volume | PIER Journals

Abstract

In this paper, our purpose is to develop methods that have high resolution and robustness in the presence of unknown source number, array error, snapshot deficient, and low SNR. The DOA (Direction-Of-Arrival) estimation with unknown source number methods referred as MUSIC-like and SSMUSIC-like methods have shown high resolution in the snapshot deficient and low SNR scenario. However, they need to take several times of fine search on the full space, which bring about high computational complexities. Thus, modified methods are proposed to reduce computational complexities and improve performances further. In the modified methods, we priori use conventional beamforming to get the rough distribution of signals' angle, which helps to reduce computational complexity and connect the technique of projection pretransformation. Then through projection pretransformation, original methods are further simplified and improved. As demonstrated in computer simulations, the modified DOA estimation with unknown source number methods shows not only higher resolution in the snapshot deficient and lower SNR scenario, but also more robustness against array errors. Although the proposed methods cannot replace the array calibration completely, they reduce the requirement of calibration accuracy. Combined with these advantages, it has been shown that the new methods are more suitable in engineering.

1. Bencheikh, M. L. and Y. Wang, "Combined esprit-rootmusic for DOA-DOD estimation in polarimetric bistatic MIMO radar," Progress In Electromagnetics Research Letters, Vol. 22, 109-117, 2011. Google Scholar

2. Yang, P., 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, 201-216, 2010.
doi:10.2528/PIER10011904 Google Scholar

3. Liang, G. L., K. Zhang, F. Jin, et al. "Modified MVDR algorithm for DOA estimation using acoustic vector hydrophone," 2011 IEEE International Conference on Computer Science and Automation Engineering, 327-330, 2011.
doi:10.1109/CSAE.2011.5952480 Google Scholar

4. Schmidt, R. O., "Multiple emitter location and signal parameter estimation," IEEE Trans. Ant. Propag., Vol. 34, No. 2, 276-280, 1986.
doi:10.1109/TAP.1986.1143830 Google Scholar

5. McCloud, M. L. and L. L. Scharf, "A subspace identification algorithm for high-resolution DOA estimation," IEEE Trans. Ant. Propag., Vol. 50, No. 10, 1382-1390, 2002.
doi:10.1109/TAP.2002.805244 Google Scholar

6. Mestre, X. and M. A. Lagunas, "Modified subsoace algorithms for DOA estimation with large arrays," IEEE Trans. Signal Process., Vol. 56, No. 2, 598-614, 2008.
doi:10.1109/TSP.2007.907884 Google Scholar

7. Porat, B. and B. Friedlander, "Analysis of the asymptotic relative efficiency of MUSIC algorithm," IEEE Trans on Acoust., Speech, Signal Process., Vol. 36, No. 4, 532-544, 1988.
doi:10.1109/29.1557 Google Scholar

8. Nadakudit, R. R. and A. Edelman, "Sample eigenvalue based detection of high-dimensional signals in white noise using relatively few samples," IEEE Trans. Signal Process., Vol. 56, No. 7, 2625-2638, 2008.
doi:10.1109/TSP.2008.917356 Google Scholar

9. Nadler, B., "Nonparametric detection of signals by information theoretic criteria: Performance analysis and an improved estimator," IEEE Trans. Signal Process., Vol. 58, No. 5, 2746-2756, 2010.
doi:10.1109/TSP.2010.2042481 Google Scholar

10. Haddadi, F., M. M. Mohamaddi, M. M. Nayebi, et al. "Statistical performance analysis of MDL source enumeration in array processing," IEEE Trans. Signal Process., Vol. 58, No. 1, 452-457, 2010.
doi:10.1109/TSP.2009.2028207 Google Scholar

11. Chen, P., T.-J. Wu, and J. Yang, "A comparative study of model selection criteria for the number of signals," IET Radar, Sonar and Navigation, Vol. 2, No. 3, 180-188, 2008.
doi:10.1049/iet-rsn:20070102 Google Scholar

12. Radich, B. M. and K. M. Buckley, "The effect of source number underestimation on MUSIC location estimates," IEEE Trans. Signal Process., Vol. 42, No. 1, 233-236, 1994.
doi:10.1109/78.258148 Google Scholar

13. Manikas, A. N. and L. R. Turnor, "Adaptive signal parameter estimation and classification technique," IEE Proceedings F, Vol. 138, No. 3, 267-277, 1991. Google Scholar

14. Qi, C. Y., Y. S. Zhang, Y. Han, et al. "An algorithm on high resolution DOA estimation with unknown number of signal sources," 4th International Conference on Microwave and Millimeter Wave Technology, ICMMT, 227-230, 2004. Google Scholar

15. Stavropoulos, K. V. and A. Manikas, "Array calibration in the presence of unknown sensor characteristics and mutual coupling," EUSIPCO Proceedings, Vol. 3, 1417-1420, 2000. Google Scholar

16. Liu, A., G. Liao, C. Zeng, et al. "An eigenstructure method for estimating DOA and sensor gain-phase errors," IEEE Trans. Signal Process., Vol. 59, No. 12, 5944-5956, 2011.
doi:10.1109/TSP.2011.2165064 Google Scholar

17. Ng, B. P., J. P Lie, M. H. Er, et al. "A practical simple geometry and gain/phase calibration technique for antenna array processing," IEEE Trans. Signal Process., Vol. 58, No. 3, 1668-1676, 2010.
doi:10.1109/TSP.2009.2037074 Google Scholar

18. Blunt, S. D., C. Tszping, and K. Gerlach, "Robust DOA estimation: The reiterative superresolution (RISR) algorithm," IEEE Trans. Aerosp. Electron. Syst., Vol. 47, No. 1, 332-346, 2011.
doi:10.1109/TAES.2011.5705679 Google Scholar

19. Stoica, P., Z. Wang, and J. Li, "Extended derivation of MUSIC in presence of steering vector errors," IEEE Trans. Signal Process., Vol. 53, No. 3, 1209-1211, 2005.
doi:10.1109/TSP.2004.842201 Google Scholar

20. Zhou, Q.-C., H. Gao, and F. Wang, "A high resolution DOA estimating method without estimating the number of sources," Progress In Electromagnetics Research C, Vol. 25, 233-247, 2012.
doi:10.2528/PIERC11102607 Google Scholar

21. Lee, H. B. and M. S. Wengrovitz, "Resolution threshold of beamspace MUSIC for two closely spaced emitters," IEEE Trans on Acoust., Speech, Signal Process., Vol. 38, No. 9, 1545-1559, 1990.
doi:10.1109/29.60074 Google Scholar

22. Luo, Y. J., T. Zhang, and S. H. Zhang, "A novel algorithm for adaptive beamforming based on projection transformation," 2001 Proceedings of CIE International Conference on Radar, 552-556, Beijing, 2001.

23. Shahi, S. N., M. Emadi, and K. H. Sadeghi, "High resolution DOA estimation in fully coherent environments," Progress In Electromagnetics Research C, Vol. 5, 135-148, 2008. Google Scholar

Dr. Qing-Chen Zhou

Prof. Huotao Gao

Dr. Fan Wang

Dr. Jie Shi