||Application of Antenna Mode Switch and Polarization Diversity to Target Direction Finding and Recognition
||Department of Systems and Naval Mechatronic Engineering
Antenna Mode Switch
Principal Component Analysis
在估測到訊號源(即目標)的方向之後，我們希望可以進一步知道來源目標物是什麼？因此，本研究的第二部分主要探討應用極化分集雷達散射截面積(Radar Cross Section, RCS)於雷達目標辨識。我們利用電磁模擬軟體ANSYS-HFSS模擬目標物在不同極化條件下的散射電磁波，再結合主成份分析(Principal Component Analysis, PCA)訊號處理，來作雷達目標辨識。模擬結果顯示本論文所提出的雷達目標辨識演算法能夠達到高辨識率，且運算雷達散射截面積所需要的矩陣大小也大幅度縮小，且驗證了即使處在高雜訊的環境中，仍然能保有高準確率。
In this dissertation, delay-and-sum method, minimum variance distortionless response method, and antenna mode switch techniques are applied to target DOA (Direction-Of-Arrival) estimation. After the target DOA is successfully estimated, the antenna polarization diversity technique, RCS (Radar Cross Section) and PCA (Principal Component Analysis) are further applied to identify the type of a target.
In the first part of this research, two DOA estimation methods based on antenna mode switch techniques are utilized for improving the DOA estimation of incoming signals. The improvement of DOA estimation is implemented on conventional delay-and-sum method and minimum distortionless response, which are very simple and fast in calculation. With the use of antenna mode switch techniques, interferences from the antenna back lobe are greatly reduced and then the accuracy of DOA estimation is significantly improved. Moreover, the required size of an antenna array and its matrix calculation efforts can be decreased. To practically implement the above concept, a symmetric bow-tie antenna is proposed in this study. By measuring its gain pattern and then taking the resulting data as input to the above improved DOA algorithms, the results are very good and consistent with the simulation. To give insight into the theoretical support, we derived a novel formula to interpret the improvement of DOA estimation. Our derived formula clearly shows how antenna back lobes significantly interfere the DOA estimation of incoming signals. By this formula, the influence of array element spacing and accuracy of DOA estimation can be predicted. For the purpose of better accuracy, the antenna mode switch is further combined with the minimum variance distortionless response method for DOA estimation of incoming signals. It shows that the accuracy, successful recognition rate and ability of tolerating noise are significantly improved. With the use of such techniques, the required array element number and element spacing are decreased.
After the DOA of an incoming signal is successfully estimated, it further motivates us to identify the type of signal source, i.e., to recognize the target. In the second part of this research, the radar target recognition is given based on polarization-diversity RCS and PCA signal processing. The polarization-diversity of this study means changing the polarizations of incident waves and antennas. Without loss of generality, models of ships are used as targets of recognition for simplicity. The RCS is simulated by ANSYS-HFSS software. For consideration of better discrimination, noise-reduction and easy computation, the identification is implemented on PCA space. Simulation results show that the polarization-diversity based target recognition scheme can accurately identify the type of a target with less efforts of measurement. Simulation results also show that the proposed recognition scheme has good ability to tolerate random effects.
This dissertation is composed of seven chapters. Chapter 1 presents an introduction of this study. Chapter 2 gives basic theories utilized in this study. Chapter 3 shows the delay-and-sum DOA estimation of incoming signals is improved by our antenna mode switch technique and shows how the concept is implemented by a practical antenna design. In Chapter 4, we derive a novel formula for interpreting and predicting the improvement of DOA by using our antenna mode switch technique on delay-and-sum algorithms. In Chapter 5, the DOA estimation of incoming signals by minimum variance distortionless response method and antenna mode switch technique is presented. Chapter 6 shows the radar target recognition by polarization-diversity RCS on PCA space. Finally, conclusions of this research are given in Chapter 7.
