Yee Hong Leung

A Dolph-Chebyshev approach to the synthesis of array patterns for uniform circular arrays

Uniform circular arrays (UCAs) are naturally suited to provide 360 degrees of coverage in the azimuthal plane. In this paper, we describe a new approach for synthesizing array patterns with guaranteed maximum sidelobe levels for any look direction. The advantage of this approach is that it is computationally efficient which makes it eminently suitable for real-time beamforming and beamsteering applications. The approach is based on the Dolph-Chebyshev method for uniform linear arrays except here, the Dolph-Chebyshev method is applied to the transformed array response vector of the UCAs.

An improved array interpolation approach to DOA estimation in correlated signal environments

Many popular direction-of-arrival (DOA) estimators rely on the fact that the array response vector of the array is Vandermonde, for example, that of a uniform linear array (ULA). Array interpolation is a preprocessing technique to transform the array response vector of a planar array of arbitrary geometry to that of a ULA over an angular sector. While good approximation within the target sector is attained in the existing array interpolation approaches, the response of the interpolated array in the out-of-sector region is at best partially controlled. Accordingly, out-of-sector signals, especially those highly correlated with the in-sector signals, can degrade significantly the performance of DOA estimators (e.g., MUSIC with spatial smoothing) that rely on the Vandermonde form to work correctly. In this paper, we propose an improved array interpolation approach that takes into account the array response over the full azimuth. We present also numerical examples to demonstrate the shortcomings of the existing approaches and the effectiveness of our proposal.

Minimax filters for microphone arrays

Conventionally, minimax spatial/spectral filters for microphone arrays are designed by first discretizing the spatial and frequency domains into a finite number of grid points and then performing the optimization over these points. The drawback with this approach is that the response of the spatial/spectral filters in between the grid points can be poor. More recently, an approach that performs the minimax design over the continuum of points in the decision space has appeared in the literature. In this brief, we describe an approach to solving this continuous decision space design problem that is numerically more elegant and efficient. The effectiveness of the new method is illustrated by a numerical example.

Data-adaptive array interpolation for DOA estimation in correlated signal environments

Many popular direction-of-arrival (DOA) estimators rely on the fact that the array response vector of the array is Vandermonde, for example, that of a uniform linear array (ULA). Array interpolation is a preprocessing technique to transform the array response vector of a planar array of arbitrary geometry to that of a ULA over an angular sector. While good approximation within the target sector is attained with the various existing array interpolation approaches, the response of the interpolated array in the out-of-sector region is at best partially controlled. Accordingly, out-of-sector signals, especially those highly correlated with the in-sector signals, can degrade significantly the performance of DOA estimators that rely on the Vandermonde form to work correctly. Recently, we proposed an improved array interpolation approach that takes into account the array response over the full azimuth. In this paper, we develop the idea further and present a simple data-adaptive array interpolation scheme that can provide significantly better accuracy in the DOA estimates. We present examples to demonstrate the effectiveness of our proposal.

The Cramer-Rao lower bound for towed array shape estimation with a single source

This correspondence derives the Cramer-Rao lower bound (CRLB) for towed array shape estimation when using the receiver outputs in the presence of a single planewave narrowband source and additive white noise. Both known and unknown source directions are considered. The CRLB shows that accurate array shape estimation is possible only if the array shape is relatively linear and the source direction away from endfire.

Transformations for nonideal uniform circular arrays operating in correlated signal environments

The Davies transformation is a method to transform the steering vector of a uniform circular array (UCA) to one with Vandermonde form. As such, it allows techniques such as spatial smoothing for direction-of-arrival (DOA) estimation in a correlated signal environment, developed originally for uniform linear arrays, to be applied to UCAs. However, the Davies transformation can be highly sensitive to perturbations of the underlying array model. This paper presents a method for deriving a more robust transformation using optimization techniques. The effectiveness of the method is illustrated through a number of DOA estimation examples.

Constraints for maximally flat optimum broadband antenna arrays

Frequency response shaping for the direct form pre-steered broadband (PB) antenna array processor is often achieved by imposing look direction constraints on the weights of the processor. This results in a linearly constrained optimization problem. To ensure a maximally flat spatial response of a specified order in the look direction of the PB processor, additional constraints known as derivative constraints can be further imposed on the weights. In general, derivative constraints corresponding to necessary and sufficient (NS) conditions for a maximally flat spatial power response can result in a quadratic equality constrained optimization problem. We transform the quadratic NS derivative constraints to parameterized linear forms. These parameterized linear forms allow the global optimum of the quadratic equality constrained optimization problem to be obtained easily. They also provide a general framework for deriving new sets of derivative constraints which correspond only to sufficient conditions for a maximally flat spatial power response. These sufficient derivative constraints are useful for real-time processing because of their reduced computational requirements and because they ran deliver performance comparable to the NS derivative constraints. >

A Nonlinear

A nonlinear M-estimation approach is proposed to solve the multiuser detection problem in asynchronous code-division multiple-access (CDMA) systems where the ambient noise is impulsive and the delays are not known. We treat the unknown delays as nuisance parameters and the transmitted symbols as parameters of interest. We also analyze the asymptotic performance of the proposed estimator and propose suboptimal but computationally efficient procedures for solving the nonlinear optimization function. Simulation results show considerable improvements over the conventional approaches

M

In acoustic applications, the signal source of interest is generally broadband and the background noise field is predominantly isotropic. In this letter, the performance of the broadband generalized sidelobe canceller, optimized with respect to an isotropic noise field, is analyzed and compared against the performance of the conventional summing beamformer. The comparison is based on an ideal continuous-time infinite-length generalized sidelobe canceller with the aim of determining the performance limits of this beamforming structure.

-Estimation Approach to Robust Asynchronous Multiuser Detection in Non-Gaussian Noise

In this paper, a new method for the design of approximately linear phase IIR filters is proposed. This method is based on first designing an asymmetrical FIR filter which is approximately linear phase and then deriving a low order approximately linear phase IIR filter by model reduction techniques.