Multi-sensor tracking using a scalable condensation filter

Surveillance and tracking systems typically use a single colour modality for their input. These systems work well in controlled conditions but often fail with low lighting, shadowing, smoke, dust, unstable backgrounds or when the foreground object is of similar colouring to the background. With advances in technology and manufacturing techniques, sensors that allow us to see into the thermal infrared spectrum are becoming more affordable. By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using visible light only for surveillance and tracking. Thermal images are not affected by lighting or shadowing and are not overtly affected by smoke, dust or unstable backgrounds. We propose and evaluate three approaches for fusing visual and thermal images for person tracking. We also propose a modified condensation filter to track and aid in the fusion of the modalities. We compare the proposed fusion schemes with using the visual and thermal domains on their own, and demonstrate that significant improvements can be achieved by using multiple modalities.

Object tracking using multiple motion modalities

This paper presents an object tracking system that utilises a hybrid multi-layer motion segmentation and optical flow algorithm. While many tracking systems seek to combine multiple modalities such as motion and depth or multiple inputs within a fusion system to improve tracking robustness, current systems have avoided the combination of motion and optical flow. This combination allows the use of multiple modes within the object detection stage. Consequently, different categories of objects, within motion or stationary, can be effectively detected utilising either optical flow, static foreground or active foreground information. The proposed system is evaluated using the ETISEO database and evaluation metrics and compared to a baseline system utilising a single mode foreground segmentation technique. Results demonstrate a significant improvement in tracking results can be made through the incorporation of the additional motion information.

Scene invariant crowd counting for real-time surveillance

Automated crowd counting allows excessive crowding to be detected immediately, without the need for constant human surveillance. Current crowd counting systems are location specific, and for these systems to function properly they must be trained on a large amount of data specific to the target location. As such, configuring multiple systems to use is a tedious and time consuming exercise. We propose a scene invariant crowd counting system which can easily be deployed at a different location to where it was trained. This is achieved using a global scaling factor to relate crowd sizes from one scene to another. We demonstrate that a crowd counting system trained at one viewpoint can achieve a correct classification rate of 90% at a different viewpoint.

Wireless channel modelling for indoor populated environments : statistical characterization of narrowband channels at 2.45 Ghz and 5.2 Ghz

The recent development of indoor wireless local area network (WLAN) standards at 2.45 GHz and 5 GHz has led to increased interest in propagation studies at these frequency bands. Within the indoor environment, human body effects can strongly reduce the quality of wireless communication systems. Human body effects can cause temporal variations and shadowing due to pedestrian movement and antenna- body interaction with portable terminals. This book presents a statistical characterisation, based on measurements, of human body effects on indoor narrowband channels at 2.45 GHz and at 5.2 GHz. A novel cumulative distribution function (CDF) that models the 5 GHz narrowband channel in populated indoor environments is proposed. This novel CDF describes the received envelope in terms of pedestrian traffic. In addition, a novel channel model for the populated indoor environment is proposed for the Multiple-Input Multiple-Output (MIMO) narrowband channel in presence of pedestrians at 2.45 GHz. Results suggest that practical MIMO systems must be sufficiently adaptive if they are to benefit from the capacity enhancement caused by pedestrian movement.

Peak-to-average power ratio of IEEE 802.11a PHY layer signals

In this chapter we propose clipping with amplitude and phase corrections to reduce the peak-to-average power ratio (PAR) of orthogonal frequency division multiplexed (OFDM) signals in high-speed wireless local area networks defined in IEEE 802.11a physical layer. The proposed techniques can be implemented with a small modification at the transmitter and the receiver remains standard compliant. PAR reduction as much as 4dB can be achieved by selecting a suitable clipping ratio and a correction factor depending on the constellation used. Out of band noise (OBN) is also reduced.

Interleaved PC-OFDM to reduce peak-to-average power ratio

Parallel combinatory orthogonal frequency division multiplexing (PC-OFDM yields lower maximum peak-to-average power ratio (PAR), high bandwidth efficiency and lower bit error rate (BER) on Gaussian channels compared to OFDM systems. However, PC-OFDM does not improve the statistics of PAR significantly. In this chapter, the use of a set of fixed permutations to improve the statistics of the PAR of a PC-OFDM signal is presented. For this technique, interleavers are used to produce K-1 permuted sequences from the same information sequence. The sequence with the lowest PAR, among K sequences is chosen for the transmission. The PAR of a PC-OFDM signal can be further reduced by 3-4 dB by this technique. Mathematical expressions for the complementary cumulative density function (CCDF)of PAR of PC-OFDM signal and interleaved PC-OFDM signal are also presented.

