Constant beamwidth generalised sidelobe canceller

In this paper, we proposed a constant beamwidth discrete Fourier transform (DFT) beamformer based on the generalised sidelobe canceller (GSC). Broadband signals are decomposed into frequency bins which are grouped into octaves and tapered individually. The resulting beampattern possesses constant beamwidth across the entire operating spectrum, thus ensuring uniform spatial resolution. Further incorporation of the GSC allows adaptive nulling of interference to coincide with uniform resolution, enhancing the beamformer’s performance. However, modification to the constraint equation of the standard GSC is required to account for the frequency-dependent weighting of sensors

Frequency invariant beamforming for two-dimensional and three-dimensional arrays

A novel method for the design of two-dimensional (2-D) and three-dimensional (3-D)arrays with frequency invariant beam patterns is proposed. By suitable substitu- tions, the beam pattern of a 2-D or 3-D arrays can be regarded as the 3-D or 4-D Fourier transform of its spatial and temporal parameters. Since frequency invariance can be easily imposed in the Fourier domain, a simple design method is derived. Design examples for the 2-D case are provided

Design of frequency invariant beamformer for broadband arrays

A simple method for the design of a class of arrays with frequency invariant beam patterns is proposed. Starting from the desired frequency invariant beam pattern of an n-D array, the proposed method uses a series of substitutions and an n-D inverse Fourier transform to obtain the desired frequency responses of the filters following each sensor. Given their desired frequency responses, these filters can be realized by either an analogue filter or a digital filter. Hence the proposed method can cover the design of broadband arrays with either analogue signals or discrete signals. Two design examples are provided, with one for a linear array and one for a planar array

Frequency Invariant Beamforming in Subbands

In this paper, two subband implementations of a frequency invariant beamformer (FIB) are studied. In the first structure, the received array signals are split into subbands and an FIB is operated in each of the corresponding decimated subbands, with a potential of achieving a lower computational complexity. As the spatio-temporal distributionof the subband signals is different from the original fullband signal, a modified design method of the FIB is proposed. Based on the subband implementation, we then change the sensor spacings of different subband signals so that lower frequency bands have a larger spacing, which results in a class of FIBs with scaled aperture with improved performance in lower frequencies. Several design examples are given to show the performance of our new structures

Off-broadside main beam design for frequency invariant beamformers

In a previously proposed design method for frequency invariant beamforming, the design for the case of an off-broadside main beam is not satisfactory. After a detailed analysis, we propose two methods to overcome this problem: one is to increase the length of the FIR filter attached to each sensor, as a result, we need to sample the transformed desired response more densely in the associated direction; the other one is to design a broadside main beam first, then it is convolved with appropriate steering delay filters. Design examples show that the two methods can provide satisfactory results

Adaptive beamforming using frequency invariant uniform concentric circular arrays

This paper proposes new adaptive beamforming algorithms for a class of uniform concentric circular arrays (UCCAs) having near-frequency invariant characteristics. The basic principle of the UCCA frequency invariant beamformer (FIB) is to transform the received signals to the phase mode representation and remove the frequency dependence of individual phase modes through the use of a digital beamforming or compensation network. As a result, the far field pattern of the array is electronic steerable and is approximately invariant over a wider range of frequencies than the uniform circular arrays (UCAs). The beampattern is governed by a small set of variable beamformer weights. Based on the minimum variance distortionless response (MVDR) and generalized sidelobe canceller (GSC) methods, new recursive adaptive beamforming algorithms for UCCA-FIB are proposed. In addition, robust versions of these adaptive beamforming algorithms for mitigating direction-of-arrival (DOA) and sensor position errors are developed. Simulation results show that the proposed adaptive UCCA-FIBs converge much faster and reach a considerable lower steady-state error than conventional broadband UCCA beamformers without using the compensation network. Since fewer variable multipliers are required in the proposed algorithms, it also leads to lower arithmetic complexity and faster tracking performance than conventional methods. © 2007 IEEE.published_or_final_versio

Frequency invariant MVDR beamforming without filters and implementation using MIMO radar

Frequency invariant beamforming with sensor arrays is generally achieved using filters in the form of tapped delay-lines following each sensor. However it has been recently shown that with the help of the rectangular smart antenna array, it is possible to generate frequency invariant beampattern without using filters. In this paper, this frequency invariant beamforming technique is utilized to perform MVDR beamforming in the beamspace by designing frequency invariant beams spanning the desired range of azimuthal angles and optimally combining them. However, the performance of the frequency invariant beamformer depends on the number of sensors which could be large for a rectangular array of size M × N. Making use of the virtual array concept used in MIMO radar, a novel method of producing the same frequency invariant beam, using only M transmitting and N receiving antennas, is proposed and a design example is provided to demonstrate the idea

Broadband adaptive beamforming with low complexity and frequency invariant response

This thesis proposes different methods to reduce the computational complexity as well as increasing the adaptation rate of adaptive broadband beamformers. This is performed exemplarily for the generalised sidelobe canceller (GSC) structure. The GSC is an alternative implementation of the linearly constrained minimum variance beamformer, which can utilise well-known adaptive filtering algorithms, such as the least mean square (LMS) or the recursive least squares (RLS) to perform unconstrained adaptive optimisation.A direct DFT implementation, by which broadband signals are decomposed into frequency bins and processed by independent narrowband beamforming algorithms, is thought to be computationally optimum. However, this setup fail to converge to the time domain minimum mean square error (MMSE) if signal components are not aligned to frequency bins, resulting in a large worst case error. To mitigate this problem of the so-called independent frequency bin (IFB) processor, overlap-save based GSC beamforming structures have been explored. This system address the minimisation of the time domain MMSE, with a significant reduction in computational complexity when compared to time-domain implementations, and show a better convergence behaviour than the IFB beamformer. By studying the effects that the blocking matrix has on the adaptive process for the overlap-save beamformer, several modifications are carried out to enhance both the simplicity of the algorithm as well as its convergence speed. These modifications result in the GSC beamformer utilising a significantly lower computational complexity compare to the time domain approach while offering similar convergence characteristics.In certain applications, especially in the areas of acoustics, there is a need to maintain constant resolution across a wide operating spectrum that may extend across several octaves. To attain constant beamwidth is difficult, particularly if uniformly spaced linear sensor array are employed for beamforming, since spatial resolution is reciprocally proportional to both the array aperture and the frequency. A scaled aperture arrangement is introduced for the subband based GSC beamformer to achieve near uniform resolution across a wide spectrum, whereby an octave-invariant design is achieved. This structure can also be operated in conjunction with adaptive beamforming algorithms. Frequency dependent tapering of the sensor signals is proposed in combination with the overlap-save GSC structure in order to achieve an overall frequency-invariant characteristic. An adaptive version is proposed for frequency-invariant overlap-save GSC beamformer. Broadband adaptive beamforming algorithms based on the family of least mean squares (LMS) algorithms are known to exhibit slow convergence if the input signal is correlated. To improve the convergence of the GSC when based on LMS-type algorithms, we propose the use of a broadband eigenvalue decomposition (BEVD) to decorrelate the input of the adaptive algorithm in the spatial dimension, for which an increase in convergence speed can be demonstrated over other decorrelating measures, such as the Karhunen-Loeve transform. In order to address the remaining temporal correlation after BEVD processing, this approach is combined with subband decomposition through the use of oversampled filter banks. The resulting spatially and temporally decorrelated GSC beamformer provides further enhanced convergence speed over spatial or temporal decorrelation methods on their own