Optimal path planning for DRSSI based localization of an RF source by multiple UAVs

The Radio Frequency (RF) source localization accuracy depends not only on the measurement performance of sensors, but also on the relative location of the sensors and the source. This paper investigates the impact of UAVs, equipped with RSSI sensors, formation and trajectory on the aerial RF source localization performance for Differential Received Signal Strength Indication (DRSSI) based approach in None Line Of Sight (NLOS) propagation condition. To eliminate the need for knowing the power of the signal source the DRSSI approach is applied. The collected measurements in each waypoint are used to estimate the location of the source iteratively by the use of Extended Kalman Filter (EKF). The Cramer-Rao Lower Bound (CRLB), which expresses a lower bound on the variance of any unbiased estimator, is used as the objective function for the proposed algorithm. Due to the complexity of Jacobin calculation to perform global CRLB optimization, the local values of CRLBs in the current waypoint and the next probable waypoints are used to determine the best path. Maximizing the determinant of the inverse of CRLB, i.e. the Fisher Information Matrix, in each measurement instance over the next probable waypoint, minimizes the estimation uncertainty area. The effectiveness of the proposed algorithm is illustrated by Monte-Carlo simulations and compared with the basic bio-inspired approach of going toward the estimated direction of the source.