Abstract
The recognition of human movements based on radar m-D (micro-Doppler) signatures attracts great interest in the field of radar research on automatic target recognition. Because there are multiple frequency components overlapping seriously in the radar echoes from walking humans, it is a very difficult work to recognize walking humans based on radar echoes. In this paper, a recognition method of walking humans based on radar m-D signatures is proposed. In this method, the m-D spectrum is generated by generalized S transform first, and then the entropy segmentation is used to segment the interesting region from the original spectrum. Next, the m-D features are extracted from the m-D region. Lastly, the support vector machine is used to recognize different walking human targets. The simulation experiments considering two factors of height and velocity are also conducted to test the performance of this proposed method.
摘要
创新点
本文基于雷达微多普勒特征, 提出了一种识别单行人和多行人的方法. 主要创新点包括: 应用广义 s 变换对行人的微多普勒谱进行分析, 时频分辨率高于传统的短时傅里叶变换; 应用信息熵分割微多普勒谱, 去除只包含噪声的部分, 减小特征提取的计算量, 也在一定程度上减小噪声的影响; 提出躯干分量和脚部分量的微多普勒谱分离方法和特征提取方法; 采用躯干和脚部的四个特征对单行人和多行人进行识别, 分类特征少, 计算量小;
Similar content being viewed by others
References
Chen V C. Spatial and temporal independent component analysis of micro-Doppler features. In: Proceedings of IEEE International Radar Conference, Arlington, 2005. 348–353
Dustin P F, Ram M N. Classification and modeling of human activities using empirical mode decomposition with Sband and millimeter-wave micro-Doppler radars. In: Proceedings of SPIE, Radar Sensor Technology XVI, Baltimore, 2012. 83610X
Li J, Phung S L, Tivive F H C, et al. Automatic classification of human motions using Doppler radar. In: Proceedings of IEEE World Congress on Computational Intelligence, Brisbane, 2012. 1–6
Tivive F H C, Phung S, Bouzerdoum A. An image-based approach for classification of human micro-Doppler radar signatures. In: Proceedings of SPIE, Active and Passive Signatures IV, Baltimore, 2013. 873406
Chen V C, Li F, Ho S S, et al. Micro-Doppler effect in radar: phenomenon, model, and simulation study. IEEE Trans Aero Electron Syst, 2006, 42: 2–21
Chen V C. Doppler signatures of radar backscattering from objects with micro-motions. IET Signal Process, 2008, 2: 291–300
Chen V C. Detection and analysis of human motion by radar. In: Proceedings of IEEE Radar Conference, Rome, 2008. 1–4
Kim Y, Ling H. Human activity classification based on micro-Doppler signatures using a support vector machine. IEEE Trans Geosci Remote Sens, 2009, 47: 1328–1337
Tahmoush D, Silvious J. Human polarimetric micro-Doppler. In: Proceedings of SPIE, Radar Sensor Technology XV, Orlando, 2011. 802106
Smith G E, Woodbridge K, Baker C J. Radar micro-Doppler signature classification using dynamic time warping. Trans Aero Electron Syst, 2010, 46: 1078–1095
Thayaparan T, Stankoisa L, Djurovic I, et al. Intelligent target recognition using micro-Doppler radar signatures. In: Proceedings of SPIE, Radar Sensor Technology XIII, Orland, 2009. 730817
Thayaparan T, Stankovi´c L, Djurovi´c I. Micro-Doppler-based target detection and feature extraction in indoor and outdoor environments. J Franklin Inst, 2008, 345: 700–722
Thayaparan T, Abrol S, Riseborough E, et al. Analysis of radar micro-Doppler signatures from experimental helicopter and human data. IET Radar Sonar Navig, 2007, 1: 289–299
Thayaparan T, Suresh P, Qian S, et al. Micro-Doppler analysis of a rotating target in synthetic aperture radar. IET Signal Process, 2010, 4: 245–255
Luo Y, Zhang Q, Qiu C, et al. Micro-Doppler effect analysis and feature extraction in ISAR imaging with steppedfrequency chirp signals. IEEE Trans Geosci Remote Sens, 2010, 48: 2087–2098
Wu X F, Wang X S, Lu H Z. Motion feature extraction for stepped frequency radar based on Hough transform. IET Radar Sonar Navig, 2010, 4: 17–27
Ai X, Li Y, Wang X, et al. Feature extraction of rotational targets in wideband T/R-R bistatic radar. IET Radar Sonar Navig, 2013, 7: 351–360
Luo Y, Zhang Q, Qiu C, et al. Micro-Doppler feature extraction for wideband imaging radar based on complex image orthogonal matching pursuit decomposition. IET Radar Sonar Navig, 2013, 7: 914–924
Guo K Y, Sheng X Q. Precise recognition of warhead and decoy based on components of micro-Doppler frequency curves. Sci China Inf Sci, 2012, 55: 850–856
Li G, Varshney P K. Micro-Doppler parameter estimation via parametric sparse representation and pruned orthogonal matching pursuit. IEEE J Sel Top Appl Earth Observations Rem Sens, 2014, 7: 4937–4948
Balleri A, Chetty K, Woodbridge K. Classification of personnel targets by acoustic micro-Doppler signatures. IET Radar Sonar Navig, 2011, 5: 943–951
Boulic R, Thalmann M N, Thalmann D. A global human walking model with real time kinematic personification. Vis Comput, 1990, 6: 344–356
Dorp P, Groen F C A. Human walking estimation with radar. IEE Proc Radar Sonar Navig, 2003, 150: 356–365
Chen V C. The Micro-Doppler Effect in Radar. Norwood: Artech House Press, 2011. 161–176
Stockwell R G, Mansinha L, Lowe R P. Localization of the complex spectrum: the S transform. IEEE Trans Signal Process, 1996, 44: 998–1001
Shannon C E. A mathematical theory of communication. Mob Comput Commun Rev, 2001, 5: 3–55
Lei P, Wang J, Guo P, et al. Automatic classification of radar targets with micro-motions using entropy segmentation and time-frequency features. Int J Electron Commun, 2011, 65: 806–813
Geisheimer J L, Greneker E F, Marshall W S. A high-resolution Doppler model of human gait. In: Proceedings of SPIE, Radar Sensor Technology and Data Visualization, Orland, 2002. 8–18
Hsu C W, Lin C J. A comparison of methods for multiclass support vector machines. IEEE Trans Neural Netw, 2002, 13: 415–425
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Sun, Z., Wang, J., Zhang, Y. et al. Multiple walking human recognition based on radar micro-Doppler signatures. Sci. China Inf. Sci. 58, 1–13 (2015). https://doi.org/10.1007/s11432-015-5327-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11432-015-5327-5