A novel covariation based noncircular sources direction finding method under impulsive noise environments

• We model the impulsive noises in array signal processing as complex SαS processes.
• We examine the non-circularity of the BPSK signals.
• Covariation measures the similarity between two SαS random variables.
• We formulate the extended covariation based matrix for the array sensor outputs.
• We apply the extended covariation based matrix with MUSIC to obtain DOA estimates.

We extend the bearing estimation method for noncircular signals to the impulsive noise scenario which can be modeled as a complex symmetric alpha-stable (SαS) process. We define the extended covariation based matrix of the sensor outputs and show that it can be applied with subspace techniques to extract the bearing information from noncircular sources. Comprehensive simulations demonstrate that the proposed direction finding algorithm outperforms the traditional NC-MUSIC algorithm in the presence of a wide range of impulsive noise environments.