In low grazing angle scenario, target detection performance is seriously deteriorated due to multipath effect. This paper deals with moving target detection in low grazing angle with orthogonal frequency division multiplexing (OFDM) multi-input multi-output (MIMO) radar. We show that the detection performance can be improved through utilizing the multipath effect. Realistic physical and statistical effects such as refraction of the lower atmosphere and the Earth's curvature are incorporated into the multipath propagation model. Then, we derive a generalized likelihood ratio test (GLRT) detector by taking advantage of the frequency diversity of OFDM and MIMO configuration. Based on the fact that the target responses resonate at different frequencies and statistical characteristics of the test, we propose an algorithm which adaptively allocates the transmitted energy to improve the detection performance. The effectiveness of the GLRT detector as well as the adaptive design method is demonstrated via numerical examples.
2. Lo, T. and J. Litva, "Use of a highly deterministic multipath signal model in low-angle tracking," IEE Proc. F - Radar and Signal Processing, Vol. 138, No. 2, 163-171, 1991. doi:10.1049/ip-f-2.1991.0022
3. Chakraborty, B., et al., "Multipath exploitation with adaptive waveform design for tracking in urban terrain," Proceedings of the IEEE Acoustics Speech and Signal Processing (ICASSP), 3894-3897, Dallas, TX, United States, 2010.
4. Silon, S. L. and B. D. Carlson, "Radar detection in multipath," IEE Proc. Radar, Sonar and Navigation, Vol. 146, No. 1, 45-54, 1999. doi:10.1049/ip-rsn:19990264
5. Zhao, J. H. and J. Y. Yang, "Frequency diversity to low-angle detecting using a highly deterministic multipath signal model," Proc. of 6th CIE Int. on Radar, 1-5, Shanghai, China, 2006.
6. Ge, P., L. J. Kong, and J. Y. Yang, "Moving target detection with frequency diversity under multipath scenario," Proceedings of 2014 IEEE International Conference on Communication Problem-Solving (ICCP), 197-201, Beijing, China, 2014.
7. Hayvaci, H. T., A. de Maio, and Erricolo, "Improved detection probability of a radar target in the presence of multipath with prior knowledge of the environment," IET Radar, Sonar & Navigation, Vol. 7, No. 1, 36-46, 2013. doi:10.1049/iet-rsn.2012.0081
8. Hayvaci, H. T. and D. Erricolo, "Improved radar target time-delay estimation with multipath exploitation," Proceedings of the 2013 International Conference on Electromagnetics in Advanced Applications (ICEAA), 1232-1235, Turin, Italy, 2013.
9. Krolik, J. L., J. Farrell, and A. Steinhardt, "Exploiting multipath propagation for GMTI in urban environments," Proceedings of 2006 IEEE Radar Conference, 65-68, Verona, NY, United States, 2006.
10. Paul, E. B. and D. P. Finch, "Low-angle target detection with interference in a multipath environment," Proceedings of 2013 International Conference on Radar, 440-445, Adelaide, SA, Australia, 2013.
11. Sen, S., M. Hurtado, and A. Nehorai, "Adaptive OFDM radar for detecting a moving target in urban scenarios," Proceedings of 2009 International Waveform Diversity and Design (WDD) Conference, 268-272, Orlando, USA, 2009.
12. Sen, S. and A. Nehorai, "Adaptive OFDM radar for target detection in multipath scenarios," IEEE Trans. on Signal Processing, Vol. 59, No. 1, 78-90, 2011. doi:10.1109/TSP.2010.2086448
13. Sen, S., G. Tang, and A. Nehorai, "Multi-objective optimization of OFDM radar waveform for target detection," IEEE Trans. on Signal Processing, Vol. 59, No. 2, 639-652, 2011. doi:10.1109/TSP.2010.2089628
14. Fisher, E., et al., "MIMO radar: An idea whose time has come," Proceedings of the 2004 IEEE Radar Conference, 71-78, Philadelphia, Pennsylvania, 2004.
15. Fishler, E., A. Haimovich, and R. Blum, "Spatial diversity in radars-models and detection performance," IEEE Trans. on Signal Processing, Vol. 54, No. 3, 823-838, 2006. doi:10.1109/TSP.2005.862813
16. Jin, Y., J. M. F. Moura, and N. O. Donoughue, "Time reversal in multiple-input multiple-output radar," IEEE Journal of Selected Topics in Signal Processing, Vol. 4, No. 1, 210-225, 2010. doi:10.1109/JSTSP.2009.2038983
17. Mecca, V. F., D. Ramakrishnan, and J. L. Krolik, "MIMO radar space-time adaptive processing for multipath clutter mitigation," Proceedings of 4th IEEE Sensor Array and Multichannel Signal Processing Workshop, 249-253, Waltham, MA, United States, 2006.
