Publications in Scientific Journals:

C. Mecklenbräuker, P. Gerstoft, E. Zöchmann, H. Groll:
"Robust estimation of DOA from array data at low SNR";
Signal Processing, 166 (2020), 107262; 1 - 9.

English abstract:
We consider direction of arrival (DOA) estimation for a plane wave hidden in additive circularly symmetric noise at low signal to noise ratio.
Starting point is the maximum-likelihood DOA estimator for a deterministic signal carried by a plane wave in noise with a Laplace-like distribution. This leads to the formulation of a DOA estimator based on the Least Absolute Deviation (LAD) criterion.
The phase-only beamformer (which ignores the magnitude of the observed array data) turns out to be an approximation to the LAD-based DOA estimator. We show that the phase-only beamformer is a well performing DOA estimator at low SNR for additive homoscedastic and heteroscedastic Gaussian noise, as well as Laplace-like noise.
We compare the root mean squared error of several different DOA estimators versus SNR in a simulation study: the conventional beamformer, the phase-only beamformer, the weighted phase-only beamformer, and sparse Bayesian learning (SBL3).
The simulations indicate that the phase-only DOA estimator and SBL3 have desirable properties when the additive noise deviates from the Laplace-like assumption.
The qualitative robustness of these DOA estimators is investigated by comparing the empirical influence functions.
Finally, the estimators are applied to passive sonar measurements acquired with a horizontal array in the Baltic Sea.

Array processing, DOA Estimation, Least absolute deviation, LAD, Laplace-like noise, Heteroscedastic noise, Phase-only processing

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Created from the Publication Database of the Vienna University of Technology.