Abstract: ‍ ‍Unmanned aerial vehicle （UAV） airborne multistatic synthetic aperture radar （SAR） has the advantages of strong anti-interference ability， high flexibility， and multi-angle observation regarding imaging perception of high-value targets on the ground and at sea. However， the localization accuracy of the UAV airborne multistatic SAR on targets tends to be seriously affected owing to time-frequency errors caused by the separation of SAR transmitters and receivers， UAV position errors caused by airflow disturbances， and other factors. To address the aforementioned problems， this paper proposes a self-localization method for UAV airborne multistatic SAR based on time difference of arrival （TDOA）. First， multiple images of the same scene from different perspectives were obtained by performing back projection（BP） imaging on the received signals， and the target position was approximated. Subsequently， considering time-frequency synchronization and UAV position errors， the TDOA localization equations were constructed using the rough target position， range information of received signals， and the UAV positions. A more accurate target position was then estimated by using the Taylor algorithm to solve the localization equations， because the solution accuracy was constrained by the redundant equations in the overdetermined localization equations. Finally， the Cramer Rao lower bound （CRLB） was derived to evaluate the proposed method under the above errors. Since the proposed self-localization method utilizes only the range information of the received signals， it avoids the adverse impact of inaccurate Doppler centroid estimation of the received signals on positioning accuracy. Numerical simulations validate the effectiveness of the method under time-frequency synchronization and UAV position errors.