Localisation of an Unknown Number of Land Mines Using a Network of Vapour Detectors

We consider the problem of localising an unknown number of land mines using concentration information provided by a wireless sensor network. A number of vapour sensors/detectors, deployed in the region of interest, are able to detect the concentration of the explosive vapours, emanating from buried land mines. The collected data is communicated to a fusion centre. Using a model for the transport of the explosive chemicals in the air, we determine the unknown number of sources using a Principal Component Analysis (PCA)-based technique. We also formulate the inverse problem of determining the positions and emission rates of the land mines using concentration measurements provided by the wireless sensor network. We present a solution for this problem based on a probabilistic Bayesian technique using a Markov chain Monte Carlo sampling scheme, and we compare it to the least squares optimisation approach. Experiments conducted on simulated data show the effectiveness of the proposed approach

Guidebook on Detection Technologies and Systems for Humanitarian Demining

The aim of this publication is to provide the mine action community, and those supporting mine action, with a consolidated review and status summary of detection technologies that could be applied to humanitarian demining operations. This Guidebook is meant to provide information to a wide variety of readers. For those not familiar with the spectrum of technologies being considered for the detection of landmines and for area reduction, there is a brief overview of the principle of operation for each technology as well as a summary listing of the strengths, limitations, and potential for use of the technology to humanitarian demining. For those with an intermediate level of understanding for detection technologies, there is information regarding some of the more technical details of the system to give an expanded overview of the principles involved and hardware development that has taken place. Where possible, technical specifications for the systems are provided. For those requiring more information for a particular system, relevant publications lists and contact information are also provided

Technology for humanitarian landmine clearance

This thesis examines the technology used for tools and equipment for humanitarian landmine clearance. The main focus is on the removal of mine and unxeploded ordnance contamination in the poor, heavily mined countries, particularly Afghanistan and Cambodia. Initially, the process of humanitarian demining in these countries was examined and described, and the relevant literature reviewed. Three studies were undertaken with a dual purpose of (a) providing relevant contributions to the science of mine clearance and (b) evaluating some of the methods commonly used in humanitarian demining research. (i) A statistical analysis of the evaluation of mine detection systems in trials was undertaken. This demonstrated that (a) this statistical analysis is straightforward, and (b) feasible sized trials do not yield useful results from analysis of the crude minedetection rate. An enhancement to the evaluation process, "Margin of Detection," was suggested. (ii) Research into improved "prodders" for detecting mines was undertaken with as much consultation with deminers as possible early in the research cycle. "Sensing prodders" were shown to function technically but not to improve the overall demining process. Measurements showed that many deminers prod in hard soils with suÆcient force to detonate some mines; rotary prodders were developed to reduce the force required for excavation, but success in the laboratory could not be duplicated in eld conditions. From this work a potentially useful tool for deminer training was developed, which might reduce the risks of accidental detonation. (iii) The limits of a high-tech detection technique (neutron irradiation and detection of prompt gamma rays) were examined (a) to advance understanding of this method and (b) to demonstrate the feasibility of early evaluation of technologies before extensive research is started. This neutron technology was shown to oer potential benets to military demining, but to be unlikely to have general application when the higher clearance standards and lower equipment budgets of humanitarian demining were applied. The thesis ends with conclusions and suggestions for some further work. Throughout the thesis, the research is focussed on investigating practical problems which deminers have suggested as important constraints on their work

The Humanitarian and Developmental Impact of Anti-Vehicle Mines

Anti-vehicle mines (AVMs) have always had a humanitarian impact, but their significance has often been overshadowed by the higher-profile topic of anti-personnel mines (APMs), and thus the need to address AVMs has been neglected. In some countries, AVMs now present a greater threat to civilian populations than APMs, yet they are often viewed as a marginal issue in international fora. This publication seeks to depict the physical, social, economic and developmental impact of AVMs. AVMs are landmines designed to be triggered by vehicles rather than individual people. They can remain active for decades, and a number of them are difficult to detect with normal demining equipment and techniques. A reduction of the duration of the active life of AVMs, restrictions on the laying of AVMs outside perimeter marked areas, increased detectability and accurate recordkeeping should be promoted as immediate steps to limit the humanitarian and developmental impact of these weapons

Scale-Wavelength Decomposition of Hyperspectral Signals - Use for Mineral Classification & Quantification

An approach for material identification & soil constituent quantification based on a generalized multi-scale derivative analysis of hyperspectral signals is presented. It employs the continuous wavelet transform to project input spectra onto a scale-wavelength space. This allows investigating the spectra at selectable level of detail while normalizing/separating disturbances. Benefits & challenges of this decomposition for mineral classification & quantification will be shown for a mining site

Development of an unsupervised remote sensing methodology of detect surface leakage from terrestrial CO2 storage sites

Imperial Users onl

Automated techniques for bat echolocation call analysis

Acoustic bat detectors are an extraordinarily valuable tool in bat research as they enable researchers to listen in on the otherwise secretive world of bats, providing the means to nqn-invasively survey and monitor bats in their natural habitats. Technological advances facilitate unprecedented data collection, considerably expanding the scope of field studies. However, the burden of manual analysis, and difficulty in identifying some species reliably from their calls, hampers the development of systematic survey and long- term monitoring methods. We developed a series of algorithms for the automated analysis of bat detector recordings, used to detect and extract calls from continuous recordings, and measure temporal and spectral call variables. By hand-labelling the .location of calls in field recordings, we were able to evaluate the accuracy of the automated method at detecting calls. Comparison on the same dataset with two conventional bioacoustic signal detectors revealed our algorithm was more accurate and robust. Using machine learning (ML) classification algorithms that learn to identify calls following training using a reference library, we developed a fully automated species identification system. Evaluation of the system was carried out by cross-validation of our reference call library, containing recordings of >5000 calls from known British species, comparing classifier predictions to ground- truth labels. The ML approach outperformed conventional statistical analysis using discriminant function analysis (DFA). We applied our novel system to two field studies that highlight its utility. Firstly, monitoring multi- species bat activity at a remote cave system over a period of three months, analysing >20,000 audio files to investigate temporal patterns in activity. Secondly, separating acoustically cryptic Myotis species from data collected in the Lake District National Park, to generate presence data for species distribution modelling, facilitatinq the creation of species-specific habitat suitability maps projected over the entire Park (ea, 3,300 km")