Counting people and things (targets) in a monitored area, also known as crowd-counting, enables several applications in diverse scenarios, including smart building, intelligent transportation, and public safety. In many scenarios, device-free systems relying on the signal backscattering from targets are preferred to device-based systems relying on the communication with the targets via dedicated or personal devices. However, the use of conventional radar techniques (e.g., for multi-target detection) requires us to associate a different set of measured data with each detected target. Data association is a redundant operation for counting and results in high complexity even with few targets. The need of lower dimensionality and complexity calls for signal features to associate the measured signals directly with the number of targets. This paper proposes a mathematical framework for the design of device-free counting systems. First, a maximum a posteriori algorithm is developed for counting via wideband signal backscattering by relying on model order selection. Then, a method that relies on low-level features is proposed to lower the computational complexity. The proposed method is verified via sample-level simulations in realistic operating conditions and compared with current solutions.
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|Titolo:||Device-Free Counting via Wideband Signals|
|Data di pubblicazione:||2017|
|Appare nelle tipologie:||03.1 Articolo su rivista|