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Path planning for localization of an RF source by multiple UAVs on the Crammer-Rao Lower Bound

This paper presents a path planning approach of several UAVs for Radio Frequency (RF) source localization in None Line Of Sight (NLOS) propagation condition using the Received Signal Strength Indication (RSSI). The paths are planned such that the lower bound of standard deviation of localization error, which is equivalent to the Cramer-Rao Lower Bound (CRLB) of the estimation, minimized at any time. Due to the complexity of Jacobin calculation to perform global CRLB optimization, the local values of CRLBs in the current waypoint and next probable waypoints are used in the steepest decent approach to determine the best path. Furthermore, the complexity is reduced by discretizing the space for UAVs to make the computation feasible. The effect of NLOS propagation on the RSSI measurements is simulated by a log-normal distribution and the last estimation of radio source location is used to calculate the local CRLBs. The proposed approach has been simulated and compared with the basic bio-inspired approach of going toward the sensed direction of the source. The result shows better performance than the basic approach.