1-1 Research Background 1
1-2 Motivation 3
1-3 Contribution 4
1-4 Dissertation overview 5
Basic Theory 11
2-1 Conventional Direction of Arrival Estimation 11
2-1-1 Delay and sum method 11
2-1-2 Capon method 12
2-2 Radar cross section 14
2-3 Polarization diversity technique 14
2-4 Principal component analysis 15
Reducing The Array Size for DOA Estimation by An Antenna Mode Switch Technique 21
3-1 Array analysis 22
3-2 Implementation of array element 26
3-3 Summary 28
A Novel Formula and Practical Antenna Design for 2-Element Antenna Mode Switch Techniques of DOA Estimation 46
4-1 Formulations and analysis 47
4-2 Practical Implementation for DOA Estimation 51
4-3 Summary 53
Improvement of Capon DOA Estimation by Antenna Mode Switch Techniques 64
5-1 Formulations and analysis 64
5-2 Simulation result 66
5-3 Summary 69
Radar Target Recognition by Polarization- Diversity RCS Including Random Effects 75
6-1 Formulations 76
6-2 Numerical simulation and analysis 79
6-3 Summary 82
7-1 Summary 95
7-2 Future work 97
 J. C. Liberti and T. S. Rappaport, Smart Antenna for Wireless Communications IS-95 and Third Generation CDMA Applications, NJ: Prentice Hall, 1999.
 K. C. Lee, “A genetic algorithm based direction finding technique with compensation of mutual coupling effects,” Journal of Electromagnetic Waves and Applications, Vol 17, pp. 1613-1624, 2003.
 S. C. Cheng and K. C. Lee., “Reducing the array size for DOA estimation by an antenna mode switch technique,” Progress In Electromagnetics Research, Vol. 131, pp.131-117, 2012.
 S. C. Cheng and K. C. Lee, “A novel formula and practical antenna design for 2-element antenna mode switch techniques of DOA estimation,” Electromagnetics , Vol 35, pp.124–137, 2015.
 G. T. Ruck, D. E. Barrick, W. D. Stuart and C.K. Krichbaum, Radar Cross Section Handbook, Vol. 1, Plenum, New York, 1970.
 J. Y. Jhang and K. C. Lee, “Array pattern optimization using electromagnetism-like algorithm,” AEU-Int J Electron Commun, Vol. 63, pp. 491–496, 2009.
 R. Goossens and H. Rogier, “Direction-of-arrival and polarization estimation with uniform circular arrays in the presence of mutual coupling,” AEU-Int. J. Electron Commun, Vol. 62, pp. 199–206, 2008.
 A. El-Keyia and T. Kirubarajan, “Adaptive beamspace focusing for direction of arrival estimation of wideband signals,” Signal Processing, Vol. 88, pp. 2063–2077, 2008.
 H. Zha, “Fast algorithms for direction-of-arrival finding using large ESPRIT arrays,” Signal Processing, Vol. 48, pp.111–121, 1996.
 N. Yilmazer and T. K. Sarkar, “2-D unitary matrix pencil method for efficient direction of arrival estimation,” Digital Signal Processing, Vol. 16, pp. 767-781, 2006.
 K. V. S. Babu, Y. Yoganandam and V. U. Reddy, “Adaptive estimation of eigensubspace and tracking the directions of arrival,” Signal Processing, Vol. 68, pp. 317–339, 1998.
 Y. Wua, G. Liaoa and H. C. So, “A fast algorithm for 2-D direction-of-arrival estimation,” Signal Processing, Vol. 83, pp. 1827–1831, 2003.
 M. A. Beygi and A. Olfat, “Subspace based direction of arrival estimation of DS-CDMA signals using orthogonal projection,” Signal Processing, Vol. 90, pp. 926–932, 2010.
 J. Verhaevert and E. V. Lil, “Capelin AV. Direction of arrival (DOA) parameter estimation with the SAGE algorithm,” Signal Processing, Vol. 84, pp. 619–629, 2004.
 M. Agrawala and S. Prasad, “Estimation of directions of arrival of wideband and wideband spread sources,” Signal Processing, Vol. 87, pp. 614–622, 2007.
 K. A. Gotsis, K. Siakavara and J. N. Sahalos, “On the direction of arrival (DOA) estimation for a switch-beam antenna system using neural networks,” IEEE Transaction on Antennas and Propagation, Vol. 57, pp. 1399-1411, 2009.
 M. R. Kamarudin, Y. I. Nechayev and P. S. Hall, “Onbody diversity and angle of arrival measurement using a pattern switching antenna,” IEEE Transaction on Antennas and Propagation, Vol. 57, pp. 964-971, 2009.
