Uniform planar array broadband angle of arrival estimation from polynomial steering matrix

In this paper, we propose a scalable broadband angle-of-arrival (AoA) estimation approach based on an estimated uniform planar array (UPA) polynomial matrix. The proposed method employs least-squares (LS) Khatri-Rao factorization in discrete Fourier transform (DFT) frequency bins to compute samples of the space-time covariance matrix in both azimuth and elevation directions. This approach eliminates the need for computing a polynomial singular value decomposition (PSVD), thereby enhancing scalability with respect to the number of sources and array elements. The proposed method’s performance is showcased in a simulation where a polynomial steering matrix for three sources is deliberately perturbed with varying degrees of estimation error to simulate different signal to noise ratio (SNR) scenarios. With azimuth and elevation angles determined independently, these are paired using an economical angle pairing strategy specifically designed for broadband scenarios.