Adaptive instantaneous frequency estimation: Techniques and algorithms

This thesis deals with the problem of the instantaneous frequency (IF) estimation of sinusoidal signals. This topic plays significant role in signal processing and communications. Depending on the type of the signal, two major approaches are considered. For IF estimation of single-tone or digitally-modulated sinusoidal signals (like frequency shift keying signals) the approach of digital phase-locked loops (DPLLs) is considered, and this is Part-I of this thesis. For FM signals the approach of time-frequency analysis is considered, and this is Part-II of the thesis. In part-I we have utilized sinusoidal DPLLs with non-uniform sampling scheme as this type is widely used in communication systems. The digital tanlock loop (DTL) has introduced significant advantages over other existing DPLLs. In the last 10 years many efforts have been made to improve DTL performance. However, this loop and all of its modifications utilizes Hilbert transformer (HT) to produce a signal-independent 90-degree phase-shifted version of the input signal. Hilbert transformer can be realized approximately using a finite impulse response (FIR) digital filter. This realization introduces further complexity in the loop in addition to approximations and frequency limitations on the input signal. We have tried to avoid practical difficulties associated with the conventional tanlock scheme while keeping its advantages. A time-delay is utilized in the tanlock scheme of DTL to produce a signal-dependent phase shift. This gave rise to the time-delay digital tanlock loop (TDTL). Fixed point theorems are used to analyze the behavior of the new loop. As such TDTL combines the two major approaches in DPLLs: the non-linear approach of sinusoidal DPLL based on fixed point analysis, and the linear tanlock approach based on the arctan phase detection. TDTL preserves the main advantages of the DTL despite its reduced structure. An application of TDTL in FSK demodulation is also considered. This idea of replacing HT by a time-delay may be of interest in other signal processing systems. Hence we have analyzed and compared the behaviors of the HT and the time-delay in the presence of additive Gaussian noise. Based on the above analysis, the behavior of the first and second-order TDTLs has been analyzed in additive Gaussian noise. Since DPLLs need time for locking, they are normally not efficient in tracking the continuously changing frequencies of non-stationary signals, i.e. signals with time-varying spectra. Nonstationary signals are of importance in synthetic and real life applications. An example is the frequency-modulated (FM) signals widely used in communication systems. Part-II of this thesis is dedicated for the IF estimation of non-stationary signals. For such signals the classical spectral techniques break down, due to the time-varying nature of their spectra, and more advanced techniques should be utilized. For the purpose of instantaneous frequency estimation of non-stationary signals there are two major approaches: parametric and non-parametric. We chose the non-parametric approach which is based on time-frequency analysis. This approach is computationally less expensive and more effective in dealing with multicomponent signals, which are the main aim of this part of the thesis. A time-frequency distribution (TFD) of a signal is a two-dimensional transformation of the signal to the time-frequency domain. Multicomponent signals can be identified by multiple energy peaks in the time-frequency domain. Many real life and synthetic signals are of multicomponent nature and there is little in the literature concerning IF estimation of such signals. This is why we have concentrated on multicomponent signals in Part-H. An adaptive algorithm for IF estimation using the quadratic time-frequency distributions has been analyzed. A class of time-frequency distributions that are more suitable for this purpose has been proposed. The kernels of this class are time-only or one-dimensional, rather than the time-lag (two-dimensional) kernels. Hence this class has been named as the T -class. If the parameters of these TFDs are properly chosen, they are more efficient than the existing fixed-kernel TFDs in terms of resolution (energy concentration around the IF) and artifacts reduction. The T-distributions has been used in the IF adaptive algorithm and proved to be efficient in tracking rapidly changing frequencies. They also enables direct amplitude estimation for the components of a multicomponent

Numerical modelling of industrial microwave heating

The numerical modelling of electromagnetic waves has been the focus of many research areas in the past. Some specific applications of electromagnetic wave scattering are in the fields of Microwave Heating and Radar Communication Systems. The equations that govern the fundamental behaviour of electromagnetic wave propagation in waveguides and cavities are the Maxwell's equations. In the literature, a number of methods have been employed to solve these equations. Of these methods, the classical Finite-Difference Time-Domain scheme, which uses a staggered time and space discretisation, is the most well known and widely used. However, it is complicated to implement this method on an irregular computational domain using an unstructured mesh. In this work, a coupled method is introduced for the solution of Maxwell's equations. It is proposed that the free-space component of the solution is computed in the time domain, whilst the load is resolved using the frequency dependent electric field Helmholtz equation. This methodology results in a timefrequency domain hybrid scheme. For the Helmholtz equation, boundary conditions are generated from the time dependent free-space solutions. The boundary information is mapped into the frequency domain using the Discrete Fourier Transform. The solution for the electric field components is obtained by solving a sparse-complex system of linear equations. The hybrid method has been tested for both waveguide and cavity configurations. Numerical tests performed on waveguides and cavities for inhomogeneous lossy materials highlight the accuracy and computational efficiency of the newly proposed hybrid computational electromagnetic strategy.

