A unified instrumental variable approach to direction finding in colored noise fields
Book chapter, 2009

Most parametric methods for direction-of-arrival (DOA) estimation require knowledge of the spatial (sensor-to-sensor) color of the background noise. If this information is unavailable, a serious degradation of the quality of the estimates can result, particularly at low signal-to-noise ratio (SNR) [1-3]. A number of methods have been proposed over the recent years to alleviate the sensitivity to the noise color. If a parametric model of the covariance matrix of the noise is available, the parameters of the noise model can be estimated along with those of the interesting signals [4-7]. Such an approach is expected to performwell in situations where the noise can be accurately modeled with relatively few parameters. An alternative approach, which does not require a precise model of the noise, is based on the principle of instrumental variables (IVs). See Söderström and Stoica [8,9] for thorough treatments of IV methods (IVMs) in the context of identification of linear time-invariant dynamical systems. A brief introduction is given in the appendix. Computationally simple IVMs for array signal processing appeared in [10,11]. These methods perform poorly in difficult scenarios involving closely spaced DOAs and correlated signals.

Author

Petre Stoica

Uppsala University

Mats Viberg

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

M. Wong

McMaster University

Q. Wu

CELWAVE

The Digital Signal Processing Handbook

Subject Categories

Probability Theory and Statistics

Control Engineering

Signal Processing

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4/9/2019 3