Defence Science and Technology Group

Increasingly, for many application areas, it is becoming important to include elements of nonlinearity and non-Gaussianity in order to model accurately the underlying dynamics of a physical system. Moreover, it is typically crucial to process data on-line as it arrives, both from the point of view of storage costs as well as for rapid adaptation to changing signal characteristics. In this paper, we review both optimal and suboptimal Bayesian algorithms for nonlinear/non-Gaussian tracking problems, with a focus on particle filters. Particle filters are sequential Monte Carlo methods based on point mass (or "particle") representations of probability densities, which can be applied to any state-space model and which generalize the traditional Kalman filtering methods. Several variants of the particle filter such as SIR, ASIR, and RPF are introduced within a generic framework of the sequential importance sampling (SIS) algorithm. These are discussed and compared with the standard EKF through an illustrative example.

Abstract Mechanisms of hydrogen embrittlement in steels and other materials are described, and the evidence supporting various hypotheses, such as those based on hydride formation, hydrogen-enhanced decohesion, hydrogen-enhanced localised plasticity, adsorption-induced dislocation emission, and hydrogen-vacancy interactions, are summarised. The relative importance of these mechanisms for different fracture modes and materials are discussed based on detailed fractographic observations and critical experiments.

This paper presents an experimental and theoretical investigation of the applicability of the time-reversal concept to guided waves in plate-like structures, where the stress waves are dispersive and of multi-modes. It is shown that temporal and spatial focusing can be achieved through time reversal, although the dispersive behaviour of the flexural waves renders it impossible to exactly reconstruct the waveform of the original excitation. Based on the principle of the time-reversal concept, a digital imaging method suitable for distributed sensor/actuator networks has been developed. This new method, which overcomes the limitation of the conventional phased array method that operates under pulse-echo mode, provides an efficient imaging method for locating and approximate sizing of structural damages. In addition, it has been shown that signal strengths can be considerably enhanced by applying the present synthetic time-reversal method, thus reducing the number of sensors and actuators required to achieve a given signal-to-noise ratio.

A fabric coating prepared from a homogeneous mixture of fluorinated-decyl polyhedral oligomeric silsesquioxane and hydrolyzed fluorinated alkyl silane shows remarkable self-healing superhydrophobic and superoleophobic properties and excellent durability against UV light, acid, repeated machine washes, and severe abrasion (see picture).

We describe an investigation into e-mail content mining for author identification, or authorship attribution, for the purpose of forensic investigation. We focus our discussion on the ability to discriminate between authors for the case of both aggregated e-mail topics as well as across different e-mail topics. An extended set of e-mail document features including structural characteristics and linguistic patterns were derived and, together with a Support Vector Machine learning algorithm, were used for mining the e-mail content. Experiments using a number of e-mail documents generated by different authors on a set of topics gave promising results for both aggregated and multi-topic author categorisation.

Mental toughness has received increased scholarly attention in recent years, yet conceptual issues related to its (a) dimensionality, (b) nomological network, and (c) traitness remain unresolved. The series of studies reported in this article were designed to examine these three substantive issues across several achievement contexts, including sport, education, military, and the workplace. Five studies were conducted to examine these research aims-Study 1: N = 30; Study 2: calibration sample (n = 418), tertiary students (n = 500), athletes (n = 427), and employees (n = 550); Study 3: N = 497 employees; Study 4: N = 203 tertiary students; Study 5: N = 115 army candidates. Collectively, the results of these studies revealed that mental toughness may be best conceptualized as a unidimensional rather than a multidimensional concept; plays an important role in performance, goal progress, and thriving despite stress; and can vary and have enduring properties across situations and time. This series of studies provides a foundation for further basic and applied research of mental toughness across various achievement contexts.

High-spectral-resolution remote-sensing data are first transformed so that the noise covariance matrix becomes the identity matrix. Then the principal components transform is applied. This transform is equivalent to the maximum noise fraction transform and is optimal in the sense that it maximizes the signal-to-noise ratio (SNR) in each successive transform component, just as the principal component transform maximizes the data variance in successive components. Application of this transform requires knowledge or an estimate of the noise covariance matrix of the data. The effectiveness of this transform for noise removal is demonstrated in both the spatial and spectral domains. Results that demonstrate the enhancement of geological mapping and detection of alteration mineralogy in data from the Pilbara region of Western Australia, including mapping of the occurrence of pyrophyllite over an extended area, are presented.>

We investigate the problem of bearings-only tracking of manoeuvring targets using particle filters (PFs). Three different (PFs) are proposed for this problem which is formulated as a multiple model tracking problem in a jump Markov system (JMS) framework. The proposed filters are (i) multiple model PF (MMPF), (ii) auxiliary MMPF (AUX-MMPF), and (iii) jump Markov system PF (JMS-PF). The performance of these filters is compared with that of standard interacting multiple model (IMM)-based trackers such as IMM-EKF and IMM-UKF for three separate cases: (i) single-sensor case, (ii) multisensor case, and (iii) tracking with hard constraints. A conservative CRLB applicable for this problem is also derived and compared with the RMS error performance of the filters. The results confirm the superiority of the PFs for this difficult nonlinear tracking problem.

