Clutter removal for Wi-Fi-based passive bistatic radar

We address the problem of static clutter removal in Wi-Fi-based passive bistatic radars. Our goal is to detect slowly moving targets in highly cluttered indoor environments, using Orthogonal Frequency-Division Multiplexing signals from the 802.11n and 802.11ac Wi-Fi standards as sources of opportunity. We propose alternatives to the commonly used Extended Cancellation Algorithm (ECA) clutter removal method. Those alternatives are compared to ECA with simulations using an innovative metric based on CA-CFAR detection, and validated with experimental measurements using two Universal Software Radio Peripherals, along with a fan and an electric train as radar targets. The conclusion of that analysis is that, thanks to the decoupled range and Doppler radar processing, simple novel methods such as Average Removal are efficient alternatives to the computationally intensive ECA which is currently the state-of-the-art in CR.