Reducing the computational complexity of WiFi-based passive radar processing

WiFi-based passive radar is considered in this paper as an effective technology for short range monitoring applications. Aiming at limiting its complexity and enhancing its suitability for civilian applications, appropriate modifications are proposed to the signal processing scheme originally designed for such sensor. Specifically, we show that a simple inversion in the order of the main processing stages, namely clutter cancellation and range compression, allows to both reduce the number of floating-point operations and relax the requirements on the data management. Moreover, the use of a reciprocal filter in lieu of a matched filter to implement the range compression stage is proved to yield a further simplification in the resulting processing scheme along with additional benefits in terms of achievable performance in the considered application. The alternative processing schemes are compared in terms of computational burden and the effectiveness of the proposed cost-effective solutions is proved against experimental datasets.