Design of time-domain modal beamformer for broadband spherical microphone arrays

ABSTRACT An approach to real-valued time-domain implementation of modal beamformer for spherical microphone arrays is proposed. The advantage of the time-domain implementation is that we can update the beamformer when each new snapshot arrives. Our technique is based on a modified filter-and-sum spherical harmonics domain (SHD) beamforming structure. The time series received at the microphones are converted into SHD data using spherical Fourier transform. The SHD data input to the steering unit and then feed a bank of finite impulse response (FIR) filters. The filter outputs are summed to produce the beamformer output time series. The FIR filters tap weights are optimally designed by making a compromise among multiple conflicting array performance measures such as directivity, mainlobe spatial response variation (MSRV), sidelobe level, and robustness. The design problem is formulated as a multiply constrained problem which is solved using second-order cone programming (SOCP). Results of simulations show good performance of the proposed time-domain SHD beamformer design approach

Broadband Beamspace DOA Estimation: Frequency-Domain and Time-Domain Processing Approaches

<p/> <p>Frequency-domain and time-domain processing approaches to direction-of-arrival (DOA) estimation for multiple broadband far field signals using beamspace preprocessing structures are proposed. The technique is based on constant mainlobe response beamforming. A set of frequency-domain and time-domain beamformers with constant (frequency independent) mainlobe response and controlled sidelobes is designed to cover the spatial sector of interest using optimal array pattern synthesis technique and optimal FIR filters design technique. These techniques lead the resulting beampatterns higher mainlobe approximation accuracy and yet lower sidelobes. For the scenario of strong out-of-sector interfering sources, our approaches can form nulls or notches in the direction of them and yet guarantee that the mainlobe response of the beamformers is constant over the design band. Numerical results show that the proposed time-domain processing DOA estimator has comparable performance with the proposed frequency-domain processing method, and that both of them are able to resolve correlated source signals and provide better resolution at lower signal-to-noise ratio (SNR) and lower root-mean-square error (RMSE) of the DOA estimate compared with the existing method. Our beamspace DOA estimators maintain good DOA estimation and spatial resolution capability in the scenario of strong out-of-sector interfering sources.</p

Optimally Joint Subcarrier Matching and Power Allocation in OFDM Multihop System

<p/> <p>Orthogonal frequency division multiplexing (OFDM) multihop system is a promising way to increase capacity and coverage. In this paper, we propose an optimally joint subcarrier matching and power allocation scheme to further maximize the total channel capacity with the constrained total system power. First, the problem is formulated as a mixed binary integer programming problem, which is prohibitive to find the global optimum in terms of complexity. Second, by making use of the equivalent channel power gain for any matched subcarrier pair, a low complexity scheme is proposed. The optimal subcarrier matching is to match subcarriers by the order of the channel power gains. The optimal power allocation among the matched subcarrier pairs is water-filling. An analytical argument is given to prove that the two steps achieve the optimally joint subcarrier matching and power allocation. The simulation results show that the proposed scheme achieves the largest total channel capacity as compared to the other schemes, where there is no subcarrier matching or no power allocation.</p

2-D Unitary ESPRIT-Like Direction-of-Arrival (DOA) Estimation for Coherent Signals with a Uniform Rectangular Array

A unitary transformation-based algorithm is proposed for two-dimensional (2-D) direction-of-arrival (DOA) estimation of coherent signals. The problem is solved by reorganizing the covariance matrix into a block Hankel one for decorrelation first and then reconstructing a new matrix to facilitate the unitary transformation. By multiplying unitary matrices, eigenvalue decomposition and singular value decomposition are both transformed into real-valued, so that the computational complexity can be reduced significantly. In addition, a fast and computationally attractive realization of the 2-D unitary transformation is given by making a Kronecker product of the 1-D matrices. Compared with the existing 2-D algorithms, our scheme is more efficient in computation and less restrictive on the array geometry. The processing of the received data matrix before unitary transformation combines the estimation of signal parameters via rotational invariance techniques (ESPRIT)-Like method and the forward-backward averaging, which can decorrelate the impinging signalsmore thoroughly. Simulation results and computational order analysis are presented to verify the validity and effectiveness of the proposed algorithm

Parametric Adaptive Radar Detector with Enhanced Mismatched Signals Rejection Capabilities

<p/> <p>We consider the problem of adaptive signal detection in the presence of Gaussian noise with unknown covariance matrix. We propose a parametric radar detector by introducing a design parameter to trade off the target sensitivity with sidelobes energy rejection. The resulting detector merges the statistics of Kelly's GLRT and of the Rao test and so covers Kelly's GLRT and the Rao test as special cases. Both invariance properties and constant false alarm rate (CFAR) behavior for this detector are studied. At the analysis stage, the performance of the new receiver is assessed and compared with several traditional adaptive detectors. The results highlight better rejection capabilities of this proposed detector for mismatched signals. Further, we develop two two-stage detectors, one of which consists of an adaptive matched filter (AMF) followed by the aforementioned detector, and the other is obtained by cascading a GLRT-based Subspace Detector (SD) and the proposed adaptive detector. We show that the former two-stage detector outperforms traditional two-stage detectors in terms of selectivity, and the latter yields more robustness.</p