 F. Gross, Smart Antennas for Wireless Communications with MATLAB, McGraw-Hill, 2005.
 T. K. Sarkar, M. Salazar-Palma, M. C. Wicks and R. J. Bonneau, Smart Antennas, John Wiley & Sons, 2003.
 G. D. Durgin, Space-Time Wireless Channels, Prentice Hall, 2003.
 R. C. Hansen, Phased Array Antenna, Wiley, New York, 1998
 J. Yeo and J. Lee, “Miniaturized LPDA antenna for portable direction finding applications,” ETRI Journal, Vol.34, pp. 118-121, 2012.
 Y. Li, Y. J. Gu, Z. G. Shi and K. S. Chen, “Robust adaptive beamforming based on particle filter with noise unknown,” Progress In Electromagnetics Research, Vol. 90, pp. 151-169, 2009.
 M. Mouhamadou, P. Vaudon and M. Rammal, “Smart antenna array patterns synthesis: null steering and multi-user beamforming by phase control,” Progress In Electromagnetics Research, Vol. 60, pp. 95-106, 2006.
 Z. D. Zaharis, C. Skeberis and T. D. Xenos, “Improved antenna array adaptive beamforming with low side lobe level using a novel adaptive invasive weed optimization method,” Progress In Electromagnetics Research, Vol. 124, pp. 137-150, 2012.
 T. Hong, M. Z. Song and Y. Liu, “RF directional modulation technique using a switched antenna array for communication and direction-finding applications,” Progress In Electromagnetics Research, Vol. 120, pp. 195-213, 2011.
 P. Wounchoum, D. Worasawate, C. Phongcharoenpanich and M. Krairiksh, “A switched-beam antenna using circumferential-slots on a concentric sectoral cylindrical cavity excited by coupling slots,” Progress In Electromagnetics Research, Vol. 120, pp. 127-141, 2011.
 X. Wang, J. F. Chen, Z. G. Shi and K. S. Chen, “Fuzzy-control-based particle filter for maneuvering target tracking,” Progress In Electromagnetics Research, Vol. 118, pp. 1-15, 2011.
 J. H. Lee, Y. S. Jeong, S. W. Cho, W. Y. Yeo and K. S. J. Pister, “Application of the Newton method to improve the accuracy of toa estimation with the beamforming algorithm and the music algorithm,” Progress In Electromagnetics Research, Vol. 116, pp. 475-515, 2011.
 B. Tian, D. Y. Zhu and Z. D. Zhu, “A novel moving target detection approach for dual-channel SAR system,” Progress In Electromagnetics Research, Vol. 115, pp. 191-206, 2011.
 P. Yang, F. Yang and Z. P. Nie, “DOA estimation with sub-array divided technique and interporlated esprit algorithm on a cylindrical conformal array antenna,” Progress In Electromagnetics Research, Vol. 103, pp. 201-216, 2010.
 A. N. Jabbar, “A novel ultra-fast ultra-simple adaptive blind beamforming algorithm for smart antenna arrays,” Progress In Electromagnetics Research B, Vol. 35, pp. 329-348, 2011.
 R. Mallipeddi, J. P. Lie, P. N. Suganthan, S. G. Razul and C. M. S. See, “Near optimal robust adaptive beamforming approach based on evolutionary algorithm,” Progress In Electromagnetics Research B, Vol. 29, pp. 157-174, 2011.
 H. Peng, Z. Yang and T. Yang, “Calibration of a six-port receiver for direction finding using the artificial neural network technique,” Progress In Electromagnetics Research Letters, Vol. 27, pp. 17-24, 2011.
 Y. Liu, Q. Wan and X. Chu, “A robust beamformer based on weighted sparse constraint,” Progress In Electromagnetics Research Letters, Vol. 16, pp. 53-60, 2010.
 G. E. Atteia, A. A. Shaalan and K. F. A. Hussein. “ Wideband partially-covered bowtie antenna for ground-penetrating-radars,” Progress In Electromagnetics Research, Vol 71, pp. 211-226, 2007
 S. W. Cho and J. H. Lee, “Efficient implementation of the capon beamforming using the levenberg-marquardt scheme for two dimensional AOA estimation,” Progress In Electromagnetics Research, Vol 137, pp 19-34, 2013.
 J. Li and P. Stoica, Robust Adaptive Beamforming, Wiley-Interscience, New Jersey, 2006.
 S.D. Somasundaram, “Reduced dimension robust Capon beamforming for large aperture passive sonar arrays,” IET Radar Sonar Navig, Vol.5, pp. 707-715, 2011.
