Department Publications

Simple expressions for the symbol error rate of some coherent and noncoherent modulation schemes with dual maximal ratio combining operating in identically distributed correlated Nakagami-q fading are derived. The new expressions are derived based on a decorrelation transformation applied to the correlated branches. New expressions are given as both closed-form and finite range single integrals of elementary mathematical functions, which can be easily evaluated using mathematical software.

This paper analyzes the performance of an Extended Kalman Filter (EKF) based attitude estimator for a Quad Rotor Unmanned Aerial Vehicle (QRUAV). A non-linear dynamic model of the QRUAV, simulated in Matlab was complemented with an EKF based attitude estimator. The estimator fuses measurements obtained from simulated accelerometers and gyroscopes onboard the QRUAV. It is then shown that this estimator only results in adequate representation of the attitude when the translational velocity is large. This behavior is explained considering the dynamics of the vehicle and the onboard accelerometers. Also a possible method of exploiting this behavior for improving the estimation accuracy is suggested.

Novel single integral representations for the multivariate probability density function and cumulative distribution function of Rayleigh and Rician distributions are derived. A generalized correlation structure is used in this analysis. The derived novel representations are used to evaluate the outage probability of N-branch selection diversity operating in correlated Rayleigh and Rician fading channels modeled by the generalized correlation model.

In elephant management and conservation, it is vital to have non-invasive methods to track elephants. Image based recognition is a non-invasive mechanism for elephant tracking, albeit the inefficiency in manual method due to difficulties in handling large amount of data from multiple sources. To mitigate the drawbacks in manual method, we have proposed a computer vision based, automated, elephant recognition mechanism, which mainly relies on appearance based recognition algorithms. We have tested feasibility of the system running on a web based interface, which can facilitate researchers and conservationists all around the world to actively participate in elephant conservation.

This paper discusses the challenges faced and lessons learned during the management of an online educational network in Sri Lanka. In all aspects of learning, technology can make a significant impact. Technology, when used appropriately, can be very effective in terms of interactivity among learners, between learners and the content and between learners and teachers, especially in contrast to print-based traditional distance education. Most difficulties that arise are due to constraints of scale, time and space and can be effectively addressed using technology. When implemented effectively, learners, teachers and educational institutions all benefit. Opportunities created in such a context for a country like Sri Lanka are enormous. At the same time, any failure to access teaching/learning material can create a very negative impression and is instantly compared with the face-to-face learning environment. Managing Information and Communication

Network traffic has been shown on numerous occasions to be self similar under normal conditions. This self similar property is however, lost during anomalous conditions such as device failure, congestion and malicious intrusions. Therefore, this loss of self similarity can be used to detect such events. The Hurst parameter (H) is the most widely accepted parameter for determining self similarity. However, an accurate estimate is data and computationally expensive. This paper discusses the potential of using efficient classifier and soft computing based approaches for determining self similarity. Traffic data is obtained for various user activities from genuine browsing to malicious attacks. This data is then analysed for self similarity. The logarithmic normalized histogram of the packet interarrival time is used to obtain a feature set for classification. Various techniques are used to analyse and reduce the feature set …

The next generation of radio telescopes requires unprecedented levels of sensitivity, resolution, and field of view (FOV) that cannot be achieved with current radio telescopes. Radio astronomers and scientist are working on the development of next generation telescope designs, such as the square kilometre array (SKA)[1]. Depending on the observations, the signals of interest (SOIs) in the next generation of radio telescopes, such as the SKA, may span at least a decade of temporal frequency and are therefore broadband (BB). Moreover, the requirement of unprecedented levels of sensitivity makes radio frequency interference (RFI) a major problem. In achieving the science specifications, two emerging synthetic aperture applications of dense phased arrays are being considered [2],[3] for the so-called mid-frequency range from about 0.3-2 GHz: they are, rectangular dense aperture arrays (DAAs)(as in Fig. 1 (a)) and/or focal plane arrays (FPAs) in the focal plane of paraboloidal dishes (as in Fig. 1 (b)). Previously reported works on the mitigation of RFIs are based on temporal blanking techniques which are mostly suitable for intermittent RFI [2], on spatial filtering techniques which use subspace-projection methods [3]-[5], on cancellation techniques which use a reference signal approach [6], and on post-correlation cancellation and anti-coincidence techniques [7]. Such methods are mostly being investigated in the context of narrowband applications. However, for next generation synthetic aperture systems, such as the SKA, the SOIs are inherently BB and therefore it is an interesting possibility to consider a suitable BB approach capable for …

