Amplitude modulation on echoes from large birds

Torvik, Børge; Knapskog, Atle Onar; Lie-Svendsen, Øystein; Olsen, Karl Erik; Griffiths, Hugh

doi:10.1109/eurad.2014.6991236

Cited by 17 publications

(17 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To our knowledge only one group has calculated scattering from a bird model with realistic shape and material properties (Torvik et al . ). More theoretical and modelling work is clearly needed, as are field measurements of as many species as possible.…”

Section: Discussionmentioning

confidence: 99%

Quantitative ornithology with a commercial marine radar: standard‐target calibration, target detection and tracking, and measurement of echoes from individuals and flocks

Urmy

Warren

2016

Methods Ecol Evol

View full text Add to dashboard Cite

Summary Marine surveillance radars are commonly used for radar ornithology, but they are rarely calibrated. This prevents them from measuring the radar cross‐sections (RCS) of the birds under study. Furthermore, if the birds are aggregated too closely for the radar to resolve them individually, the bulk volume reflectivity cannot be translated into a numerical density. We calibrated a commercial off‐the‐shelf marine radar, using a standard spherical target of known RCS. Once calibrated, the radar was used to measure the RCS of common and roseate terns (Sterna hirundo L. and Sterna dougallii Montagu) tracked from a land‐based installation at their breeding colony on Great Gull Island, NY, USA. We also integrated echoes from flocks of terns, comparing these total flock cross‐sections with visual counts from photos taken at the same time as the radar measurements. The radar's calibration parameters were determined with 1% error. RCS measurements made after calibration were expected to be accurate within ±2 dB. Mean tern RCS was estimated at −28 dB relative to one square meter (dBsm), agreeing in magnitude with a simple theoretical model. RCS was 3–4 dB higher when birds’ aspect angles were broadside to the radar beam compared with head‐ or tail‐on. Integrated flock cross‐section was linearly related to the number of birds. The slope of this line, an independent estimate of RCS, was −32 dBsm, within an order of magnitude of the estimate from individual birds, and near the middle of the frequency distribution of RCS values. These results indicate that a calibrated marine radar can count the birds in an aggregation via echo integration. Field calibration of marine radars is practical, enables useful measurements, and should be done more often.

show abstract

Section: Discussionmentioning

confidence: 99%

Quantitative ornithology with a commercial marine radar: standard‐target calibration, target detection and tracking, and measurement of echoes from individuals and flocks

Urmy

Warren

2016

Methods Ecol Evol

View full text Add to dashboard Cite

show abstract

“…In addition to the challenge of detecting the presence of such difficult targets there are also many naturally present targets such as birds, which would cause a large number of false alarms for a sensitive radar. The characterisation of radar signatures from birds has been previously investigated within [6,7], evaluating the differences in their RCS compared with the micro-Doppler profiles. However, there is little available research on radar detection and classification of micro-drones.…”

Section: Introductionmentioning

confidence: 99%

Multistatic micro‐Doppler radar feature extraction for classification of unloaded/loaded micro‐drones

Ritchie

Fioranelli

Borrion

et al. 2017

IET Radar, Sonar & Navigation

133

View full text Add to dashboard Cite

This paper presents the use of micro-Doppler signatures collected by a multistatic radar to detect and discriminate between micro-drones hovering and flying while carrying different payloads, which may be an indication of unusual or potentially hostile activities. Different features have been extracted and tested, namely features related to the Radar Cross Section of the micro-drones, as well as the Singular Value Decomposition (SVD) and centroid of the micro-Doppler signatures. In particular, the added benefit of using multistatic information in comparison with conventional radar is quantified. Classification performance when identifying the weight of the payload that the drone was carrying while hovering was found to be consistently above 96% using the centroid-based features and multistatic information. For the non-hovering scenarios classification results with accuracy above 95% were also demonstrated in preliminary tests in discriminating between three different payload weights.

show abstract

“…Likewise, the simulated echoes added to the radar images were duplicates of echoes from real birds, though we did assume that their RCS was constant in time. This is not true for real animals, whose RCS varies with aspect angle to the radar beam, body shape and wingbeat (Edwards & Houghton, ; Torvik, Knapskog, Lie‐Svendsen, Olsen, & Griffiths, ; Vaughn, ), and may have led us to over‐estimate detectability or trackability. Variability in RCS would be easy to add to echo simulations, but was beyond the scope of this paper.…”

Section: Discussionmentioning

confidence: 99%

Evaluating the target‐tracking performance of scanning avian radars by augmenting data with simulated echoes

Urmy

Warren

2020

Methods Ecol Evol

View full text Add to dashboard Cite

Small scanning radars have been used for many years to track the movements of insects, birds and bats. While the ability to track multiple flying animals simultaneously has numerous applications in basic ecology and applied conservation, translating radar tracks into accurate animal densities and fluxes requires estimates of detection and tracking probabilities. These can be challenging to determine, especially in environments with variable background clutter. In order to assess radar tracking probabilities, we added echoes from simulated bird tracks to sequences of scans collected with an X‐band marine radar at a colony of common and roseate terns (Sterna hirundo and S. dougallii) on Great Gull Island, New York, USA in the summers of 2014 and 2015. Automated detection, classification and tracking algorithms were used to extract the trajectories of terns from the radar data. The proportion of simulated tracks recovered by these procedures could then be used to estimate the tracking probabilities for real birds. Stationary telescope transects provided visual ground truth. The radar could track individual birds up to 3 km away, performing best between 0.5 and 1.2 km, where 38% of simulated birds were correctly detected and tracked in each scan. Overall, 94% of all simulated birds were tracked over at least part of their trajectories. Tracking performance was limited by weak bird echoes, backscatter from the sea surface and the inherent challenges of multi‐target tracking. This simulation‐based method provides a low‐cost, flexible approach for estimating radar‐tracking probabilities in complex, cluttered environments. Knowledge of these probabilities in turn allows the animal densities and fluxes to be corrected for imperfect detection. Despite their limitations, small scanning radars can track hundreds of birds simultaneously over tens of km2, giving a view of animal movement unavailable with other techniques.

show abstract

Amplitude modulation on echoes from large birds

Cited by 17 publications

References 8 publications

Quantitative ornithology with a commercial marine radar: standard‐target calibration, target detection and tracking, and measurement of echoes from individuals and flocks

Quantitative ornithology with a commercial marine radar: standard‐target calibration, target detection and tracking, and measurement of echoes from individuals and flocks

Multistatic micro‐Doppler radar feature extraction for classification of unloaded/loaded micro‐drones

Evaluating the target‐tracking performance of scanning avian radars by augmenting data with simulated echoes

Contact Info

Product

Resources

About