The periodogram of a time series that contains a sinusoidal component provides a crude estimate of its frequency parameter, the maximizer over the Fourier frequencies being within O(T/sup -1/) of the frequency as the sample size T increases. In the paper, a technique for obtaining an estimator that has root mean square error of order T/sup -3/2/ is presented, which involves only the Fourier components of the time series at three frequencies, The asymptotic variance of the estimator varies between, roughly, the asymptotic variance of the maximizer of the periodogram over all frequencies (the Cramer-Rao lower bound) and three times this variance. The advantage of the new estimator is its computational simplicity.>

Information communications technology systems are facing an increasing number of cyber security threats, the majority of which are originated by insiders. As insiders reside behind the enterprise-level security defence mechanisms and often have privileged access to the network, detecting and preventing insider threats is a complex and challenging problem. In fact, many schemes and systems have been proposed to address insider threats from different perspectives, such as intent, type of threat, or available audit data source. This survey attempts to line up these works together with only three most common types of insider namely traitor, masquerader, and unintentional perpetrator, while reviewing the countermeasures from a data analytics perspective. Uniquely, this survey takes into account the early stage threats which may lead to a malicious insider rising up. When direct and indirect threats are put on the same page, all the relevant works can be categorised as host, network, or contextual data-based according to audit data source and each work is reviewed for its capability against insider threats, how the information is extracted from the engaged data sources, and what the decision-making algorithm is. The works are also compared and contrasted. Finally, some issues are raised based on the observations from the reviewed works and new research gaps and challenges identified.

Recent developments in random finite sets (RFSs) have yielded a variety of tracking methods that avoid data association. This paper derives a form of the full Bayes RFS filter and observes that data association is implicitly present, in a data structure similar to multiple hypothesis tracking (MHT). Subsequently, algorithms are obtained by approximating the distribution of associations. Two algorithms result: one nearly identical to joint integrated probabilistic data association (JIPDA), and another related to the multiple target multi-Bernoulli (MeMBer) filter. Both improve performance in challenging environments.

Situation-aware technologies enabled by multitarget tracking will lead to new services and applications in fields such as autonomous driving, indoor localization, robotic networks, and crowd counting. In this tutorial paper, we advocate a recently proposed paradigm for scalable multitarget tracking that is based on message passing or, more concretely, the loopy sum-product algorithm. This approach has advantages regarding estimation accuracy, computational complexity, and implementation flexibility. Most importantly, it provides a highly effective, efficient, and scalable solution to the probabilistic data association problem, a major challenge in multitarget tracking. This fact makes it attractive for emerging applications requiring real-time operation on resource-limited devices. In addition, the message passing approach is intuitively appealing and suited to nonlinear and non-Gaussian models. We present message-passing-based multitarget tracking methods for single-sensor and multiple-sensor scenarios, and for a known and unknown number of targets. The presented methods can cope with clutter, missed detections, and an unknown association between targets and measurements. We also discuss the integration of message-passing-based probabilistic data association into existing multitarget tracking methods. The superior performance, low complexity, and attractive scaling properties of the presented methods are verified numerically. In addition to simulated data, we use measured data captured by two radar stations with overlapping fields-of-view observing a large number of targets simultaneously.

This paper studies the problem of tracking a ballistic object in the reentry phase by processing radar measurements. A suitable (highly nonlinear) model of target motion is developed and the theoretical Cramer-Rao lower bounds (CRLB) of estimation error are derived. The estimation performance (error mean and standard deviation; consistency test) of the following nonlinear filters is compared: the extended Kalman filter (EKF), the. statistical linearization, the particle filtering, and the unscented Kalman filter (UKF). The simulation results favor the EKF; it combines the statistical efficiency with a modest computational load. This conclusion is valid when the target ballistic coefficient is a priori known.

In order to improve the efficiency of the carbon dioxide cycling process and to reduce amine emissions, a series of nonvolatile amino acid salts with sterically hindered amine groups were investigated to determine their potential as direct replacements for monoethanolamine (MEA) in submarine-based CO 2 scrubbers. Absorption from atmospheres containing various levels of CO 2 was measured to assess the total capacities and absorption rates of amine solutions. The regeneration rates and extent of CO 2 desorption were established by heating these solutions. 13 C NMR spectroscopy was used to establish reaction products and solution compositions after both absorption and desorption. Methyl groups substituted adjacent to the amine were found to increase solution absorption capacities but with an overall reduction in absorption rate. Poor absorption rates at low CO 2 levels and precipitation problems would prevent the α-dimethylamines examined from being used in existing submarine scrubbers. These amines, however, show potential as replacements in industrial CO 2 scrubbing processes.

