Peter O'Shea

Algorithms for instantaneous frequency estimation: a comparative study

This paper examines the problem of instantaneous frequency (IF) estimation for Frequency Modulated (FM) signals imbedded in white Gaussian noise. It reviews currently available techniques and in addition proposes some new ones based on a modelling of the signal phase as a polynomial. Both linear least-squares techniques and Maximum Likelihood (ML) techniques are investigated for estimating the polynomial coefficients. It is seen that the linear least squares approach is efficient (i. e. unbiased and meets the Cramer-Rao bounds) for high SNR while the ML scheme is efficient for a much larger range of SNR. Theoretical lower variance bounds are given for estimating the polynomial coefficients and are compared with the results of simulations. Guidelines are given as to which estimation method should be used for a given signal class and Signal to Noise Ratio (SNR) level.

Characterization of Sky-region Morphological-temporal Airborne Collision Detection

Automated airborne collision-detection systems are a key enabling technology for facilitat- ing the integration of unmanned aerial vehicles (UAVs) into the national airspace. These safety-critical systems must be sensitive enough to provide timely warnings of genuine air- borne collision threats, but not so sensitive as to cause excessive false-alarms. Hence, an accurate characterisation of detection and false alarm sensitivity is essential for understand- ing performance trade-offs, and system designers can exploit this characterisation to help achieve a desired balance in system performance. In this paper we experimentally evaluate a sky-region, image based, aircraft collision detection system that is based on morphologi- cal and temporal processing techniques. (Note that the examined detection approaches are not suitable for the detection of potential collision threats against a ground clutter back- ground). A novel collection methodology for collecting realistic airborne collision-course target footage in both head-on and tail-chase engagement geometries is described. Under (hazy) blue sky conditions, our proposed system achieved detection ranges greater than 1540m in 3 flight test cases with no false alarm events in 14.14 hours of non-target data (under cloudy conditions, the system achieved detection ranges greater than 1170m in 4 flight test cases with no false alarm events in 6.63 hours of non-target data). Importantly, this paper is the first documented presentation of detection range versus false alarm curves generated from airborne target and non-target image data.

A Kalman Filtering Approach to Rapidly Detecting Modal Changes in Power Systems

This paper applies Kalman filtering techniques to the problem of detecting modal changes in large interconnected power systems. Short term alarming procedures are developed based on the statistics of the power spectral density of the Kalman filter innovation. The new technique is tested on both simulated data and real data obtained from power systems in normal operation. The particular advantage of the new method is its ability to detect changes very quickly.

On Refining Polynomial Phase Signal Parameter Estimates

Newton algorithms are commonly used in the final “refinement” stage of parameter estimation for sinusoids and higher order phase polynomial signals. Such parameter estimation scenarios arise commonly in radar applications where the radial target velocity (which is possibly time-varying) must be estimated. The author and coworkers have previously proposed an elegant and efficient alternative to a Newton gradient search type algorithm based on filtering and phase unwrapping. A statistical and computational analysis of this filtering/phase unwrapping method is presented here. The analysis shows the algorithm to be computationally efficient and much less sensitive to the accuracy of the initial guesses for the parameters than a Newton algorithm. A first-order statistical analysis of the filtering/phase unwrapping algorithm is performed, and guidelines are derived for the required accuracy of the initial estimates. Simulations are presented to confirm the analysis.

Estimation of Modal Damping in Power Networks

This paper describes a new Fourier-based sliding window method for estimating the damping of exponentially decaying modes that occur in power networks as a result of electric disturbances. The key innovation in the new method is the use of multiple orthogonal sliding windows rather than just a single pair of sliding windows. The use of these multiple orthogonal windows allows least-squares averaging strategies to be used, enabling lower variance estimates to be obtained as a result. A statistical analysis is provided, and simulations are presented to illustrate the effectiveness of the new method. The technique is also applied to real power system data.

A computationally efficient technique for estimating the parameters of polynomial-phase signals from noisy observations

Many real-world applications are characterized by the presence of polynomial phase signals embedded in noise. These applications include radar, sonar, telemetry, communications, and power systems. In a significant number of these applications, it is highly desirable to be able to accurately estimate the polynomial phase signal parameters. This correspondence presents a computationally efficient method for estimating any or all of the parameters of polynomial-phase signals in white Gaussian noise and provides a first-order statistical analysis of the technique. Simulations are also presented to support the theoretical analysis.

Instantaneous Frequency Of Signals: Concepts, Estimation Techniques And Applications

The instantaneous frequency (IF) of a signal is a parameter which is of significant practical importance, since in many situations it corresponds to some physical phenomenon. This paper considers the definition of the IF, describes a number of ways of estimating it (along with a consideration of how closely the estimates are likely to correspond to physical reality), and presents two applications where IF estimation is used.

A New Class of Multilinear Functions for Polynomial Phase Signal Analysis

This paper introduces a new class of multilinear functions which can be used for analyzing a signal with time-varying frequency. The new class subsumes a number of existing functions, including the higher order ambiguity functions (HAFs), the polynomial Wigner-Ville distributions (PWVDs), and the higher order phase (HP) functions. As well as establishing a link between these existing functions, the new class provides a formalism which allows for the creation of useful new multilinear functions. A number of new functions are derived from the class.

Improving Polynomial Phase Parameter Estimation by Using Nonuniformly Spaced Signal Sample Methods

This paper investigates the computationally efficient parameter estimation of polynomial phase signals embedded in noise. Many authors have previously proposed multilinear analysis methods which operate on uniformly spaced samples of the signal. Such methods include the higher-order ambiguity functions (HAFs), the Polynomial Wigner-Ville distributions (PWVDs) and the higher-order phase (HP) functions. This paper investigates the use of multilinear methods which operate on nonuniformly spaced signal samples. It is seen that the relaxation of the requirement to use uniformly spaced samples in the analysis can lead to significant performance improvements. A theoretical analysis and simulations are presented in support of these claims.

Research and/or learning and teaching: a study of Australian professors' priorities, beliefs and behaviours

This paper presents findings from an empirical study of key aspects of the teaching and research priorities, beliefs and behaviours of 72 professorial and associate professorial academics in Science, Information Technology and Engineering across four faculties in three Australian universities. The academics ranked 16 research activities and 16 matched learning and teaching (L&T) activities from three perspectives: job satisfaction, role model behaviour and perceptions of professional importance. The findings were unequivocally in favour of research in all three areas and remarkably consistent across the universities. The only L&T activity that was ranked consistently well was ‘improving student satisfaction ratings for teaching’, an area in which academics are increasingly held accountable. Respondents also indicated that their seniors encourage research efforts more than L&T efforts. Recommendations include that higher education rewards for quality L&T are maintained or improved and that recognition of L&T research domains is further strengthened.