A geometrical approach for aerial cooperative obstacle mapping using RSSI observations

Abstract

The effect of an obstacle on signal strength attenuation is the most important reason that affects the performance of distance estimation based on Received Signal Strength Indication (RSSI) observations. Consequently, in this paper, a novel approach for estimation of the location and height of an obstacle between two UAVs using RSSI observations is proposed which would help to better estimate the location of a radio frequency (RF) source. The long-term goal of developing this approach is to improve the localization of an RF source by removing the effect of obstacle(s) on the signal attenuation. This approach is based on path planning of the UAVs to estimate the tip of the obstacle between them. The change in the diffraction loss observations are used to find the Line Of Sight (LOS) positions of the UAVs. These LOS lines, constructed by connecting the UAVs in LOS situation, are the locus of the tip of the obstacle and used in an iterative geometrical approach for estimation of the location of the tip of the obstacle. Due to the uncertainty in determining the LOS position which is created because of the radius of the Fresnel zone, the motion steps of UAVs, and the non-modeled dynamics in signal attenuation, an EKF filter is used to estimate the tip of the obstacle. The approach has been simulated and the results show that the approach provides better accuracy in RF source localization compared to the basic approach which does not consider the obstacles in the localization process.

Propagation Characteristics for Uavs Operating at Short Range and Low Altitude

“…According to the measurement results analyzed in Section 3.2, we state that for UAVs operating in short range, low altitude and obstacle-free areas, two-ray based models are a better approach than the free space model ‡ , and some considerations must be taken related to the reflecting surface. For example, in our grass testbed, we propose an adjusted two-ray model which includes a phase shifting factor α = κ π in the received electric field (5), in such a way that,…”

“…Moreover, Tatar Mamaghani and Hong [3] pointed out that at low-altitude the UAV propagation channel presents small-scale Rician fading with a probabilistic path loss attenuation † . See [3,[5][6][7] for LOS or NLOS approaches taken for different examples of UAVs implementations.…”