Secure tracking for critical applications : communications, GPS and future Galileo services

Tracking/remote monitoring systems using GNSS are a proven method to enhance the safety and security of personnel and vehicles carrying precious or hazardous cargo. While GNSS tracking appears to mitigate some of these threats, if not adequately secured, it can be a double-edged sword allowing adversaries to obtain sensitive shipment and vehicle position data to better coordinate their attacks, and to provide a false sense of security to monitoring centers. Tracking systems must be designed with the ability to perform route-compliance and thwart attacks ranging from low-level attacks such as the cutting of antenna cables to medium and high-level attacks involving radio jamming and signal / data-level simulation, especially where the goods transported have a potentially high value to terrorists. This paper discusses the use of GNSS in critical tracking applications, addressing the mitigation of GNSS security issues, augmentation systems and communication systems in order to provide highly robust and survivable tracking systems.

An enhanced explicit rate algorithm for ABR traffic control in ATM networks

A high performance, low computational complexity rate-based flow control algorithm which can avoid congestion and achieve fairness is important to ATM available bit rate service. The explicit rate allocation algorithm proposed by Kalampoukas et al. is designed to achieve max–min fairness in ATM networks. It has several attractive features, such as a fixed computational complexity of O(1) and the guaranteed convergence to max–min fairness. In this paper, certain drawbacks of the algorithm, such as the severe overload of an outgoing link during transient period and the non-conforming use of the current cell rate field in a resource management cell, have been identified and analysed; a new algorithm which overcomes these drawbacks is proposed. The proposed algorithm simplifies the rate computation as well. Compared with Kalampoukas's algorithm, it has better performance in terms of congestion avoidance and smoothness of rate allocation.

Distributed orthogonal space-time block codes with adaptive diversity gain

In this paper we present a novel distributed coding protocol for multi-user cooperative networks. The proposed distributed coding protocol exploits the existing orthogonal space-time block codes to achieve higher diversity gain by repeating the code across time and space (available relay nodes). The achievable diversity gain depends on the number of relay nodes that can fully decode the signal from the source. These relay nodes then form space-time codes to cooperatively relay to the destination using number of time slots. However, the improved diversity gain is archived at the expense of the transmission rate. The design principles of the proposed space-time distributed code and the issues related to transmission rate and diversity trade off is discussed in detail. We show that the proposed distributed space-time coding protocol out performs existing distributed codes with a variable transmission rate.

An investigation of consumer acceptance of M-banking

This paper aims to identify and test the key motivators and inhibitors for consumer acceptance of mobile phone banking (M-banking), particularly those that affect the consumer’s attitude towards, and intention to use, this self-service banking technology. A web-based survey was undertaken where respondents completed a questionnaire about their perceptions of M-banking’s ease of use, usefulness, cost, risk, compatibility with their lifestyle, and their need for interaction with personnel. Correlation and hierarchical multiple regression analysis, with Sobel tests, were used to determine whether these factors influenced consumers’ attitude and intention to use M-banking.

Paradigm shifters : tricksters and cultural science

This paper seeks to link anthropological and economic treatments of the process of innovation and change, not only within a given ‘complex system’ (e.g. a cosmology; an industry) but also between systems (e.g. cultural and economic systems; but also divine and human systems). The role of the ‘Go-Between’ is considered, both in the anthropological figure of the Trickster (Hyde 1998) and in the Schumpeterian entrepreneur. Both figures parlay appetite (economic wants) into meaning (cultural signs). Both practice a form of creativity based on deception, ‘creative destruction’; renewal by disruption and needs-must adaptation. The disciplinary purpose of the paper is to try to bridge two otherwise disconnected domains – cultural studies and evolutionary economics – by showing that the traditional methods of the humanities (e.g. anthropological, textual and historical analysis) have explanatory force in the context of economic actions and complex-system evolutionary dynamics. The objective is to understand creative innovation as a general cultural attribute rather than one restricted only to accredited experts such as artists; thus to theorise creativity as a form of emergence for dynamic adaptive systems. In this context, change is led by ‘paradigm shifters’ – tricksters and entrepreneurs who create new meanings out of the clash of difference, including the clash of mutually untranslatable communication systems (language, media, culture).