A framework to support creation of location based services (LBS) applications using map services is designed and implemented. It provides a means to develop interoperable LBS applications which are independent of service provider, device or data providers. Application developers can use the framework to utilize multiple map servers following Web Map Service (WMS) and Web Feature Service (WFS) standards in creating the LBS applications. Mobile phone users can access the applications created by the framework through mobile Internet. A cascading map server and a application database is used at the application server. The LBS applications developed by the framework can provide directory assistance services on wide spectrum of mobile phones ranging from mid-range to smart phones. Thus many LBSs which have hitherto been denied to mid-range phones are made possible, exploiting their available …

In order to obtain depth perception in computer vision, it is needed to process pairs of stereo images. This process is computationally challenging to be carried out in real-time, because it requires the search for matches between objects in both images. Such process is significantly simplified if the images are rectified. Stereo image rectification involves a matrix transformation which when done in software will not produce real-time results although it is very demanding. Therefore, the video streaming and matrix transformation are not usually implemented in the same system. Our product is a stereo camera pair which produces a rectified real time image output with a resolution of 320×240 at a frame rate of 15FPS and delivers them via a 100-Ethernet interface. We use a Spartan 3E FPGA for real-time processing within which we implement an image rectification algorithm.

Novel simple forms for the probability density function (PDF) and the cumulative distribution function (CDF) of two correlated Rician random variables (RVs) are derived. The new representations for the bivariate Rician PDF and CDF are given in the form of single integral solutions in terms of well known functions that are available in common mathematical software packages. The general case of non-identically distributed Rician RVs is considered in this analysis. The new form of the bivariate Rician cumulative distribution function is applied to give a new expression for the outage probability of dual selection combining diversity operating in correlated Rician fading.

Position estimation using wheel odometric systems tends to give rather poor performances for an outdoor four-wheel skid steered mobile robot. Therefore autonomous control of these vehicles is extremely challenging in outdoor environments. This paper describes an outdoor localization system based on visual odometry for skid steered vehicle using forward faced camera and a downward faced camera. Optical flow field data is statistically analyzed to correctly estimate the position of the robot. Kalman Filtering is used to fuse data from two cameras for optimum performance. Also real-time Instantaneous Center of Rotation (ICR) detection using optical flow field data is proposed to calculate the heading angle. Two consumer grade cameras were used and algorithm was tested using open source image processing libraries. The proposed system yielded an acceptable positioning accuracy on short runs in typical …

Control the data flow between device interfaces, processing blocks and memories in a vision system is complex in hardware implementation. In the research, high-level synthesis tool is used to design, implement and test the vision system within the context of required control, synchronization, and parameterization on a processor based platform. In addition, both HLS tools and HDL were used for the development of the processing cores, and the performance of the two versions were analyzed and compared. The operational structures of benchmarked vision core consist of custom vision coprocessor with efficient memory and bus interfaces. The performance properties such as accuracy, throughput and efficiency are measured and presented. Xilinx XC5VLX110T FPGA, has been used for prototype the hardware platforms. According to results, without any complex optimizations, pipeline length and resource …

