Iman Moazzen

Broadband beamforming using 2D trapezoidal filters and nested arrays

A broadband beamforming technique using 2D trapezoidal filters (TFs) and nested arrays is proposed. Each subarray feeds into a subband beamformer processing an octave frequency band. Using subsampling in space and time all frequency subbands are transformed into the same frequency range in the 2D frequency domain. This allows using the same 2D trapezoidal filter design for all subbands. The advantage of using nested arrays is that the effective aperture for low temporal frequencies is larger than in the case of using a Uniform Linear Array (ULA) with the same number of array elements. This leads to a better spatial selectivity at low frequencies than using ULAs. The performance of the proposed beamformer is illustrated and evaluated using simulations.

Efficient Implementation of Broadband Beamformers Using Nested Hexagonal Arrays and Frustum Filters

A broadband beamformer is proposed based on nested hexagonal arrays, hexagonal frustum filters and multirate techniques. The nested hexagonal arrays used here consist of several hexagonal arrays of increasing size in the x-y plane (each one called subarray) where the distance between elements in each subarray is two times larger than in the previous one. The proposed beamformer consists of subarray beamformers, each one using the signals obtained from one of the nested hexagonal arrays as the input. These signals are filtered and downsampled so that the Region of Support (ROS) of the resulting 3D signals in the 3D frequency domain are the same for all subbands. The same hexagonal frustum filter design can therefore be used for all subarray beamformers to pass the desired signal and eliminate interferences. The use of nested arrays leads to larger effective aperture at low temporal frequencies and thus, better selectivity for low frequencies. Further, hexagonal arrays are known to require a lower sensor density for alias free sampling than rectangular arrays. Examples illustrate the performance of the proposed beamformer with respect to beampattern and computational complexity.

Broadband beamfoming using Nested Planar Arrays and 3D FIR frustum filters

A topology of planar array called Nested Planar Arrays (NPAs) is used for broadband beamforming. The NPAs consist of several Uniform Planar Arrays (UPAs), each one with the double element distance of the previous array. The signals from these arrays are fed into different subbands which process different octaves of temporal frequency bands. The combination of NPAs and multirate techniques leads to the same 3D frustum filter frequency specifications for all subbands. The passband of these 3D frustum filters does not include the low temporal frequencies where it is difficult to achieve high selectivity. Simulation results indicate that with the same number of sensors, NPA can achieve longer aperture size compared to a UPA and thus higher selectivity particularly for lower temporal frequencies. For the same aperture size, NPA can be implemented with much less sensors and much less computations than a UPA with small deterioration in the performance.

An intelligent classifier for cardiac arrhythmias recognition

The aim of this article is to propose an intelligent electrocardiogram classifier. The classifier is similar to probabilistic neural networks. In these networks, a user needs to set some parameters optionally. Improper selections may decrease the performance drastically. The proposed method needs no optional parameter settings and all required parameters are extracted from the statistics of the input signals. The proposed classifier has two layers and a database of known signals that has been categorized and labeled to M classes based on their similarities. The first layer calculates the similarities of the input unknown signal to the known signals of each class using Basis Radial functions and outputs Bayesian variables equal to the number of classes. The second layer is just a maximum selector of these Bayesian variables as the winner. In fact, it indicates that the input signal most probably belongs to the class in which Bayesian variable is maximum. Five classes of ECG signals from MIT-BIH arrhythmia database are selected to illustrate the good performance of the non-invasive proposed classifier compared to the previous methods. Moreover, acceptable low computational complexity and robustness against high noise are significant features of the proposed classifier.

A novel blind frequency domain equalizer for SIMO systems

A novel blind equalization method is introduced for SIMO systems. In the proposed design method, based on the blindly estimated characteristics of Rician fading channels, a realizable equalizer which is constructed to minimize the mean square error (MSE) from the frequency domain perspective is designed to recover the transmitted sequence. Diversity techniques and equalization methods are combined to enhance the performance. Illustrative simulations demonstrate the improvement in the proposed method.

A nested microphone array for broadband audio signal processing

The application of a recently developed broadband beamformer to distinguish audio signals received from different directions is experimentally tested. The beamformer combines spatial and temporal subsampling using a nested array and multirate techniques which leads to the same region of support in the frequency domain for all subbands. This allows using the same beamformer for all subbands. The experimental set-up is presented and the recorded signals are analyzed. Results indicate that the proposed approach can be used to distinguish plane waves propagating with different direction of arrivals.

Analysis of a broadband beamformer based on trapezoidal filters and nested arrays

A broadband beamformer using nested arrays, multi-rate techniques and multi-dimensional filters, recently proposed in [11-12], will be analyzed in detail. Using appropriate subsampling in space and time for each nested subarray leads to signals with the same region of support (ROS) in the 2D frequency domain for all subarrays. This ROS will be shown to be the top octave of the signal bandwidth and can be used to obtain higher selectivity at low frequencies. An example of the beampattern obtained using the proposed approach illustrates the almost frequency-invariant response of the beamformer.

An approach for joint blind space-time equalization and DOA estimation

A multi-stage structure to jointly combat multi-user interference and fading channels is presented. Neither the DOA nor a training sequence is assumed to be available for the receiver. The only assumption is that the transmitted signal satisfies the constant modulus property which is valid for many modulation schemes, and can be exploited by the multimodulus algorithm. Taking advantage of virtual subarrays, the DOA at each stage is estimated and used to compute the next stage input. Each stage operates in two modes, the starting and the tracking mode. Thanks to the adaptive structure, it can deal with time-varying DOAs and channels. Simulation results illustrate the performance of this method.

A Multistage Space---Time Equalizer for Blind Source Separation

A multistage space–time equalizer (STE) is proposed to blindly separate signals received by an antenna array from different sources simultaneously. Neither the direction of arrival (DOA) nor a training sequence is assumed to be available at the receiver. The only assumption is that the transmitted signals satisfy the constant modulus property, which is valid for many modulation schemes, and can be exploited by the multi-modulus algorithm. Each stage consists of an adaptive beamformer, a DOA estimator and an equalizer. Its function is to jointly combat multi-user interference and the effect of fading channels between sources and the antenna. An adaptive version of the basic structure of generalized sidelobe canceller (GSC), called adaptive GSC, is presented which can track a user and strongly attenuate other users with different DOAs. The possibly time-varying DOA for each user is estimated using the phase shift between the outputs of two subarray beamformers at each stage. The estimated DOAs are used to improve multi-user interference rejection and to compute the input to the next stage. In order to significantly alleviate inter-stage error propagation and provide a fast convergence, a mean-square-error sorting algorithm is proposed which assigns detected sources to different stages according to the reconstruction error. Further, to speed up the convergence, a simple, yet efficient, DOA estimation algorithm is proposed which can provide good initial DOAs for the multistage STE. Simulation results illustrate the performance of the proposed STE and show that it can deal effectively with changing DOAs and time-varying channels.

A blind equalization method for multipath rician fading channels

A novel blind equalization method is proposed for multipath Rician fading channels. In the proposed method, based on blindly estimated characteristics of Rician fading channel, a realizable DFE is designed to minimize the mean square error (MSE) from the frequency domain perspective. DFEs filters are implemented in an adaptive structure to enable dealing with rapid time-varying channels. The method shows better convergence performance compared to similar existing methods. Furthermore, it works satisfactorily even for channels with severe dispersions.