 G. Hajduch, J.M.Le Caillec and R. Garello, “Airborne high-resolution ISAR imaging of ship targets at sea,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 40, pp.378-384, 2004.
 M. Tello, C. Lopez-Martinez and J.J. Mallorqui, “A novel algorithm for ship detection in SAR imagery based on the wavelet transform,” IEEE Geoscience and Remote Sensing Letters, Vol.2, pp.201-205, 2005.
 H. Osman, S. Blostein and L. Gagnon, “Classification of ships in airborne SAR imagery using backpropagation neural networks,” SPIE Proc. Radar Processing, Technology, and Applications II, Vol.3161, pp126-136, 1997.
 M. Menon, “Automatic ship classification system for ISAR imagery,” SPIE In Proceedings on Applications and Science of Artificial Neural Networks Orlando, Vol. 2492, pp, 373-388, 1995.
 S. Musman, D. Kerr and C. Bachmann, “Automatic recognition of ISAR ship image,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 32, pp.1392-1402, 1996.
 S. C. Chan and K. C. Lee, “Angular-diversity target recognition by kernel scatter-difference based discriminate analysis on RCS,” International Journal of Applied Electromagnetics and Mechanics, Vol.42, pp. 409-420, 2013.
 K. C. Lee, J. S. Ou and C. W. Huang, “Angular-diversity radar recognition of ships by transformation based approaches --- including noise effects,” Progress In Electromagnetics Research-PIER, Vol. 72, pp.141-159, 2007.
 K. C. Lee and J. S. Ou, “Radar target recognition by using linear discriminant algorithm on angular-diversity RCS,” Journal of Electromagnetic Waves and Applications, Vol. 21, pp. 2033-2048, 2007.
 K. C. Lee, C. W. Huang and M. C. Fang, “Radar target recognition by projected features of frequency-diversity RCS,” Progress In Electromagnetic Research- PIER, Vol. 81, pp.121-133, 2008.
 C. W. Huang and K. C. Lee, “Application of ICA technique to PCA based radar target recognition,” Progress In Electromagnetic Research-PIER, Vol.105, pp157-170, 2010.
 C. W. Huang and K. C. Lee, “Frequency-diversity RCS based target recognition with ICA projection,” Journal of Electromagnetic Waves and Applications, Vol.24, pp.2547-2559, 2010.
 X. Li, G. Adamiuk, M. Janson, and T. Zwick, “Polarization system in ultra-wideband image Systems,” Proceedings of 2010 IEEE International Conference on Ultra-Wideband, 2010.
 K. C. Lee, “Polarization Effects on Bistatic Microwave Imaging of Perfectly Conducting Cylinders,” Master Thesis, National Taiwan University, Taipei, Taiwan, 1991.
 T. K. Moon and W. C. Stirling, Mathematical Methods and Algorithms for Signal Processing, Prentice Hall, 2000.
 R. O. Duda, P. E. Hart and D. G. Stork, Pattern Classification, 2nd edition, John Wiley, New York, 2001.
 S. Theodoridis and K. Koutroumbas, Pattern Recognition, 2nd edition, Academic Press, Boston, 2003.
 G. A. Ioannidis and D. E. Hammers, “Optimum antenna polarizations for target discrimination in clutter,” IEEE Transactions on Antennas and Propagation, Vol. 27, pp. 357-363, 1979.
 R. L. Haupt, Antenna Arrays, John Wiley & Sons, 2010.
 J. Wright, “A new model for sea clutter,” IEEE Transactions on Antennas and Propagation, Vol.16, pp. 217-223, 1968.
 G. V. Trunk and S. F. George, “Detection of targets in non-Gaussian sea clutter,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 6, pp. 620-628, 1970.
 H. W. Melief, H. Greidanus, P. Genderen and P. Hoogeboom, “Analysis of sea spikes in radar sea clutter data,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 44, pp. 985-993, 2006.
 N. W. Guinard and J. C. Daley, “An experimental study of a sea clutter model,” Proceedings of the IEEE, Vol. 58, pp. 543-550, 1970.
 R. A. Paulus, “Evaporation duct effects on sea clutter,” IEEE Transactions on Antennas and Propagation, Vol.38, pp. 1765-1771, 1990.