Micro-Doppler analysis of pedestrians in ISAR imaging

Ghaleb, Antoine; Vignaud, L.; Nicolas, Jean‐Marie

doi:10.1109/radar.2008.4720889

Cited by 8 publications

(4 citation statements)

References 7 publications

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“…Motion capture techniques have also been successfully applied to generate radar microDoppler signatures for animals [15]. Indeed, several works have subsequently utilized motion capture-based simulated micro-Doppler as a basis for studying the extraction of features relevant to gait analysis [16] and classification [17]- [20]. However, validation of the approach has primarily been done by simple visual comparison with measured micro-Doppler signatures [21]- [24].…”

Section: Introductionmentioning

confidence: 99%

Knowledge Exploitation for Human Micro-Doppler Classification

Karabacak

Gürbüz

et al. 2015

IEEE Geosci. Remote Sensing Lett.

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Abstract-Micro-Doppler radar signatures have a great potential for classifying pedestrians and animals, as well as their motion pattern, in a variety of surveillance applications. Due to the many degrees of freedom involved, real data needs to be complemented with accurate simulated radar data to successfully be able to design and test radar signal processing algorithms. In many cases, the ability to collect real data is limited by monetary and practical considerations, whereas in a simulated environment any desired scenario may be generated. Motion capture has been used in several works to simulate the human micro-Doppler signature measured by radar; however, validation of the approach has only been done based on visual comparisons of micro-Doppler signatures. This work validates and, more importantly, extends the exploitation of motion capture data not just to simulate micro-Doppler signatures but also to use the simulated signatures as a source of a priori knowledge to improve the classification performance of real radar data, especially in the case when the total amount of data is small.

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Section: Introductionmentioning

confidence: 99%

Knowledge Exploitation for Human Micro-Doppler Classification

Karabacak

Gürbüz

et al. 2015

IEEE Geosci. Remote Sensing Lett.

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“…The waves are reflected by an object and received by the radar via one or several receiver antennas (Rx). The comparison between the transmitted and the received waveforms infers the distance, the radial velocity, the azimuth angle and the elevation of the reflector regarding the radar position [16]. Most of the automotive radars use Multiple Input Multiple Output (MIMO) systems: each couple of Tx/Rx receives the reflected signal assigned to a specific Tx transmitting a waveform.…”

Section: B Radar Sensor and Effectsmentioning

confidence: 99%

CARRADA Dataset: Camera and Automotive Radar with Range- Angle- Doppler Annotations

Ouaknine

Newson

Rebut

et al. 2021

2020 25th International Conference on Pattern Recognition (ICPR)

104

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“…The use of micro‐range and micro‐Doppler signatures can decompose Doppler and range features into human body parts for improving classification, recognition, and identification [76]. An X‐band radar imaging system with very high‐range resolution studied two people cross‐walking, cross‐running, and a cyclist [5, 77, 78]. They have created range‐Doppler movies where the micro‐Doppler can easily be perceived.…”

Section: Review Of Micro‐doppler Effect In Radarmentioning

confidence: 99%