Measurement and Analysis of Multiband Bistatic and Monostatic Radar Signatures of Wind Turbines

This paper presents the results of recent measurements taken with two radar systems to measure the simultaneous monostatic and bistatic signature of wind turbines, at S-band and X-band. Coherent monostatic and bistatic data was collected with the University College London (UCL) NetRAD 2.4 GHz radar, and the Cranfield University CW radar operating at X-band. This initial analysis shows the bistatic Doppler signature of wind turbines and informs on the key differences seen at modest bistatic angles. Polarimetric variations are also analysed via data gathered using co-polarised VV and HH and cross-polarised VH components

Biologically inspired radar and sonar target classification

Classification of targets is a key problem of modern radar and sonar systems. This is an activity carried out with great success by echolocating mammals, such as bats, that have evolved echolocation as a means of detecting, selecting and attacking prey over a period of more than 50 million years. Because they have developed a highly sophisticated capability on which they depend for their survival, it is likely that there is potentially a great deal that can be learnt from understanding how they use this capability and how this might be valuably applied to radar and sonar systems. Bat-pollinated plants and their flowers represent a very interesting class of organisms for the study of target classification as it is thought that co-evolution has shaped bat-pollinated flowers in order to ease classification by bats. In this thesis, the strategy that underpins classification of flowers by bats is investigated. An acoustic radar has been developed to collect data to perform a floral echoes analysis. Results show that there is a relative relevance of specific parts of the flower in displaying information to bats and show that there are different characteristics in the flowers' echo fingerprints, depending on age and stage of maturity, that bats might use to choose the most suitable flowers for pollination. We show that, as suggested by the oral echoes analysis, a more intelligent way to perform target classification can result in improved classification performance and, investigate biologically inspired methods and ideas that might become important tools for the study and the development of radar and sonar target classification

Reverse engineering of mandible and prosthetic framework: Effect of titanium implants in conjunction with titanium milled full arch bridge prostheses on the biomechanics of the mandible.

This study aimed at investigating the effects of titanium implants and different configurations of full-arch prostheses on the biomechanics of edentulous mandibles. Reverse engineered, composite, anisotropic, edentulous mandibles made of a poly(methylmethacrylate) core and a glass fibre reinforced outer shell were rapid prototyped and instrumented with strain gauges. Brånemark implants RP platforms in conjunction with titanium Procera one-piece or two-piece bridges were used to simulate oral rehabilitations. A lateral load through the gonion regions was used to test the biomechanical effects of the rehabilitations. In addition, strains due to misfit of the one-piece titanium bridge were compared to those produced by one-piece cast gold bridges. Milled titanium bridges had a better fit than cast gold bridges. The stress distribution in mandibular bone rehabilitated with a one-piece bridge was more perturbed than that observed with a two-piece bridge. In particular the former induced a stress concentration and stress shielding in the molar and symphysis regions, while for the latter design these stresses were strongly reduced. In conclusion, prosthetic frameworks changed the biomechanics of the mandible as a result of both their design and manufacturing technology

Pose-informed deep learning method for SAR ATR

Synthetic aperture radar (SAR) images for automatic target classification (automatic target recognition (ATR)) have attracted significant interest as they can be acquired day and night under a wide range of weather conditions. However, SAR images can be time consuming to analyse, even for experts. ATR can alleviate this burden and deep learning is an attractive solution. A new deep learning Pose-informed architecture solution, that takes into account the impact of target orientation on the SAR image as the scatterers configuration changes, is proposed. The classification is achieved in two stages. First, the orientation of the target is determined using a Hough transform and a convolutional neural network (CNN). Then, classification is achieved with a CNN specifically trained on targets with similar orientations to the target under test. The networks are trained with translation and SAR-specific data augmentation. The proposed Pose-informed deep network architecture was successfully tested on the Military Ground Target Dataset (MGTD) and the Moving and Stationary Target Acquisition and Recognition (MSTAR) datasets. Results show the proposed solution outperformed standard AlexNets on the MGTD, MSTAR extended operating condition (EOC)1, EOC2 and standard operating condition (SOC)10 datasets with a score of 99.13% on the MSTAR SOC10

The radar signature of the Wind Lens: a less disruptive wind turbine?

We study the radar signature of a new type of wind turbine, named the Wind Lens. This design includes a flanged shroud around the turbine which concentrates the wind flow past the turbine blades and hence improves the efficiency. The design also offers improved safety, and reduces acoustic noise. Furthermore, it may offer a significantly lower radar signature, which may make the design much more attractive for use in situations where conventional wind turbine designs may disturb the operation of radars. We present the results of an experimental trial, carried out in the UK, to measure the Radar Cross Section (RCS) of a 5 kW Wind Lens turbine prototype and we provide a reference database that can be used for comparing the Wind Lens RCS with that of conventional turbines. We investigate methods to further reduce the Wind Lens RCS and present the results of a time-varying Doppler analysis. Results show that the addition of a metallic mesh around the shroud obscures the rotating blades, and hence mitigates the RCS by 15 dBm2, at angles where the radar interference is highest

Editorial. Biologically-inspired radar and sonar systems

In the last century both radar and sonar active technology developed from inception to the point where high resolution images can be obtained from long ranges. The available technology can exploit Doppler effects, structural resonances, nonlinear scattering, synthetic aperture platforms, and sediment-penetrating modalities. Active sonar and radar share many common approaches, in part because of the similarities of the problems they address, both in the military and commercial research areas. Moreover, in the last two decades, research into both radar and sonar has explored biomimetic and bioinspired solutions, in recognition of the fact that whilst man-made systems have access to power and bandwidth far beyond that available to any living organism, some biological solutions have benefitted from millions of years of natural optimisation to evolve sensing capabilities and strategies and meet the challenges of survival (finding food and mates, avoiding predators, sensing and navigating to and within appropriate habitats, etc.). Problem solving for survival goes beyond the particular radiation used in sensing, covering also signal processing, detection and classification of targets, use of platforms, and strategies for deploying sensors and interpreting data. Bio-inspired approaches follow logically when the problems facing manufactured technology resemble those addressed in nature. For example, in the last 15 years the arena for sonar challenge has changed from the passive detection of large quiet nuclear submarines in the deep, relatively quiet and uncluttered waters, to minehunting by active sonar in shallow coastal waters, a problem far closer to that faced by dolphins and bats in their natural environments