Addresses the problem of stabilizing a class of nonlinear systems by using an H/sub /spl infin// fuzzy output feedback controller. First, a class of nonlinear systems is approximated by a Takagi-Sugeno (TS) fuzzy model. Then, based on a well-known Lyapunov functional approach, we develop a technique for designing an H/sub /spl infin// fuzzy output feedback control law which guarantees the L/sub 2/ gain from an exogenous input to a regulated output is less or equal to a prescribed value. A design algorithm for constructing an H/sub /spl infin// fuzzy output feedback controller is given. In contrast to the existing results, the premise variables of the H/sub /spl infin// fuzzy output feedback controller are not necessarily to be the same as the premise variables of the TS fuzzy model of the plant. A numerical simulation example is presented to illustrate the theory development.

Abstract A range of probiotic and other intestinal bacteria were examined for their ability to ferment the dietary fibre carbohydrates β‐glucan, xylan, xylo‐oligosaccharides (XOS) and arabinoxylan. β‐Glucan was fermented by Bacteroides spp and Clostridium beijerinckii but was not fermented by lactobacilli, bifidobacteria, enterococci or Escherichia coli . Unsubstituted xylan was not fermented by any of the probiotic bacteria examined. However, many Bifidobacterium species and Lactobacillus brevis were able to grow to high yields using XOS. XOS were also efficiently fermented by some Bacteroides isolates but not by E coli , enterococci, Clostridium difficile, Clostridium perfringens or by the majority of intestinal Lactobacillus species examined. Bifidobacterium longum strains were able to grow well using arabinoxylan as the sole carbon source. These organisms hydrolysed and fermented the arabinosyl residues from arabinoxylan but did not substantially utilise the xylan backbone of the polysaccharide. Arabinoxylan was not fermented by lactobacilli, enterococci, E coli, C perfringens or C difficile and has potential to be an applicable carbohydrate to complement probiotic Bif longum strains in synbiotic combinations. © 2002 Society of Chemical Industry

This paper provides a detailed overview of the Digital Video Broadcasting Terrestrial (DVB-T) signal structure and the implications for passive radar systems that use these signals as illuminators of opportunity. In particular, we analyze the ambiguity function and explain its delay and Doppler properties in terms of the underlying structure of the DVB-T signal. Of particular concern for radar range-Doppler processing are ambiguities consistent in range and Doppler with targets of interest. In this paper we adopt a mismatched filtering approach for range-Doppler processing. We also recognize that while the structure of the DVB-T signal introduces ambiguities, the structure can also be exploited to better estimate the transmitted signal and channel, as well as any mismatch between transmitter and receiver (e.g., clock offsets). This study presents a scheme for pre-processing both the reference and surveillance signals obtained by the passive radar to mitigate the effects of the ambiguities and the clutter in range-Doppler processing. The effectiveness of our proposed scheme in enhancing target detection is demonstrated using real-world data from an (Australian) 8k-mode DVB-T system. A 29 dB reduction in residual ambiguity levels over existing techniques is observed, and a 36 dB reduction over standard matched filtering; with only a 1 dB reduction in the zero-delay, zero-Doppler peak.

The Z-scan technique is a popular method for measuring degenerate (single frequency) optical nonlinearities using a single laser beam. In order to perform reliable measurements, it is necessary to carefully characterize and control a number of experimental parameters, such as the beam quality, the power and temporal characteristics of the laser, the collection aperture size and position, the sample reflectivity, sample thickness and imperfections in the sample. Failure to control these parameters leads to inaccurate determinations of the nonlinearities. In this paper, we review the theory of Z-scan and examine each of these issues from experimental and theoretical viewpoints. This work will be of interest to anyone who performs Z-scan experiments and to those interested in optical power limiting and nonlinear optical propagation.

Bernoulli filters are a class of exact Bayesian filters for non-linear/non-Gaussian recursive estimation of dynamic systems, recently emerged from the random set theoretical framework. The common feature of Bernoulli filters is that they are designed for stochastic dynamic systems which randomly switch on and off. The applications are primarily in target tracking, where the switching process models target appearance or disappearance from the surveillance volume. The concept, however, is applicable to a range of dynamic phenomena, such as epidemics, pollution, social trends, etc. Bernoulli filters in general have no analytic solution and are implemented as particle filters or Gaussian sum filters. This tutorial paper reviews the theory of Bernoulli filters as well as their implementation for different measurement models. The theory is backed up by applications in sensor networks, bearings-only tracking, passive radar/sonar surveillance, visual tracking, monitoring/prediction of an epidemic and tracking using natural language statements. More advanced topics of smoothing, multi-target detection/tracking, parameter estimation and sensor control are briefly reviewed with pointers for further reading.

Nature provides many examples of mechanisms to control fouling. These defences can be copied (biomimetic) or tailored (bioinspired) to solve problems of fouling on manmade structures. With increasing research in this area over the last two decades, it is timely to review this burgeoning subject, in particular as the biofouling field shifts focus towards novel, physical mechanisms to prevent and control fouling. This change is being promoted by advances in nano- and micro-scale patterning as well as in a variety of nano-biotechnologies, which are transforming the translation of natural surfaces into experimental materials. In this article, research on the defence of marine organisms against fouling and the technologies they are defining is reviewed.