Proceedings of 2014 3rd Asia-Pacific Conference on Antennas and Propagation 2014
DOI: 10.1109/apcap.2014.6992691
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Empirical analysis of chirp and multitones performances with a UWB software defined radar: Range, distance and Doppler

Abstract: Abstract-In this study, a protocol for an unbiased analysis of radar signals' performance. Using a novel UWB softwaredefined radar, range profile, Doppler profile and detection range are evaluated for both Linear Frequency Modulated pulse and Multitones. The radar was prototyped and is comparable in overall performance to software defined radar test-beds found in the literature. The measured performance was in agreement with the simulations.

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Cited by 5 publications
(6 citation statements)
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“…The result is commonly known as micro-Doppler signature or spectrogram representing the evolution of Doppler as a function of time at the cost of resolution because of the smaller window size. However, it allows capturing the motions of moving parts of a structure [15][16][17]. The overlap factor is 0.95, and the window size is 0.2s, giving a 200-point FFT zeropadded to 800.…”
Section: Data Collection and And Pre-processingmentioning
confidence: 99%
“…The result is commonly known as micro-Doppler signature or spectrogram representing the evolution of Doppler as a function of time at the cost of resolution because of the smaller window size. However, it allows capturing the motions of moving parts of a structure [15][16][17]. The overlap factor is 0.95, and the window size is 0.2s, giving a 200-point FFT zeropadded to 800.…”
Section: Data Collection and And Pre-processingmentioning
confidence: 99%
“…This paper builds on our previous work on experimental radar design [44–48] for the experimental setup and procedure. As for the activities of daily living, this is the continuation of our work in gait analysis [49], activity classification with radar [19, 21, 32, 50] taking into account similar actions challenging the classification process and including a Parkinsonian gait and a gerontology test for independence assessment.…”
Section: Sensing Modalities and Machine Learningmentioning
confidence: 99%
“…Related student projects investigating the viability of onboard processing of SAR imagery for machine vision [5] gave promising results. Likewise, legacy projects on Software Defined Radar are expected to be applicable to the side-looking radar for networking neighbouring UAVs [6]. Future projects will be designed under the assumption that fully autonomous flight will be required for flying multi-rotor UAVs in the most densely populated, 20 to 30 storey high rise urban environments for building exterior inspection, post-fire building interior/exterior inspection, first responders and environmental/pollution monitoring.…”
Section: Introductionmentioning
confidence: 99%