The bag of visual words model has seen immense success in addressing the problem of image classification. Algorithms using this model generate the codebook of visual words by vector quantizing the features (such as SIFT) of the images to be classified. However, a codebook so formed tends to get biased by the nature of the dataset. In this paper we propose an alternative method to create the codebook for the dataset of images to be classified. Instead of directly using the dataset itself we first create a visual word dictionary by studying the SIFT features of a universal set of images. The codebook for the images to be classified is derived from this dictionary. To assess the effectiveness of the codebook thus derived, we classify the images using Probabilistic Latent Semantic Analysis in an unsupervised setting and Naive Bayes' classification in a supervised setting. The use of a dictionary achieves results …

This paper details the development of a model for a walking tractor also known as power tiller. A complete model for power tiller is developed considering kinematics, dynamics and engine dynamics for autonomous operation. Inputs to the simulation model are left clutch control signal and right clutch control signal. Data from an Inertial Measurement Unit (IMU) attached to the power tiller enables validation of the model using analogue matching and integral least squares. The result of the validation is that the model is a suitable representation of the power tiller. Developed model is intended to use for development of a controller for the remote and autonomous operation at agricultural fields.

In this paper we first analyze the effects of least square based parameter estimation for a autoregressive stochastic model of inertial sensor errors. We then proceed to develop the recursive least squares (RLS) estimation of the autoregressive model parameters and also discuss a fast update method for recursive least square estimation to reduce the computation complexity. This reduction leads to an efficient online dynamic estimation of inertial sensor error model which can then augment a navigation system based on such sensors. Simulation results and actual inertial sensor data are analyzed and it is shown that the RLS estimate can achieve a 20% reduction in forward prediction error as compared to the non-recursive estimate.

Novel single integral representations for the multivariate probability density function (PDF) and cumulative distribution function (CDF) of the Nakagami-m distribution with integer and identical fading severity parameter m are derived. A generalized correlation structure is used in this model. The single integral solutions for the PDF and the CDF are given in terms of well known mathematical functions which are available in common mathematical software packages. The novel representation derived for multivariate CDF is used to evaluate the outage probability of N-branch selection diversity combining operating in correlated Nakagami-m fading modeled by the generalized correlation model.

This paper is about the development of a framework for the formal certification of software for masquerade detection based upon natural mimicry. A masquerade is when an intruder mimics a genuine user in order to compromise the security of a computer system. The framework consists of looking at mimicry in the natural world. Based on this, a model for mimicry is developed based on the principle of indiscernibility. This is followed by a look into the requirements for masquerade detection software. A formal model for an agent for masquerade detection is then derived which discerns the static attributes of the user as well as detects anomalies in the dynamic user behavior via a statistical classifier. This agent is then used for masquerade detection in the Human Machine Interface (HMI) of an industrial automation network.

Research in the areas of localization, mapping and path planning for single mobile robots has been carried out extensively. Nevertheless, relatively little of its work is applied to multiple robot systems. Moreover, when these robots coexist with human, complex and unpredictable human environments make the above navigational tasks even more challenging. To address this problem we propose intelligent assistance, a novel scheme to assist mobile robots by providing localization information externally. This scheme aims to combine the research fields of autonomous mobile robot navigation and target tracking. The mobile robots are detected using a laser range finder and camera based sensor unit. Using Rao-Blackwellized particle filter technique, the sensory information is integrated in a probabilistic manner and the mobile robots that need assistance are continuously tracked. We maneuver the non-holonomic …

We present an effective solution for both digital map generation and real time user tracking for teams operating in hazardous environments or unfamiliar territory. The system is based on the client server model, where the client is a GPS enabled mobile phone which is capable of capturing coordinates and serving dynamic maps to the user. The maps plot the team's navigational routes and enables real time tracking of each other. The server builds a GIS at the back end based on the data sent by the users, and also develops maps on demand. The system is implemented with simple hardware and uses the available GPRS network for data gathering. This enables the system to be used both in hazardous environments and by the general public.

