This paper addresses the problem of direction-of-arrival (DOA) estimation of multiple wideband coherent chirp signals, and a new method is proposed. The new method is based on signal component analysis of the array output covariance, instead of the complicated time-frequency analysis used in previous literatures, and thus is more compact and effectively avoids possible signal energy loss during the hyper-processes. Moreover, the a priori information of signal number is no longer a necessity for DOA estimation in the new method. Simulation results demonstrate the performance superiority of the new method over previous ones.
References
[1]
Ma, N.; Goh, J.T. Ambiguity-function-based techniques to estimate DOA of broadband chirp signals. IEEE Trans. Signal Proc. 2006, 54, 1826–1839.
[2]
Wang, G.; Xia, X.G. Iterative algorithm for direction of arrival estimation with wideband chirp signals. IEE Proc. Radar Sonar Navig. 2000, 147, 233–238.
[3]
Gershman, A.B.; Amin, M.G. Wideband direction-of-arrival estimation of multiple chirp signals using spatial time-frequency distributions. IEEE Signal Proc. Lett. 2000, 7, 152–155.
[4]
Gershman, A.B.; Pesavento, M.; Amin, M.G. Estimating parameters of multiple wideband polynomial-phase sources in sensor arrays. IEEE Trans. Signal Proc. 2001, 49, 2924–2934.
[5]
Cowell, D.M.J.; Freear, S. Separation of overlapping linear frequency modulated (LFM) signals using the fractional Fourier transform. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 2010, 57, 2324–2333.
[6]
Malioutov, D.; Cetin, M.; Willsky, A.S. A sparse signal reconstruction perspective for source localization with sensor arrays. IEEE Trans. Signal Proc. 2005, 53, 3010–3022.
[7]
Tropp, J.A.; Wright, S.J. Computational methods for sparse solution of linear inverse problems. Proc. IEEE 2010, 98, 948–958.
[8]
Fuchs, J.J. Multipath time-delay detection and estimation. IEEE Trans. Signal Proc. 1999, 47, 237–243.
[9]
Chen, J.; Huo, X. Theoretical results on sparse representations of multiple-measurement vectors. IEEE Trans. Signal Proc. 2006, 54, 4634–4643.
[10]
Donoho, D.L.; Mallat, S.; Sachs, R.; Samuelides, Y. Locally stationary covariance and signal estimation with macrotiles. IEEE Trans. Signal Proc. 2003, 51, 614–627.
[11]
Stoica, P.; Selen, Y. Model-order selection: A review of information criterion rules. IEEE Signal Proc. Mag. 2004, 21, 36–47.
[12]
Sturm, J.F. Using SeDuMi 1.02, a Matlab Toolbox for Optimization over Symmetric Cones. Optim. Methods softw. 1999, 11, 625–653.
[13]
Wang, H.; Kaveh, M. Coherent signal-subspace processing for the detection and estimation of angles of arrival of multiple wide-band sources. IEEE Trans. Acoust. Speech Signal Proc. 1985, 33, 823–831.
[14]
Sustin, C.D.; Moses, R.L.; Ash, J.N.; Ertin, E. On the relation between sparse reconstruction and parameter estimation with model order selection. IEEE J. Sel. Top. Signal Proc. 2010, 4, 560–570.
