Uniform Concentric Circular Arrays With Frequency-Invariant Characteristics—Theory, Design, Adaptive Beamforming and DOA Estimation

This paper proposes a new digital beamformer for uniform concentric circular arrays (UCCAs) having nearly frequency-invariant (FI) characteristics. The basic principle is to transform the received signals to the phase mode and remove the frequency dependency of the individual phase mode through the use of a digital beamforming or compensation network. As a result, the far-field pattern of the array, which is governed by a set of variable beamformer weights, is electronically steerable, and it is approximately invariant over a wider range of frequencies than conventional uniform circular arrays (UCAs). This also makes it possible to design the compensation network and the beamformer weights separately. The design of the compensation network is formulated as a second order cone programming (SOCP) problem and is solved optimally for minimax criterion. By employing the beamspace approach using the outputs of a set of fixed UCCA frequency-invariant beamformers (FIBs), a new beamspace MUSIC algorithm is proposed for estimating the direction-of-arrivals (DOAs) of broadband sources. Since the beampatterns of the UCCA-FIB is approximately invariant with frequency and is governed by a small set of weights, a very efficient adaptive beamformer using the minimum variance beamforming (MVB) approach can be developed. Simulation results using broadband Gaussian and multisinusoidal inputs show that the proposed adaptive UCCA-FIB is numerically better conditioned than the conventional broadband tapped-delay-line-based adaptive beamformers, due to the FI property and significantly fewer numbers of adaptive parameters. Consequently, a higher output signal-to-inference-plus-noise ratio over the conventional tapped-delay-line approach is observed. The usefulness of the proposed UCCA-FIB in broadband DOA estimation is also verified by computer simulation