K Band Radar Drone Signatures

Kolev, Nikolay Ivanov; Sivkov, Yordan; Sirakov, Ekaterinoslav

doi:10.11610/isij.4726

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…In the case of drones and UAVs, the spinning of the rotor blades is the primary cause of their micro-Doppler signatures [21,22]. The rotation is deterministic and controlled, and coupled with the fact that these targets have a high RCS, their micro-Doppler signatures are clean, symmetric, and recognizable compared to those of birds.…”

Section: General Characteristics Of Micro-doppler Signatures From Bir...mentioning

confidence: 99%

Classification and Discrimination of Birds and Small Drones Using Radar Micro-Doppler Spectrogram Images

Narayanan

Tsang

Bharadwaj

2023

Signals

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This paper investigates the use of micro-Doppler spectrogram signatures of flying targets, such as drones and birds, to aid in their remote classification. Using a custom-designed 10-GHz continuous wave (CW) radar system, measurements from different scenarios on a variety of targets were recorded to create datasets for image classification. Time/velocity spectrograms generated for micro-Doppler analysis of multiple drones and birds were used for target identification and movement classification using TensorFlow. Using support vector machines (SVMs), the results showed an accuracy of about 90% for drone size classification, about 96% for drone vs. bird classification, and about 85% for individual drone and bird distinction between five classes. Different characteristics of target detection were explored, including the landscape and behavior of the target.

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Section: General Characteristics Of Micro-doppler Signatures From Bir...mentioning

confidence: 99%

Classification and Discrimination of Birds and Small Drones Using Radar Micro-Doppler Spectrogram Images

Narayanan

Tsang

Bharadwaj

2023

Signals

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“…The availability of ground-based data in addition allows effective and cost-effective monitoring of climate change in remote areas using SAR data. The SAR C-band enables the effective study of various objects [5][6][7][8][9][10][11][12][13][14][15] and especially wet snow and ice 3,4,[16][17][18][19] . Using SAR data, we studied the type of changes in the digital value of the reflected signal (Q) from various objects, including water in different phase states.…”

Section: Introductionmentioning

confidence: 99%

A synchronized remote sensing monitoring approach in the Livingstone island region of Antarctica

Spasova,

Avetisyan

2023

Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023)

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Data-driven innovations bring significant benefits to societies directly affected by global warming, as they underpin Global and European climate change policy. The application of a synchronous approach and interoperability of data from different sources for environmental monitoring in one of the most vulnerable to climate change regions in the World is the aim of this research. The research was conducted at Hannah Point peninsula, near the Bulgarian Antarctic base "St. Kliment Ohridski" on Livingstone Island, South Shetland Islands, Antarctica. The study area has high ecological importance for tracking the dynamics of processes not only on a local but also on a global scale. Various research sites with different groups of objects serving as environmental benchmarks were selected to be studied. The study objects include snow cover, wet snow, water, ice (including sea ice), herbaceous vegetation, lichens, mosses, soils, and sand. For each of the objects, ground GPS points were defined and in situ spectrometric measurements were performed. Data from an innovative automatic recording weather station (AWG), as well as various indicators and indices based on the spectral reflectance characteristics of the investigated objects in the optical and microwave range, were used. For their generation were used satellite images from Sentinel-1 and Sentinel-2 sensors of European Space Agency. Multiple optical indices were used to demonstrate the changes in the state of the objects for the summer season of 2022-2023. The data obtained and models used will serve the Bulgarian initiative for the construction of the Digital Twins, which is being on pilot developed in the Department of Aerospace Information (SRTI-BAS) and could be used by a wide range of scientists in the field of polar research as well as for climate change education. Open Data were used in this study, to promote the Open science policy and FAIR principles as much as possible.

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“…However, typical long-distance radar frequencies are often in the S (form 2 GHz to 4 GHz), and L (form 1 GHz to 2 GHz) bands. Furthermore, using a higher than X frequency band is even better to detect UAVs; nonetheless, the range of view of such radar decreases considerably, so in practice UAVs can be seen or even heard right next door [3][4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Investigation of UAV Detection by Different Solid-State Marine Radars

et al. 2022

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The development of unmanned aerial vehicle (UAV) technologies provides not only benefits but also threats. UAV technologies are developing faster than means of detecting and neutralizing them. Radar technology is one of the means of UAV detection which provides the longest detection range. Today’s market provides low-cost solid-state marine radar working on FMCW and pulse-compression principles of operation. Despite such radars having attractive features, they were not designed for UAV detection. Although they are not optimal, they could be used for UAV detection. The detection possibility of UAVs by marine radars was investigated by using three types of radars and two types of small UAVs as targets. Radar cross-section measurements of the targets were made in laboratory conditions.

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K Band Radar Drone Signatures

Abstract: An experimental K-band radar setup has been developed using industrial radar board IVS-465 and NI MyRIO for control and data acquisition. This article presents results for drone reflected signals processing.

Cited by 3 publications

References 2 publications

Classification and Discrimination of Birds and Small Drones Using Radar Micro-Doppler Spectrogram Images

Classification and Discrimination of Birds and Small Drones Using Radar Micro-Doppler Spectrogram Images

A synchronized remote sensing monitoring approach in the Livingstone island region of Antarctica

Investigation of UAV Detection by Different Solid-State Marine Radars

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