ABSTRACT
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.
