Adaptive Beamforming and Recursive DOA Estimation Using Frequency-Invariant Uniform Concentric Spherical Arrays

This paper proposes recursive adaptive beamforming and broadband 2D direction-of-arrival (DOA) estimation algorithms for uniform concentric spherical arrays (UCSAs) having nearly frequency-invariant (FI) characteristics. The basic principle of the FI-UCSA is to transform the received signals to the phase mode and remove the frequency dependency of individual phase modes through a digital beamforming network. Hence, the far-field pattern of the array is determined by a set of weights. Thanks to the FI characteristic, traditional narrowband adaptive beamforming algorithms such as minimum variance beamforming and the generalized sidelobe canceller method can be applied to the FI-UCSA. Simulation results show that the proposed adaptive FI-UCSA beamformer achieves a lower steady-state error and converges faster than the conventional tapped-delay line approach while requiring fewer adaptive coefficients. A new broadband 2-D DOA estimation algorithm using ESPRIT techniques for FI-UCSA is proposed to recursively estimate the DOAs of the moving targets. Simulation results show that the proposed DOA estimation algorithm achieves a satisfactory performance for slowly varying sources at low arithmetic complexity.