Doppler Elaboration for Vibrations Detection Using Software Defined Radar

Raffo, Antonio; Costanzo, Sandra

doi:10.1007/978-3-319-56538-5_103

Cited by 2 publications

(1 citation statement)

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“…First introduced by the author of [7], the SDRadar concept leads to a new radar paradigm, where all functions are fully implemented via software, thus providing a solution to design customized radar systems, able to operatively modify their abilities with no change in the hardware configuration. The capabilities of the SDRadar approach have been illustrated in the literature [7,8,9,10], and its applicability to vibrations detection was been first demonstrated by the authors of [11,12], and recently has also been explored by the authors of [13,14].…”

Section: Introductionmentioning

confidence: 99%

Software-Defined Doppler Radar Sensor for Human Breathing Detection

Costanzo

2019

Sensors

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Non-contact wireless sensing approaches have emerged in recent years, in order to enable novel enhanced developments in the framework of healthcare and biomedical scenarios. One of these technologically advanced solutions is given by software-defined radar platforms, a low-cost radar implementation, where all operations are implemented and easily changed via software. In the present paper, a software-defined radar implementation with Doppler elaboration features is presented, to be applied for the non-contact monitoring of human respiration signals. A quadrature receiver I/Q (In-phase/Quadrature) architecture is adopted in order to overcome the critical issues related to the occurrences of null detection points, while the phase-locked loop components included in the software defined radio transceiver are successfully exploited to guarantee the phase correlation between I/Q signal components. The proposed approach leads to a compact, low-cost, and flexible radar solution, whose application abilities may be simply changed via software, with no need for hardware modifications. Experimental results on a human target are discussed so as to demonstrate the feasibility of the proposed approach for vital signs detection.

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