Antenna array calibration in wireless communications

Imperial Users onl

Estimation of DOAs of Acoustic Sources in the Presence of Sensors with Uncertainties

Direction of Arrival (DOA) estimation finds its practical importance in sophisticated video conferencing by audio visual means, locating underwater bodies, removing unwanted interferences from desired signals etc. Some efficient algorithms for DOA estimation are already developed by the researchers . The performance of these algorithms is limited by the fact that the receiving antenna array is affected by some uncertainties like mutual coupling, antenna gain and phase error etc. So considerable attention is there in recent research on this area. In this research work the effect of mutual coupling and the effect of antenna gain and phase error in uniform linear array (ULA) on the direction finding of acoustic sources is studied. Also this effect for different source spacing is compared. For that, estimates of the directions of arrival of all uncorrelated acoustic signals in the presence of unknown mutual coupling has been found using conventional Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT). Also DOAs are computed after knowing the coupling coefficients so that we can compare the two results. Simulation results have shown the fact that the degradation in performance of the algorithm due to mutual coupling becomes more if the sources become closer to each other. Also we have estimated DOAs in the presence of unknown sensor gain and phase errors and we have compared this results with the results we got by considering ideal array. Finally in this case also the effect of gain and phase error as the source spacing varies has been tested. Simulation results verify that performance degradation is more if the sources become closer

Wavefield modeling and signal processing for sensor arrays of arbitrary geometry

Sensor arrays and related signal processing methods are key technologies in many areas of engineering including wireless communication systems, radar and sonar as well as in biomedical applications. Sensor arrays are a collection of sensors that are placed at distinct locations in order to sense physical phenomena or synthesize wavefields. Spatial processing from the multichannel output of the sensor array is a typical task. Such processing is useful in areas including wireless communications, radar, surveillance and indoor positioning. In this dissertation, fundamental theory and practical methods of wavefield modeling for radio-frequency array processing applications are developed. Also, computationally-efficient high-resolution and optimal signal processing methods for sensor arrays of arbitrary geometry are proposed. Methods for taking into account array nonidealities are introduced as well. Numerical results illustrating the performance of the proposed methods are given using real-world antenna arrays. Wavefield modeling and manifold separation for vector-fields such as completely polarized electromagnetic wavefields and polarization sensitive arrays are proposed. Wavefield modeling is used for writing the array output in terms of two independent parts, namely the sampling matrix depending on the employed array including nonidealities and the coefficient vector depending on the wavefield. The superexponentially decaying property of the sampling matrix for polarization sensitive arrays is established. Two estimators of the sampling matrix from calibration measurements are proposed and their statistical properties are established. The array processing methods developed in this dissertation concentrate on polarimetric beamforming as well as on high-resolution and optimal azimuth, elevation and polarization parameter estimation. The proposed methods take into account array nonidealities such as mutual coupling, cross-polarization effects and mounting platform reflections. Computationally-efficient solutions based on polynomial rooting techniques and fast Fourier transform are achieved without restricting the proposed methods to regular array geometries. A novel expression for the Cramér-Rao bound in array processing that is tight for real-world arrays with nonidealities in the asymptotic regime is also proposed. A relationship between spherical harmonics and 2-D Fourier basis, called equivalence matrix, is established. A novel fast spherical harmonic transform is proposed, and a one-to-one mapping between spherical harmonic and 2-D Fourier spectra is found. Improvements to the minimum number of samples on the sphere that are needed in order to avoid aliasing are also proposed

Analysis and design of smart antenna arrays (SAAs) for improved directivity at GHz range for wireless communication systems.

Doctor of Philosophy in Electronic Engineering. University of KwaZulu-Natal, Durban 2018.Abstract available in PDF file

A room acoustics measurement system using non-invasive microphone arrays

This thesis summarises research into adaptive room correction for small rooms and pre-recorded material, for example music of films. A measurement system to predict the sound at a remote location within a room, without a microphone at that location was investigated. This would allow the sound within a room to be adaptively manipulated to ensure that all listeners received optimum sound, therefore increasing their enjoyment. The solution presented used small microphone arrays, mounted on the room's walls. A unique geometry and processing system was designed, incorporating three processing stages, temporal, spatial and spectral. The temporal processing identifies individual reflection arrival times from the recorded data. Spatial processing estimates the angles of arrival of the reflections so that the three-dimensional coordinates of the reflections' origin can be calculated. The spectral processing then estimates the frequency response of the reflection. These estimates allow a mathematical model of the room to be calculated, based on the acoustic measurements made in the actual room. The model can then be used to predict the sound at different locations within the room. A simulated model of a room was produced to allow fast development of algorithms. Measurements in real rooms were then conducted and analysed to verify the theoretical models developed and to aid further development of the system. Results from these measurements and simulations, for each processing stage are presented