A multi-step Gaussian filtering approach to reduce the effect of non-Gaussian distribution in aerial localization of an RF source in NLOS condition

The hybrid localization using angle of arrival (aoa) and differential received strength signal indicator (drssi) of an rf source with unknown power and non- line-of-sight (nlos) condition has been proven to be advantageous compared to using each method separately. in this paper, the initial hybrid method, which was implemented using particle filters due to the multi-modal/non-gaussian nature of localization in nlos condition, has been replaced by a multi-step gaussian filtering approach which provides similar accuracy with better performance. this has been done using drssi input in the first step of the filtering to determine the linearization point, and then using aoa and drssi inputs together in the second step of the filtering to improve the localization accuracy. the proposed method has been implemented using extended kalman filter and unscented kalman filter. the simulation results show that the accuracy of the multi-step gaussian filtering is comparable to the particle filtering approach with much lower computational load that is important for online localization of several rf sources. furthermore, the effects of uncertainty on the propagation parameters have been studied to show that the robustness of the multi-step gaussian filtering to the uncertainties is comparable to the particle filter approach.