Use of Pattern Classification Algorithms to Interpret Passive and Active Data Streams from a Walking-Speed Robotic Sensor Platform

In order to perform useful tasks for us, robots must have the ability to notice, recognize, and respond to objects and events in their environment. This requires the acquisition and synthesis of information from a variety of sensors. Here we investigate the performance of a number of sensor modalities in an unstructured outdoor environment, including the Microsoft Kinect, thermal infrared camera, and coffee can radar. Special attention is given to acoustic echolocation measurements of approaching vehicles, where an acoustic parametric array propagates an audible signal to the oncoming target and the Kinect microphone array records the reflected backscattered signal. Although useful information about the target is hidden inside the noisy time domain measurements, the Dynamic Wavelet Fingerprint process (DWFP) is used to create a time-frequency representation of the data. A small-dimensional feature vector is created for each measurement using an intelligent feature selection process for use in statistical pattern classification routines. Using our experimentally measured data from real vehicles at 50 m, this process is able to correctly classify vehicles into one of five classes with 94% accuracy. Fully three-dimensional simulations allow us to study the nonlinear beam propagation and interaction with real-world targets to improve classification results

Radar interferometry techniques for the study of ground subsidence phenomena: a review of practical issues through cases in Spain

Subsidence related to multiple natural and human-induced processes affects an increasing number of areas worldwide. Although this phenomenon may involve surface deformation with 3D displacement components, negative vertical movement, either progressive or episodic, tends to dominate. Over the last decades, differential SAR interferometry (DInSAR) has become a very useful remote sensing tool for accurately measuring the spatial and temporal evolution of surface displacements over broad areas. This work discusses the main advantages and limitations of addressing active subsidence phenomena by means of DInSAR techniques from an end-user point of view. Special attention is paid to the spatial and temporal resolution, the precision of the measurements, and the usefulness of the data. The presented analysis is focused on DInSAR results exploitation of various ground subsidence phenomena (groundwater withdrawal, soil compaction, mining subsidence, evaporite dissolution subsidence, and volcanic deformation) with different displacement patterns in a selection of subsidence areas in Spain. Finally, a cost comparative study is performed for the different techniques applied.The different research areas included in this paper has been supported by the projects: CGL2005-05500-C02, CGL2008-06426-C01-01/BTE, AYA2 010-17448, IPT-2011-1234-310000, TEC-2008-06764, ACOMP/2010/082, AGL2009-08931/AGR, 2012GA-LC-036, 2003-03-4.3-I-014, CGL2006-05415, BEST-2011/225, CGL2010-16775, TEC2011-28201, 2012GA-LC-021 and the Banting Postdoctoral Fellowship to PJG

Nonlinear Acoustics and an Inverse Scattering Problem

Abstract This Ph.D is concerned with wave propagation problems. The main focus is on nonlinear acoustics, looking at sonic boom propagation in a physically realistic atmosphere, whilst a secondary part will look at the problem of landmine detection and how to improve the target detection rates. The work on nonlinear acoustics emerged as a desire to model the behaviour of the sonic booms formed by supersonic aircraft in the atmosphere to see what environmental impact they would have on people and animals on the ground, in terms of the form of the sound waves once they reach the ground. The work on landmine detection originated from a Knowledge Transfer Partner- ship between the University of East Anglia (UEA) and Cobham Technical Services (CTS) organised through the Knowledge Transfer Network (KTN). This partnership took the form of a six month internship with work undertaken afterwards to publish the �ndings of the internship.