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.
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.
3. Liang, G. L., 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.
4. Schmidt, R. O., "Multiple emitter location and signal parameter estimation," IEEE Trans. Ant. Propag., Vol. 34, No. 2, 276-280, 1986.
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.
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.
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.
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.
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.
10. Haddadi, F., et al., "Statistical performance analysis of MDL source enumeration in array processing," IEEE Trans. Signal Process., Vol. 58, No. 1, 452-457, 2010.
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.
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.
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.
14. Qi, C. Y., 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.
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.
16. Liu, A., et al., "An eigenstructure method for estimating DOA and sensor gain-phase errors," IEEE Trans. Signal Process., Vol. 59, No. 12, 5944-5956, 2011.
17. Ng, B. P., 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.
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.
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.
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.
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.
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.