UAV Assisted Localization Scheme of WSNs Using RSSI and CSI Information

In recent years, the research of high-precision positioning with wireless sensor networks has attracted a lot of attention, especially in the scenarios of UAV (unmanned aerial vehicles) assisted positioning. This paper proposes a new method of getting more accurate range information. In contrast to existing traditional works, we use multiple range information instead of a single distance information. First, a UAV transmits beacon packets to each sensor node at random positions and all nodes record RSSI (Received Signal Strength Indicator) vectors. We can estimate the distance between nodes by comparing the similarity of RSSI vectors. Second, we estimate the distance between two nodes by means of comparing their CSI (channel state Information) to UAV. Finally, we use Kalman filter to fuse the two-range information. And we can get more accurate range information for positioning. Simulations validate high localization accuracy of the proposed algorithm. Besides, the numbers of beacons transmitted by UAV and the energy consumption can be reduced in the simulation.