2014-05-23
Space-Time Matrix Method for Mixed Near-Field and Far-Field Sources Localization
By
Progress In Electromagnetics Research M, Vol. 36, 131-137, 2014
Abstract
Mixed near-field and far-field sources localization problem has received significant attention recently in some practical applications, such as speaker localization using microphone arrays and guidance systems, etc. This paper presents a novel space-time matrix method to localize mixed near-field and far-field sources. Using the proposed method, both the direction-of-arrival (DOA) and range of a source can be estimated by the same eigen-pair of a defined spacetime matrix. Therefore, the pairing of the estimated angles and ranges is automatically determined. Compared with the previous work, the presented method offers a number of advantages over other recently proposed algorithms. For example, it can avoid not only parameters matching problem but also aperture loss problem. It has lower computational complexity since the proposed method does not require the high-order statistics or any parameter search. Simulation results show the performance of the proposed algorithm.
Citation
Ruiyan Du, Fulai Liu, and Jinkuan Wang, "Space-Time Matrix Method for Mixed Near-Field and Far-Field Sources Localization," Progress In Electromagnetics Research M, Vol. 36, 131-137, 2014.
doi:10.2528/PIERM14040203
References

1. Schimidt, R. O., "Multiple emitter location and signal parameter estimation," IEEE Transactions on Antennas and Propagation, Vol. 34, 276-280, 1986.
doi:10.1109/TAP.1986.1143830        Google Scholar

2. Roy, R. and T. Kailath, "ESPRIT-estimation of signal parameters via rotational invariance techniques," IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 37, No. 7, 984-995, 1989.
doi:10.1109/29.32276        Google Scholar

3. Liu, F. L., J. K. Wang, C. Y. Sun, and R. Y. Du, "Spatial differencing method for DOA estimation under the coexistence of both uncorrelated and coherent signals," IEEE Transactions on Antennas and Propagation, Vol. 60, No. 4, 2052-2062, 2012.
doi:10.1109/TAP.2012.2186216        Google Scholar

4. Huang, Y. D. and M. Barkat, "Near-field multiple sources localization by passive sensor array," IEEE Transactions on Antennas and Propagation, Vol. 39, 968-975, 1991.
doi:10.1109/8.86917        Google Scholar

5. Grosicki, E., K. Abed-Meraim, and Y. Hua, "A weighted linear prediction method for near-field source localization," IEEE Transactions on Signal Processing, Vol. 53, No. 10, 3651-3660, 2005.
doi:10.1109/TSP.2005.855100        Google Scholar

6. Zhi, W. and M. Y. W. Chia, "Near-field source localization via symmetric subarrays," IEEE Transactions on Signal Processing Letters, Vol. 14, No. 6, 409-412, 2007.
doi:10.1109/LSP.2006.888390        Google Scholar

7. Wu, Y., H. C. So, and J. Li, "Passive localization of near-field sources with a polarization sensitive array," IEEE Transactions on Antennas and Propagation, Vol. 55, No. 8, 2402-2408, 2007.
doi:10.1109/TAP.2007.901912        Google Scholar

8. Liang, J. and D. Liu, "Passive localization of mixed near-field and far-field sources using two-stage MUSIC algorithm," IEEE Transactions on Signal Processing, Vol. 58, No. 1, 108-120, 2010.
doi:10.1109/TSP.2009.2029723        Google Scholar

9. He, J., N. S. Swamy, and M. O. Ahmad, "Efficient application of MUSIC algorithm under the coexistence of far-field and near-field sources," IEEE Transactions on Signal Processing, Vol. 60, No. 4, 2066-2070, 2012.
doi:10.1109/TSP.2011.2180902        Google Scholar

10. Jiang, J. J., F. J. Duan, J. Chen, et al. "Mixed near-field and far-field sources localization using the uniform linear sensor array," IEEE Sensors Joural, Vol. 13, No. 8, 3136-3143, 2013.
doi:10.1109/JSEN.2013.2257735        Google Scholar

11. Chen, L., X. Z. Yan, and G. H. Liu, "An improved method for passive localization of coexistent far-field and near-field sources," International Congress on Image and Signal Processing, Vol. 3, 1417-1421, 2013.        Google Scholar

12. Wen, F. X. and W. P. Tay, "Localization for mixed near-field and far-field sources using data supported optimization," International Conference on Information Fusion, 402-407, 2012.        Google Scholar

13. Wang, B., J. J. Liu, and X. Y. Sun, "Mixed sources localization based on sparse signal reconstruction," IEEE Signal Processing Letters, Vol. 19, No. 8, 487-490, 2012.
doi:10.1109/LSP.2012.2204248        Google Scholar

14. Liu, G. H. and X. Y. Sun, "Two-stage matrix differencing algorithm for mixed far-field and near- ¯eld sources classi¯cation and localization," IEEE Sensor Journal, Vol. 44, No. 6, 1-8, 2014.
doi:10.1109/JSEN.2014.2336240        Google Scholar

15. Huang, Q. H. and T. Song, "DOA estimation of mixed near-field and far-field sources using spherical array," International Conference on Signal Processing, Vol. 1, 382-385, 2012.        Google Scholar

16. Liang, J. and Q. Y. Yin, "Space-time DOA matrix method," Acta Electronica Sinica, Vol. 28, No. 6, 8-12, 2000.        Google Scholar

17. Liu, F. L., J. K.Wang, R. Y. Du, and Y. Ge, "Space-time matrix method for 2-D direction-of-arrival estimation," Signal Processing, Vol. 87, No. 1, 101-106, 2007.
doi:10.1016/j.sigpro.2006.05.001        Google Scholar