Over-the-horizon Radar potential signal parameter estimation accuracy in harsh sensing environments

Modern high frequency (HF) over-the-horizon Radar´s (OTHR´s) that perform parametric sensing over a huge coverage of several million square kilometers operate in harsh sensing environments consisting of strong interference and clutter. The highly dynamic nature of such an environment governed by harsh ionosphere propagation conditions and a highly occupied HF spectrum mandate the application of adaptive signal processing architectures enabled by the emerging direct digital receiver technology. In this paper, we investigate the potential accuracy of OTHR signal parameter estimation, in particular, direction-of-arrival (DOA) estimation of target returns and/or HF signals masked by both interference and background noise. Recently, the concept of two-dimensional (2D) receive arrays has been introduced for skywave OTHR, along with a more accurate model of the background noise spatial distribution. In this prior work it was shown that with 2D spatial sampling, the external background noise covariance is no longer white. In this paper we introduce the Cramer-Rao bound for angle estimates using an arbitrary array geometry and arbitrary known colored noise spatial covariance. We will show through numerical simulation that improved DOA performance is possible with 2D array geometries that provide both improved signal-to-external noise ratio and more highly curved array manifolds. The particular array geometries discussed exploit the colored noise spatial covariance.