Lorentzian model of spatially coherent noise field in narrowband direction finding

When studying the radiation coming from far field sources using an array of sensors, besides the internal thermal noise, the received wave field is always perturbed by an external noise field, which can be temporally and spatially coherent to some degree, temporally incoherent and spatially coherent, spatially incoherent and temporally correlated or finally, the incoherence in both domains. Thus treating the received data needs to consider the nature of perturbing field in order to make accurate measurements such as powers of punctual sources, theirs locations and the types of waveforms which can be deterministic or random. In this paper, we study the type of temporally white and spatially coherent noise field; we propose a new spatial coherence function using Lorentz function. After briefly describing some existing models, we numerically study the effect of spatial coherence length on resolving the angular locations of closely radiating sources using spectral techniques which are divided into beam forming and subspace based methods, this study is made comparatively to temporally and spatially white noise with the same power as the proposed one in order to make a precise comparisons.

[1]  R. J. Talham Noise correlation functions for anisotropic noise fields , 1963 .

[2]  Chong-Yung Chi,et al.  DOA estimation of quasi-stationary signals via Khatri-Rao subspace , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[3]  Christoph F. Mecklenbräuker,et al.  Direction finding with imperfect wavefront coherence: a matrix fitting approach using genetic algorithm , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[4]  Thomas Kailath,et al.  On spatial smoothing for direction-of-arrival estimation of coherent signals , 1985, IEEE Trans. Acoust. Speech Signal Process..

[5]  J. Nossek,et al.  Blind noise and channel estimation , 2000, Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing (Cat. No.00TH8496).

[6]  Fu Li,et al.  Performance degradation of DOA estimators due to unknown noise fields , 1992, IEEE Trans. Signal Process..

[7]  Kishore D. Kulat,et al.  Robust Algorithms for DOA Estimation and Adaptive Beamforming for Smart Antenna Application , 2009, 2009 Second International Conference on Emerging Trends in Engineering & Technology.

[8]  Yong-Liang Wang,et al.  Estimation DOAs of the Coherent Sources Based on Toeplitz Decorrelation , 2008, 2008 Congress on Image and Signal Processing.

[9]  S. Bourennane,et al.  High Resolution Methods Based On Rank Revealing Triangular Factorizations , 2004 .

[10]  A.. Kisliansky,et al.  Direction of Arrival Estimation in the Presence of Noise Coupling in Antenna Arrays , 2007, IEEE Transactions on Antennas and Propagation.

[11]  J. S. Bird,et al.  Speech enhancement for mobile telephony , 1990 .

[12]  Said Safi,et al.  DOA estimation with fourth order propagator , 2014, 2014 International Conference on Multimedia Computing and Systems (ICMCS).

[13]  M. Viberg,et al.  Two decades of array signal processing research: the parametric approach , 1996, IEEE Signal Process. Mag..

[14]  Shujing Su,et al.  New method of DOA estimation for coherent sources under unknown noise field , 2009, 2009 9th International Conference on Electronic Measurement & Instruments.

[15]  Wei Cui,et al.  Vector Field Smoothing for DOA Estimation of Coherent Underwater Acoustic Signals in Presence of a Reflecting Boundary , 2007, IEEE Sensors Journal.

[16]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .

[17]  F. X. Kneizys,et al.  Convolution algorithm for the Lorentz function. , 1979, Applied optics.

[18]  M. Frikel,et al.  Comparative Study between Several Direction of Arrival Estimation Methods , 2014 .

[19]  M. Frikel,et al.  Lorentzian Operator for Angular Source Localization with Large Array , 2015 .