On the empirical eigenvalue distribution of slotted amplify-and-forward relaying protocol model

In this paper we consider the case of large cooperative communication systems where terminals use the protocol known as slotted amplify-and-forward protocol to aid the source in its transmission. Using the perturbation expansion methods of resolvents and large deviation techniques we obtain an expression for the Stieltjes transform of the asymptotic eigenvalue distribution of a sample covariance random matrix of the type HH† where H is the channel matrix of the transmission model for the transmission protocol we consider. We prove that the resulting expression is similar to the Stieltjes transform in its quadratic equation form for the Marcenko-Pastur distribution.

Consumers’ intentions to adopt 3G in regional cities in China : a comparative study

Rapid mobile technological evolution and the large economic stake in commercial development of mobile technological innovation make it necessary to understand consumers' motivations towards the latest advanced and updated technologies and services. 3G (the third generation of mobile communication technology) recently started its commercial development in the world‘s largest mobile communication market, China, after being delayed for a few years. Although China fell behind in commercially developing 3G, it is difficult to ignore studying this area, given the size of the market and promising future developments. This market deserves focused research attention, especially in terms of consumer behaviour towards the adoption of mobile technological innovation. Thus, the program of research in this thesis was designed to investigate how Chinese consumers respond to the use of this newly launched mobile technological innovation, with a focus on what factors affect their 3G adoption intentions. It aimed to yield important insights into Chinese consumers‘ innovation adoption behaviours and to contribute to marketing and innovation adoption research. Furthermore, it has been documented that Chinese consumers vary widely between regions in dialect, lifestyle, culture, purchasing power and consumption attitudes. Based on economic development and local culture, China can be divided geographically into distinctive regional consumer markets. Consequently, the results of consumer behaviour research in one region may not necessarily be extrapolated to other regions. In order to better understand Chinese consumers, the disparities between regions should not be overlooked. Therefore, another objective of this program of research was to examine regional variances in consumers' innovation adoption, specifically to identify the similarities and differences in factors influencing 3G adoption, contributing to intra-cultural studies. An extensive literature review identified two gaps: current China-based innovation adoption research studies are limited in providing adequate prediction and explanation of Chinese consumers' intentions to adopt 3G; and there was limited knowledge about the differences between regional Chinese consumers in innovation adoption. Two research questions therefore were developed to address these gaps: 1) What factors influence Chinese consumers' intentions to adopt 3G? 2) How do Chinese consumers differ between regional markets in the relative influence of the factors in determining their intentions to adopt 3G? In accordance with postpositivist research philosophy, two studies were designed to answer the research questions, using mixed methods. To meet the research objectives, the two studies were both conducted in three regional cities, namely Beijing, Shanghai and Wuhan, centred in the three regions of North China, East China and Central China respectively, with sufficient cultural and economical regional variances. Study One was an exploratory study with qualitative research methods. It involved 45 in-depth interviews in the three research cities to gain rich insights into the research context from natural settings. Eight important concepts related to 3G adoption were generated from analysis of the interview data, namely utilitarian expectation, hedonic expectation, status gains, status loss avoidance, normative influence, external influence, cost and quality concern. The concepts of social loss avoidance and quality concern were two unique findings, whereas the other concepts were similar to the findings in Western innovation adoption studies. Moreover, variances in 3G adoption between three groups of regional consumers were also identified, focusing on the perceptions of two concepts, namely status gains and normative influence. The conceptual research model was then developed incorporating the eight concepts plus the dependent variable of adoption intention. The hypothesized relationships between the nine constructs and hypotheses about the differences between regional consumers in 3G adoption were informed by the findings of Study One and the literature reviewed. Study Two was a quantitative study involving a web-based survey and statistical analysis procedure. The web-based survey attracted 800 residents from the three research cities, 270 from Beijing, 265 from Shanghai and 265 from Wuhan. They comprised three research samples for this study and consequently three sets of data were obtained. The data was analysed by Structural Equation Modelling together with Multi-group Analysis. The analysis confirmed that the concepts generated in Study One were influential factors affecting Chinese consumers' 3G adoption intention, with the exception of the concept external influence. Differences were found between the samples in the three research cities in the effect of hedonic expectation, status gains, status loss avoidance and normative influence on 3G adoption intention. The two Studies undertaken in this thesis contributed a better understanding of Chinese consumers' intentions to adopt advanced mobile technological innovation, namely 3G, in three regional markets. This knowledge contributes to innovation adoption and intra-cultural research, as well as consumer behaviour theory. It is also able to inform international and domestic telecommunication companies to develop and deliver more effective marketing strategies across Chinese regional markets. Limitations in the research were identified in terms of the sampling techniques used and the design of the two Studies. Future research was suggested in other Chinese regional markets and into consumer adoption of other types of mobile technological innovations.