Design and evaluation of a low-cost multistatic netted radar system

IET Radar, Sonar & Navigation

Borrion

et al. 2017

132

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.

Section: Experimental Setup and Radar Systemmentioning

confidence: 99%

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

IET Radar, Sonar & Navigation

Borrion

et al. 2017

132

“…The multistatic radar system used to gather the data analysed for this paper is the coherent pulsed radar NetRAD, developed at University College London over the past twelve years [30]. NetRAD consists of three separate but identical nodes operating at 2.4 GHz with 45 MHz signal bandwidth.…”

Section: Radar System and Data Analysismentioning

confidence: 99%

Feature Diversity for Optimized Human Micro-Doppler Classification Using Multistatic Radar

IEEE Trans. Aerosp. Electron. Syst.

Gürbüz

et al. 2017

Feature diversity for optimized human micro-doppler classification using multistatic radar. IEEE Transactions on Aerospace and Electronic Systems, 53(2), pp. 640-654. (doi:10.1109/TAES.2017.2651678) This is the author's final accepted version.There may be differences between this version and the published version. FEATURE DIVERSITY FOR OPTIMIZED HUMAN MICRO-DOPPLER CLASSIFICATION USING MULTISTATIC RADARFrancesco Fioranelli (1) , Matthew Ritchie (2) , Sevgi Zübeyde Gürbüz (3) , Hugh Griffiths (2) ( AbstractThis paper investigates the selection of different combinations of features at different multistatic radar nodes, depending on scenario parameters, such as aspect angle to the target and signal-to-noise ratio, and radar parameters, such as dwell time, polarisation, and frequency band. Two sets of experimental data collected with the multistatic radar system NetRAD are analysed for two separate problems, namely the classification of unarmed vs potentially armed multiple personnel, and the personnel recognition of individuals based on walking gait. The results show that the overall classification accuracy can be significantly improved by taking into account feature diversity at each radar node depending on the environmental parameters and target behaviour, in comparison with the conventional approach of selecting the same features for all nodes.

“…The radar system used for these measurements was the NetRAD system that has been developed at University College London (UCL) over the past 10 years [8]. NetRAD is an SBand (2.4 GHz) coherent pulsed multistatic radar, with three separate but identical nodes [9].…”

Section: Radar and Measurement Geometrymentioning

confidence: 99%

Monostatic and bistatic radar measurements of birds and micro-drone

2016 IEEE Radar Conference (RadarConf)

Griffiths

et al. 2016

-This paper analyses the experimental results from recent monostatic and bistatic radar measurements of multiple birds as well as a quadcopter micro-drone. The radar system deployed for these measurements was the UCL developed NetRAD system. The aim of this work is to evaluate the key differences observed by a radar system between different birds and a micro-drone. In order to do simultaneous monostatic co and cross polarized data was measured along with coherent bistatic measurements. The results obtained show comparable signature within the time domain and a marked difference in the Doppler domain, from the various birds in comparison to the micro-drone.