Passive wireless local area network radar network using compressive sensing technique

Abstract

Distributed networks constructed from heterogeneous or homogeneous sensors, which are also called multiple-input–multiple-output systems, offer several advantages compared to single sensor systems. In particular for a distributed homogeneous sensor network targets are illuminated from various aspect angles and reflections are received at different locations simultaneously. Hence, these networks outperform single-input–single-output systems easily by several aspects. This spatial diversity improves target detection and parameter estimation dramatically. Therefore these radar networks attract more and more scientists worldwide. This study shows the potential of compressive sensing technique applied to a distributed homogeneous sensor network comprised of several wireless local area network routers as transmitters and dedicated receivers. The CS group sparsity approach is employed to reduce the required data rate, which has to be transferred to a central processing unit for data fusion, without decreasing the performance of the sensor network.