Robust Detection of Moving Human Target in Foliage-Penetration Environment Based on Hough Transform

Attention has been focused on the robust moving human target detection in foliage-penetration environment, which presents a formidable task in a radar system because foliage is a rich scattering environment with complex multipath propagation and time-varying clutter. Generally, multiple-bounce returns and clutter are additionally superposed to direct-scatter echoes. They obscure true target echo and lead to poor visual quality time-range image, making target detection particular difficult. Consequently, an innovative approach is proposed to suppress clutter and mitigate multipath effects. In particular, a clutter suppression technique based on range alignment is firstly applied to suppress the time-varying clutter and the instable antenna coupling. Then entropy weighted coherent integration (EWCI) algorithm is adopted to mitigate the multipath effects. In consequence, the proposed method effectively reduces the clutter and ghosting artifacts considerably. Based on the high visual quality image, the target trajectory is detected robustly and the radial velocity is estimated accurately with the Hough transform (HT). Real data used in the experimental results are provided to verify the proposed method

Foraging under Predation Risk: A test of giving-up densities with samango monkeys in South Africa

Animals frequently make a trade-off between food and safety and will sacrifice feeding effort if it means safety from predators. A forager can also vary its vigilance levels to manage predation risk. Giving-up densities (GUDs), the amount of food items left once a forager has quit an experimental food patch, have been used extensively as measures of foraging behaviour under risk of predation in a wide range of species. Vigilance also serves as an anti-predatory response to predation risk and has been the focus of a range of behavioural studies. However, very few studies have looked at these two measures together. The principal aim of this study was to determine the effect of habitat factors on the foraging behaviour of samango monkeys (Cercopithcus mitis erythrarchus) by measuring GUDs in artificial food patches and foraging behaviour, and relating this to height from the ground, canopy cover, habitat visibility and observed behaviour. The second objective was then to determine the extent to which the experimental approach matched observed behaviour in measuring primate responses to predation risk. The monkeys revealed lower GUDs with increasing height and with decreasing canopy cover and but were not affected by habitat visibility. Vigilance varied considerably with only conspecific and observer vigilance showing significant effects. Conspecific vigilance increased with height and decreasing canopy cover. Vigilance directed at observers increased with decreasing canopy cover. There was no effect of habitat visibility on any of the component behaviours of vigilance. The vigilance behaviour of the monkeys did not completely compliment the GUD results. The findings of this study confirm the prediction that habitat plays a key role in the foraging behaviour of samango monkeys but that vigilance is more sensitive to other factors such as sociality. Further work is required to determine the extent to which experimental approaches based on giving up densities match patterns of antipredatory behaviour recorded by observational methods

PUGTIFs: Passively user-generated thermal invariant features

Feature detection is a vital aspect of computer vision applications, but adverse environments, distance and illumination can affect the quality and repeatability of features or even prevent their identification. Invariance to these constraints would make an ideal feature attribute. Here we propose the first exploitation of consistently occurring thermal signatures generated by a moving platform, a paradigm we define as passively user-generated thermal invariant features (PUGTIFs). In this particular instance, the PUGTIF concept is applied through the use of thermal footprints that are passively and continuously user generated by heat differences, so that features are no longer dependent on the changing scene structure (as in classical approaches) but now maintain a spatial coherency and remain invariant to changes in illumination. A framework suitable for any PUGTIF has been designed consisting of three methods: first, the known footprint size is used to solve for monocular localisation and thus scale ambiguity; second, the consistent spatial pattern allows us to determine heading orientation; and third, these principles are combined in our automated thermal footprint detector (ATFD) method to achieve segmentation/feature detection. We evaluated the detection of PUGTIFs in four laboratory environments (sand, grass, grass with foliage, and carpet) and compared ATFD to typical image segmentation methods. We found that ATFD is superior to other methods while also solving for scaled monocular camera localisation and providing user heading in multiple environments

A review of the meteorological parameters which affect aerial application

The ambient wind field and temperature gradient were found to be the most important parameters. Investigation results indicated that the majority of meteorological parameters affecting dispersion were interdependent and the exact mechanism by which these factors influence the particle dispersion was largely unknown. The types and approximately ranges of instrumented capabilities for a systematic study of the significant meteorological parameters influencing aerial applications were defined. Current mathematical dispersion models were also briefly reviewed. Unfortunately, a rigorous dispersion model which could be applied to aerial application was not available

Multi-model CFAR detection in FOliage PENetrating SAR images

A multi-model approach for Constant False Alarm Ratio (CFAR) detection of vehicles through foliage in FOliage PENetrating (FOPEN) SAR images is presented. Extreme value distributions and Location Scale properties are exploited to derive an adaptive CFAR approach that is able to cope with different forest densities. Performance analysis on real data is carried out to estimate the detection and false alarm probabilities in the presence of a ground truth

Biological Control of Weeds: Theory and Practical Application

Crop Production/Industries,

Assessing handheld mobile laser scanners for forest surveys

Abstract: A handheld mobile laser scanning (HMLS) approach to forest inventory surveying allows virtual reconstructions of forest stands and extraction of key structural parameters from beneath the canopy, significantly reducing survey time when compared against static laser scan and fieldwork methods. A proof of concept test application demonstrated the ability of this technique to successfully extract diameter at breast height (DBH) and stem position compared against a concurrent terrestrial laser scan (TLS) survey. When stems with DBH > 10 cm are examined, an HMLS to TLS modelling success rate of 91% was achieved with the root mean square error (RMSE) of the DBH and stem position being 1.5 cm and 2.1 cm respectively. The HMLS approach gave a survey coverage time per surveyor of 50 m 2/min compared with 0.85 m2/min for the TLS instrument and 0.43 m2/min for the field study. This powerful tool has potential applications in forest surveying by providing much larger data sets at reduced operational costs to current survey methods. HMLS provides an efficient, cost effective, versatile forest surveying technique, which can be conducted as easily as walking through a plot, allowing much more detailed, spatially extensive survey data to be collected

A good practice guide on the sources and magnitude of uncertainty arising in the practical measurement of environmental noise

A brief introduction to measurement uncertainty, uncertainty budgets, and inter-comparison exercises (repeated measurements), is provided in Chapter 2. The procedure forformulating an uncertainty budget and evaluating magnitudes is outlined in greater detail in Chapter 3. A flow chart summarising this process, and a checklist for the identification of sources of measurement uncertainty are included at the end of the chapter. Two example measurement exercises with corresponding uncertainty budgets are presented in Chapter 4. Some of the more commonly encountered sources of measurement uncertainty are outlined in Chapter5. Where possible, information on magnitudes or pointers to where that information can be found are included. The more important sources of uncertainty are highlighted, and “good practice guidelines” provided to help the practitioner identify means of reducing their effect. Case studies illustrating some of the points made in Chapter 5,and listing of relevant guidelines and further reading are provided in the Appendices