Single snapshot DOA estimation

Abstract. In array signal processing, direction of arrival (DOA) estimation has been studied for decades. Many algorithms have been proposed and their performance has been studied thoroughly. Yet, most of these works are focused on the asymptotic case of a large number of snapshots. In automotive radar applications like driver assistance systems, however, only a small number of snapshots of the radar sensor array or, in the worst case, a single snapshot is available for DOA estimation. In this paper, we investigate and compare different DOA estimators with respect to their single snapshot performance. The main focus is on the estimation accuracy and the angular resolution in multi-target scenarios including difficult situations like correlated targets and large target power differences. We will show that some algorithms lose their ability to resolve targets or do not work properly at all. Other sophisticated algorithms do not show a superior performance as expected. It turns out that the deterministic maximum likelihood estimator is a good choice under these hard conditions.

[1]  Robert Boorstyn,et al.  Single tone parameter estimation from discrete-time observations , 1974, IEEE Trans. Inf. Theory.

[2]  R. R. Boorstyn,et al.  Multiple tone parameter estimation from discrete-time observations , 1976, The Bell System Technical Journal.

[3]  Hamid Krim,et al.  Two Decades of Array Signal Processing , 1997 .

[4]  Xavier Mestre,et al.  The role of subspace swap in maximum likelihood estimation performance breakdown , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[5]  P. Stoica,et al.  Novel eigenanalysis method for direction estimation , 1990 .

[6]  Petre Stoica,et al.  Maximum likelihood methods for direction-of-arrival estimation , 1990, IEEE Trans. Acoust. Speech Signal Process..

[7]  Kristine L. Bell,et al.  Threshold Region Performance of Maximum Likelihood Direction of Arrival Estimators , 2007 .

[8]  Xavier Mestre,et al.  The role of subspace swap in music performance breakdown , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[9]  Jingmin Xin,et al.  Computationally efficient subspace-based method for direction-of-arrival estimation without eigendecomposition , 2004, IEEE Transactions on Signal Processing.

[10]  Björn E. Ottersten,et al.  Analysis of subspace fitting and ML techniques for parameter estimation from sensor array data , 1992, IEEE Trans. Signal Process..

[11]  A. G. Jaffer,et al.  Maximum likelihood direction finding of stochastic sources: a separable solution , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

[12]  Jian Li,et al.  Comparative study of IQML and MODE direction-of-arrival estimators , 1998, IEEE Trans. Signal Process..

[13]  Ronald K. Jurgen,et al.  Adaptive Cruise Control , 2006 .

[14]  T. Kailath,et al.  Estimation of Signal Parameters via Rotational Invariance Techniques - ESPRIT , 1986 .

[15]  A. L. Swindlehurst Fast updating of maximum likelihood direction of arrival estimates , 1991, [1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers.

[16]  Bin Yang,et al.  High-Resolution Angle Estimation for an Automotive FMCW Radar Sensor , 2011 .

[17]  Arthur Jay Barabell,et al.  Improving the resolution performance of eigenstructure-based direction-finding algorithms , 1983, ICASSP.

[18]  J. Litva,et al.  Radar Array Processing , 1993 .

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

[20]  Björn E. Ottersten,et al.  Detection and estimation in sensor arrays using weighted subspace fitting , 1991, IEEE Trans. Signal Process..

[21]  S. Unnikrishna Pillai,et al.  Forward/backward spatial smoothing techniques for coherent signal identification , 1989, IEEE Trans. Acoust. Speech Signal Process..

[22]  J. Capon High-resolution frequency-wavenumber spectrum analysis , 1969 .

[23]  Pedro Luis Dias Peres,et al.  Improving the MODEX algorithm for direction estimation , 2003, Signal Process..

[24]  A. Moffet Minimum-redundancy linear arrays , 1968 .

[25]  Petre Stoica,et al.  MODE with extra-roots (MODEX): a new DOA estimation algorithm with an improved threshold performance , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[26]  M. Viberg,et al.  Estimation accuracy of maximum likelihood direction finding using large arrays , 1991, [1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers.

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