Electrical and Electronic Engineering, Imperial College London
Doi
Abstract
In this thesis, efficient methods are presented to calibrate large or small aperture
array systems containing different types of uncertainties. specifically the challenge of reducing the number of external sources required to calibrate an array
is addressed and array calibration methods suitable for use when sources may be
operating in the "near-far" field of the array are developed. Together, this can
ease the overheads involved in calibrating and recalibrating an array system.
In addition to presenting novel array calibration algorithms, this thesis also
presents a novel transformation allowing a planar array to be expressed as a
virtual uniform linear array of a much larger number of elements. This allows the
array manifold of a planar array, which in general consists of non-hyperhelical
curves, to be expressed using a number of hyperhelices which each correspond to
the array manifold of a linear array. This hyperhelical structure has the potential
to ease calibration overheads as well as having many other potential applications
in array processing.
This thesis presents novel pilot and auto array calibration schemes for estimating different types of array uncertainties. A novel pilot calibration algorithm
is proposed whereby a single source transmitting from a known location (i.e. a
pilot) at two carrier frequencies is used to estimate geometrical uncertainties in
a planar array. This is achieved by exploiting the frequency dependence on the
boundary between the "near-far" and "far" field of the array. In addition, an
auto-calibration method is presented which doesn't require any external sources
to estimate array uncertainties. Here, geometrical, complex gain and local oscillator (i.e. frequency and phase) uncertainties associated with the array elements
are considered. In this approach, array elements transmit in turn to the others
which operate as an array receiver. Large and small array apertures are investigated. Throughout the thesis, extensive computer simulations are presented to
analyse the performance of the algorithms developed.Open Acces
