Autonomous wireless radar sensor mote for target material classification
Autonomous wireless sensor networks consisting of different types of sensor modalities have been receiving greater attention from researchers due to their versatility and portability. These autonomous sensor networks commonly include passive sensors such as infrared, acoustic, vibration, and magnetic nodes. However, fusion of active sensors in the integrated sensor network, such as Doppler radars, may offer powerful capabilities for many different sensing and classification tasks. In this work, we demonstrate the design and implementation of an autonomous wireless sensor network integrating a Doppler sensor with commercial off-the-shelf components. We investigate the effect of various types of target materials on the measured radar signal as one of the applications of the newly designed radar-mote network. Different types of materials affect the amount of energy reflected back to the source of an electromagnetic wave. We obtain mathematical and simulation models for the reflectivity of different homogeneous non-conducting materials and study the effect of such reflectivity on the classification of targets. We validate our simulation results using real experimental data collected through our autonomous radar-mote sensor network using various types of targets. © 2012 Elsevier Inc.
Digital Signal Processing: A Review Journal
Khan, M., Iftekharuddin, K., McCracken, E., Islam, K., Bhurtel, S., & Wang, L. (2013). Autonomous wireless radar sensor mote for target material classification. Digital Signal Processing: A Review Journal, 23 (3), 722-735. https://doi.org/10.1016/j.dsp.2012.11.010