN X Y, WANG W, LIU J, et al. Modulation effect and inverse synthetic aperture radar imaging of rotationally symmetric ballistic targets with precession[J]. IET Radar, Sonar & Navigation, 2013, 7(9):950-958.
[12] CAMP W W, JOSEPH T M, O' DONNELL R M. Wideband radar for ballistic missile defense and range-Doppler imaging of satellites[J]. Lincoln Laboratory Journal, 2000, 2(2):267-268.
[13] GUO K Y, SHENG X Q. Precise recognition of warhead and decoy based on components of micro-Doppler frequency curves[J]. Science China Information Sciences, 2012, 55(4):850-856.
[14] BARHAT M. Signal detection and estimation[M]. London:Artech House, 2005:576-580.
[15] WANG J, LEI P, SUN J P, et al. Spectral characteristics of mixed micro-Doppler time-frequency data sequences in micro-motion and inertial parameter estimation of radar targets[J]. IET Radar, Sonar & Navigation, 2014, 8(4):275-281.
[16] SHAO C Y, DU L, HAN X. Multiple target tracking based separation of micro-Doppler signals from coning target[C]//Proceeding of IEEE Radar Conference. Piscataway, NJ:IEEE Press, 2014:130-133.
[17] 李靖卿, 冯存前, 张栋. 基于自适应视野聚类匹配的多目标分离与提取[J]. 系统工程与电子技术, 2015, 37(9):1974-1979. LI J Q, FENG C Q, ZHANG D. Multi-target separation and extraction based on adaptive vision cluster matching[J]. Systems Engineering and Electronics, 2015, 37(9):1974-1979(in Chinese).
[18] 张群, 罗迎. 雷达目标微多普勒效应[M]. 北京:国防工业出版社, 2013:22-81. ZHANG Q, LUO Y. Micro-Doppler effect of radar targets[M]. Beijing:National Defense Industry Press, 2013:22-81(in Chinese).
[19] ALEX R, ALESSANDRO L. Clustering by fast search and find of density peaks[J]. Science, 2014, 344(6):1492-1496.
[20] 李孝辉, 杨旭海, 刘娅, 等. 时间频率信号的精密测量[M]. 北京:科学出版社, 2010:162-180. LI X H, YANG X H, LIU Y, et al. Precise measure of time-frequency signature[M]. Beijing:Science Press, 2010:162-180(in Chinese).
[21] OSSAMA A, AHMED G. Dynamic-size multiple populations genetic algorithm for multigravity-assist trajectory optimization[J]. Journal of Guidance, Control, and Dynamics, 2012, 35(2):520-529.
/
| 〈 |
|
〉 |
CJA