Super resolution passive radars based on 802.11ax Wi‐Fi signals for human movement detection

Passive Radars based on Wi-Fi signals provide an excellent opportunity for human sensing without violating the privacy of individuals. Due to limited integration time bursts and relatively low bandwidths, Fourier Transform-based methods do not required accuracy. Herein, a Wi-Fi-based passive radar algorithm is proposed indoor movement detection with super resolution which relies ESPRIT estimate range/speed parameters from number measurements. To determine targets in environment, new Model Order Selection (MOS) method exploits orthogonality between basis vectors signal noise subspaces obtained sample covariance matrix The MOS along are numerically analysed compared other existing methods. Finally, performance experimentally validated conditions.