18. Tohidur Rahman, A. K. M., S. M. M. Hossain Mahmud, and T. K. Biswas, "Target detection performance of coherent MIMO radar using space time adaptive processing," Proceedings of 3rd International Conference on Informatics, Electronics & Vision (ICIEV), 1-5, Dhaka, Bangladesh, 2014.
19. Ding, J., H. W. Chen, H. Wang, X. Li, and Z. Zhuang, "Low-grazing angle target detection and system configuration of MIMO radar," Progress In Electromagnetics Research B, Vol. 48, 23-42, 2013. doi:10.2528/PIERB12120201
20. Ding, J. C., et al., "Low-grazing angle detection in compound-Gaussian clutter with hybrid MIMO radar," International Journal of Antennas and Propagation, Vol. 2013, Article ID374342, 2013.
21. Bar-Shalom, Y., A. Kumar, W. Blair, and G. Groves, "Tracking low elevation targets in the presence of multipath propagation," IEEE Trans. on Aerospace and Electronic Systems, Vol. 30, No. 3, 973-979, 1994. doi:10.1109/7.303775
22. Long, M. W., Radar Reflectivity of Land Sea, 3rd Ed., Artech House, Apr. 2001.
23. Jian, L. and P. Stoica, "MIMO radar with colocated antennas," IEEE Trans. on Signal Processing Magazine, Vol. 24, No. 5, 106-114, 2007. doi:10.1109/MSP.2007.904812
24. Michael, S. D., A. S. Gregory, and A. Lanterman, "Coherent MIMO radar: The phased array and orthogonal waveforms," IEEE Trans. on Aerospace and Electronic Systems Magazine, Vol. 29, No. 8, 76-91, 2014. doi:10.1109/MAES.2014.130148
25. Kay, S. M., Fundamentals of Statistical Signal Processing: Detection Theory, Prentice Hall PTR, Upper Saddle River, NJ, 1998.
26. Andersen, H. H., M. Højbjerre, D. Sørensen, and P. S. Eriksen, Linear and Graphical Models for Multivariate Complex Normal Distribution, Springer-Verlag, Inc., New York, NY, 1995.
27. Xu, L., P. Stoica, and J. Li, "A block-diagonal growth curve model," Digital Signal Process., Vol. 16, No. 6, 902-912, 2006. doi:10.1016/j.dsp.2006.05.005
28. Xu, L., P. Stoica, and J. Li, "A diagonal growth curve model and some signal processing applications," IEEE Trans. on Signal Processing, Vol. 54, No. 9, 3363-3371, 2006. doi:10.1109/TSP.2006.879296
29. Dogandzic, A. and A. Nehorai, "Generalized multivariate analysis of variance: A unified framework for signal processing in correlated noise," IEEE Trans. on Signal Processing Magazine, Vol. 20, 39-54, 2003. doi:10.1109/MSP.2003.1236771
30. Kelly, E. J. and K. M. Forsythe, "Adaptive detection and parameter estimation for multidimensional signal models,", Tech. Rep. 848, Lincoln Laboratory, MIT, Lexington, MA, Apr. 1989.
31. Fujikoshi, Y., "Asymptotic expansions of the non-null distributions of three statistics in GMANOVA," Annals of the Institute of Statistical Mathematics, Vol. 26, No. 1, 289-297, 1974. doi:10.1007/BF02479824
32. Anderson, T. W., An Introduction to Multivariate Statistical Analysis, 2nd Ed., Wiley, Hoboken, NJ, Sep. 2003.
33. Bickel, P. and K. Doksum, Mathematical Statistics: Basic Ideas and Selected Topics, 2nd Ed., Prentice-Hall, Upper Saddle River, NJ, 2000.
34. Akcakaya, M. and A. Nehorai, "Adaptive MIMO radar design and detection in compound-Gaussian clutter," IEEE Trans. on Aerospace and Electronic Systems, Vol. 47, No. 3, 2200-2207, 2011. doi:10.1109/TAES.2011.5937292