A method of wall clutter removal for through-wall radar based on entropy of expanded antenna source

Li Jia-Qiang; Cai Hong-Yuan; Chen Jin-Li; Li Peng; Ge Jun-Xiang

doi:10.7498/aps.64.198402

Abstract

Strong front wall clutter has serious impacts on the target detection and imaging in the through-wall radar (TWR) system. A method of robust wall clutter suppression based on the entropy of an expanded antenna source for ultra-wide-band through-wall radar is presented in this paper. The model of TWR scenario consists of four layers. Assume that the first and the third layers are air space, while the second and the fourth layers are composed of uniform flat concrete wall. The circular target, assumed to be a perfect electric conductor, is located in the third layer. Along the measurement line which is parallel to the front wall, the transceiver antenna scans uniformly. The echo signals that come from the target and walls are processed into discrete data at first, so that the calculation of probability space is subsequently implemented and the discrete data are expanded as well. And then the entropy of the expanded data that contain robust wall clutter and echo of target is calculated. Taking into consideration the amplitude of target signal varying in each scan, while that of clutter signal is not, it is evident that the entropy can be utilized to discriminate the signals between the target and wall. According to the difference between the entropy of the wall clutter and that of the target, a certain threshold can be set and the optimum tolerance threshold is adaptively selected on the basis of target-to-clutter ratio. With the optimum tolerance threshold, process of clutter suppression is conducted. Finally, back projection is employed for imaging of target. In this paper, data of through-wall radar for simulation are provided by GprMax2D/3D, based on the finite difference-time domain methsd. The clutter suppression and imaging are separately conducted by the method based on data entropy and the method proposed in this paper. Comparing the results of simulations, it is shown that the gain of target-to-clutter ratio for the former is 15.51 dB, and that for the latter is 19.74 dB. It is obvious that the proposed method can provide imaging with higher quality for the same measurement, and it requires fewer scans with the same quality of imaging as well. Computational complexity of the proposed method and the method based on entropy can be expressed as O(M NL) and O(M N) , respectively

Keywords:

Authors and contacts

1.
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China;
2.
School of Electronic & Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China;
3.
Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing 210044, China

Corresponding author: Li Jia-Qiang, lijiaqiang@sina.com

Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 61372066, 61302188), the Natural Science Foundation of Jiangsu province, China (Grant No. BK20131005), and the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.

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Cited By

[1]	Zhao X L, Kang X, Chen L, Zhang Z B, Liu J L, Ouyang X P, Peng W B, He Y N 2014 Acta Phys. Sin. 63 098502(in Chinese) [赵小龙, 康雪, 陈亮, 张忠兵, 刘金良, 欧阳晓平, 彭文博, 贺永宁 2014 63 098502]
[2]	Yuan J R, Huang H B, Deng X H, Liang X J, Zhou N G, Zhou L 2015 Chin. Phys. B 24 048501
[3]	Wu S Y, Ding Y P, Chen C, Xu Y Y, Fang G Y, Yin H J 2012 Journal of Electronics 34 1277 (in Chinese) [吴世有, 丁一鹏, 陈超, 徐艳云, 方广有, 阴和俊 2012 电子与信息学报 34 1277]
[4]	M Demollaian, K Sarabandi 2008 IEEE Trans. Geosci. Remote Sens. 46 1589
[5]	R Solimene, F Soldovieri, G Prisco, R. Pierri 2009 IEEE Trans. Geosci. Remote Sens. 47 1310
[6]	Wang F F, Zhang Y R 2012 Acta Phys. Sin. 61 084101(in Chinese) [王芳芳, 张业荣 2012 61 084101]
[7]	Jia Y, Cui G L, Kong L J, Yang X B 2014 IEEE Geosci. Remote Sens. Lett. 11 970
[8]	Kevin Chetty, Graeme E Smith, Karl Woodbridge 2012 IEEE Trans. Geosci. Remote Sens. 50 1218
[9]	Colone F, Pastina D, Falcone P, Lombardo P 2014 IEEE Trans. Geosci. Remote Sens. 52 3486
[10]	Amin M G, Estephan H 2009 Proceedings of SPIE Orlando, Florida, USA, May, 2009 p6
[11]	Chang P C, Burkholder R J, Volakis J L 2010 IEEE Trans. Antennas and Propagation. 58 155
[12]	Admin M G, Ahmad F 2013 IEEE Trans. Aerosp. Electron. Syst. 49 1410
[13]	Zhao Z X, Kong L J, Ja Y, Li Z X 2014 Radar Science and Technology. 12 51 (in Chinese) [赵中兴, 孔令讲, 贾勇, 李志希 2014 雷达科学与技术 12 51]
[14]	GaikwadA N, Singh D, Nigam M J 2011 IET. Radar, Sonar Navigation.5 416
[15]	Tivive F H C, Bouzerdoum A, Amin M G 2015 IEEE Trans. Geosci. Remote Sens. 53 2108
[16]	Y Yoon, M Amin 2009 IEEE Trans. Geosci. Remote Sens. 47 3192
[17]	D Potin, E Duflos, P Vanheeghe 2006 IEEE Trans. Geosci.Remote Sens. 44 2393
[18]	M Dehmollaian, M Thiel, K Sarabandi 2009 IEEE Trans. Geosci. Remote Sens. 47 1289
[19]	Raffaele Solimene, Antonio Cuccaro 2014 IEEE Geosci. Remote Sens. Lett. 11 1158
[20]	Fu Z Y 2001 Information Theory-Principles and Applications (Beijing: Electronics Industry Press) pp38-40 (in Chinese) [傅祖芸 2001 信息论基础理论与应用(北京: 电子工业出版社)第2240页]
[21]	Shore J E, Johnson R W 1980 IEEE Trans. Inform. Theory. 26 26
[22]	Fok Hing Chi Tivive, Abdesselam Bouzerdoum, van Ha Tang 2014 Sensor Array and Multichannel Signal Processing Workshop (SAM), 2014 IEEE 8th A Coruna, Spain, June 22-25, 2014 p48

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Vol. 64, Issue 19 - 2015-10-05

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