Doppler radars are widely used and investigated due to their peculiar capability to measure very small target displacements with high accuracy and without any contacts. If measuring the motion extent of a single moving target can be considered a quite acknowledged task, the automatic motion detection of a target alternating stationary and moving intervals gives rise to some concerns. Indeed, the output of a quadrature mixer in the presence of a stationary target shows the presence of noise fluctuations which in turns result in uncorrelated phases. This will lead to a wrong phase history and consequently displacement detection.In this contribution, an automatic procedure to highlight only the real target movements is presented. It is demonstrated both by simulating a possible scenario and by testing the solution effectiveness in a real case. These results can be exploited for different applications, e.g., from vital signs detection to structural monitoring.
Robust Doppler Displacement Measurement Resolving the Uncertainty during Target Stationary Moment
Ferro L.
Primo
;Scandurra G.Secondo
;Cardillo E.Ultimo
2024-01-01
Abstract
Doppler radars are widely used and investigated due to their peculiar capability to measure very small target displacements with high accuracy and without any contacts. If measuring the motion extent of a single moving target can be considered a quite acknowledged task, the automatic motion detection of a target alternating stationary and moving intervals gives rise to some concerns. Indeed, the output of a quadrature mixer in the presence of a stationary target shows the presence of noise fluctuations which in turns result in uncorrelated phases. This will lead to a wrong phase history and consequently displacement detection.In this contribution, an automatic procedure to highlight only the real target movements is presented. It is demonstrated both by simulating a possible scenario and by testing the solution effectiveness in a real case. These results can be exploited for different applications, e.g., from vital signs detection to structural monitoring.Pubblicazioni consigliate
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