Novel single integral representations for the multivariate probability density function (PDF) and cumulative distribution function (CDF) of Gaussian class Weibull distributions are derived. A special linear transformation of independent Gaussian random variables is used to generate correlated Weibull random variables. The solutions are expressed in terms of familiar functions which are available in common mathematical software. The well known equal (constant) correlation model is used in this paper. The advantage of the new representation is that only a single integral computation is needed to compute a L-dimensional distribution. Some applications of the new distribution representations are also given.

Multivariate statistics play an important role in performance analysis of wireless communication systems in correlated fading channels. This thesis presents a framework which can be used to derive easily computable mathematical representations for some multivariate statistical distributions, which are derivatives of the Gaussian distribution, and which have a particular correlation structure. The new multivariate distribution representations are given as single integral solutions of familiar mathematical functions which can be evaluated using common mathematical software packages. The new approach can be used to obtain single integral representations for the multivariate probability density function, cumulative distribution function, and joint moments of some widely used statistical distributions in wireless communication theory, under an assumed correlation structure. The remarkable advantage of the new …

Analysis of fertile material such as flowers and fruit is a key factor in the proper identification of plant species. Despite object recognition being a mature research area, the use of it in automated plant identification is still relatively new. This paper describes a novel method of detecting fertile material in plant images using rectangular features. Rectangular features are obtained for the grayscale image, the J value image, the magnitude and angle of the gradient of the image. From these, the features with the best performance are selected based on their ability to detect fertile material (flowers) and non-fertile material (leaves). Based on performance, the rectangular features of the grayscale image and J value image are used. Multiple Support Vector Machine (SVM) classifiers with different kernels are tested and the final result is obtained using classifier voting based on the confidence of each classifier. After applying the …

Real-time scanned-array direct-form-I hardware implementations of two-dimensional (2D) infinite impulse response (IIR) frequency-planar beam plane-wave (PW) filters have potentially wide applications in the directional enhancement of spatio-temporal broadband PWs based on their directions of arrival (DOAs). The proposed prototypes consist of a microphone sensor array, low-noise-amplifiers (LNAs), multiplexers (MUXs), a programmable gain amplifier (PGA), an analog to digital converter (ADC), a digital to analog converter (DAC), and a field programmable gate array (FPGA) circuit based 2D IIR spatio-temporal beam filter implemented on a single Xilinx Virtex2P xc2vp30-7ff896 FPGA chip. Starting from published 1 st -order designs, novel FPGA architectures for highly-selective 2 nd - and 3 rd -order beam PW filters are proposed, simulated, implemented on FPGA, and verified on-chip.

Industrial automation is undergoing an increased use of wireless networks due to high flexibility and ease of deployment. However, despite the benefits, wireless networks have their inherent problems and vulnerabilities. This paper investigates the feasibility of using anomaly detection using possibility theory for network traffic. This is then used as a lightweight hostbased intrusion detection system for single board computer or embedded devices of an IEEE 802.11 based wireless industrial automation network. Traffic data is collected for genuine browsing and simulated attacks. It is then subjected to cluster analysis and tested using standard classifiers. The logarithmic histogram of the interpacket delay is used as the feature for classification. Subsequently it is used for training and testing a possiblisitic anomaly detector. The performance is then compared with a statistical outlier detector.

Monitoring the ECG (Electrocardiogram) of patients with cardiac disorder is of paramount importance since they may undergo cardiac arrhythmias even without noticing it. Majority of existing devices for this purpose are only capable of recording ECG of patients which are analyzed later on by cardiologists. This paper presents a new system developed to continuously monitor the ECG of patients and analyze them in real time to identify any abnormalities. The new system consists of two parts: a portable device worn by the patient and a server side component. The arrhythmia detection algorithm used in the portable device shows 99.78% sensitivity, 99.65% positive predictivity for QRS complex detection and 93.48% sensitivity, 96.45% positive predictivity for ventricular beat classification when evaluated on MIT-BIH arrhythmia database. When an arrhythmia is detected the device automatically uploads the ECG data in …