Such 3D through-wall imaging would be very useful in disaster scenarios for search and rescue missions, or for surveillance operations.
In their paper titled “3D Through-Wall Imaging with Unmanned Aerial Vehicles Using WiFi” (PDF), the researchers note that although through-wall imaging based on Wi-Fi’s RSSI measurements had already been successfully demonstrated in 2D using unmanned ground vehicles (but only yielding a 2D footprint), moving up to the third dimension was much more challenging, especially with the constraint to estimate rapidly a high number of voxels (the volume) from only a relatively small number of measurements.
In search and rescue situations, time is of essence, hence limiting the number of measurement paths and making 3D-reconstruction more difficult based on how the WiFi signal is being affected by the obstacles within the unknown area.
The researchers solved this problem using Markov random field (MRF) modelling, loopy belief propagation and sparse signal processing, together with optimized path planning to fly the drones (two octo-copters) along zigzagging parallel 3D routes, on each side of the walled-up area.
With their experiments, the researchers demonstrated how they were able to obtain high-quality through-wall images of different test setups made up of thick brick walls, with less than 4% of measurements.
University of California Santa Barbara – www.ucsb.edu
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