Fraser K. Coutts

MVDR broadband beamforming using polynomial matrix techniques

This paper presents initial progress on formulating minimum variance distortionless response (MVDR) broadband beam-forming using a generalised sidelobe canceller (GSC) in the context of polynomial matrix techniques. The quiescent vector is defined as a broadband steering vector, and we propose a blocking matrix design obtained by paraunitary matrix completion. The polynomial approach decouples the spatial and temporal orders of the filters in the blocking matrix, and decouples the adaptive filter order from the construction of the blocking matrix. For off-broadside constraints the polynomial approach is simple, and more accurate and considerably less costly than a standard time domain broadband GSC.

Model-based sparse recovery method for automatic classification of helicopters

The rotation of rotor blades of a helicopter induces a Doppler modulation around the main Doppler shift. Such a non-stationary modulation, commonly called micro-Doppler signature, can be used to perform classification of the target. In this paper a model-based automatic helicopter classification algorithm is presented. A sparse signal model for radar return from a helicopter is developed and by means of the theory of sparse signal recovery, the characteristic parameters of the target are extracted and used for the classification. This approach does not require any learning process of a training set or adaptive processing of the received signal. Moreover, it is robust with respect to the initial position of the blades and the angle that the LOS forms with the perpendicular to the plane on which the blades lie. The proposed approach is tested on simulated and real data.

Memory and complexity reduction in parahermitian matrix manipulations of PEVD algorithms

A number of algorithms for the iterative calculation of a polynomial matrix eigenvalue decomposition (PEVD) have been introduced. The PEVD is a generalisation of the ordinary EVD and will diagonalise a parahermitian matrix via paraunitary operations. This paper addresses savings - both computationally and in terms of memory use - that exploit the parahermitian structure of the matrix being decomposed, and also suggests an implicit trimming approach to efficiently curb the polynomial order growth usually observed during iterations of the PEVD algorithms. We demonstrate that with the proposed techniques, both storage and computations can be significantly reduced, impacting on a number of broadband multichannel problems.

Complexity and search space reduction in cyclic-by-row PEVD algorithms

In recent years, several algorithms for the iterative calculation of a polynomial matrix eigenvalue decomposition (PEVD) have been introduced. The PEVD is a generalisation of the ordinary EVD and uses paraunitary operations to diagonalise a parahermitian matrix. This paper addresses potential computational savings that can be applied to existing cyclic-by-row approaches for the PEVD. These savings are found during the search and rotation stages, and do not significantly impact on algorithm accuracy. We demonstrate that with the proposed techniques, computations can be significantly reduced. The benefits of this are important for a number of broadband multichannel problems.

Analysing the performance of divide-and-conquer sequential matrix diagonalisation for large broadband sensor arrays

A number of algorithms capable of iteratively calculating a polynomial matrix eigenvalue decomposition (PEVD) have been introduced. The PEVD is an extension of the ordinary EVD to polynomial matrices and will diagonalise a parahermitian matrix using paraunitary operations. Inspired by recent work towards a low complexity divide-and-conquer PEVD algorithm, this paper analyses the performance of this algorithm — named divide-and-conquer sequential matrix diagonalisation (DC-SMD) — for applications involving broadband sensor arrays of various dimensionalities. We demonstrate that by using the DC-SMD algorithm instead of a traditional alternative, PEVD complexity and execution time can be significantly reduced. This reduction is shown to be especially impactful for broadband multichannel problems involving large arrays.

Label Consistent K-SVD for sparse micro-Doppler classification

Secondary motions of targets observed by radar introduce non-stationary returns containing the so-called micro-Doppler information. This is characterizing information that can be exploited to enhance automatic target recognition systems. In this paper, the challenge of classifying the micro-Doppler return of helicopters is addressed. A robust dictionary learning algorithm, Label Consistent K-SVD (LC-KSVD), is applied to identify effectively and efficiently helicopters. The effectiveness of the proposed algorithm is demonstrated on both synthetic and real radar data.

Exploring the use of image processing to survey and quantitatively assess historic buildings

Before architectural conservation takes place, a survey is conducted to assess the condition of the building and estimate the cost of the work. For facades, scaffolding is erected so that experts can access the building’s whole extent and gather data for analysis. This paper presents the results of a collaborative and cross-disciplinary research project aiming to automate data capture and analysis techniques for conservation of stone facades. Our research demonstrates the feasibility of a new methodology for the survey and assessment of historic buildings and will facilitate frequent surveys with minimal disruption to the general public in cities. The project has embedded architects’ expert knowledge into intelligent algorithms for automatically analysing images of facades. The combination of technologies allows for an efficient data capture while minimising the requirement for manual data analysis as well as more accurate estimates of its cost.The paper aims at illustrating how the practices of planned preventive conservation may interact with structural behavior of old buildings. First, the effectiveness of regular maintenance will be underlined, also referring to preparedness to seismic risk, and other major risks as well. Many proves have been gathered that vulnerability increases as the lack of maintenance leads to decay of devices, such as iron or timber ties, which were required by the original structural conception. Second, preparedness to risk has also a top-down meaning, traditionally expressed in tools like risk maps used for support to decision making. Mass-screening of vulnerability has already been implemented as a practice capable to reduce the impact of natural hazards, as for instance earthquakes and storms. These tools can be used for enhancing programs and therefore the quality of interventions. Third, as the understanding of preventive conservation has been enlarged by the latest researches, the theme of uses compatibility evaluation is included, considering carrying capacity and loads, or safety and strategic functions.