Study On NLOS UAV Positioning Method By Passive Receivers Based On Modeling Of Complex Electromagnetic Environment

In recent years,UAV technolog,y has developed rapidly,and if it is not properly controlled,it has great potential harm.For example,UAVs can invade restricted military areas for aerial reconnaissance,or they can carry bombs to attack specific facilities.However,there is currently no reasonable control measures,especially in urban low-altitude and ultra-low-altitude environments,where the electromagnetic targets are dense,the frequency is high,and the UAV signal propagation path is very complicated.In the urban space environment,the electromagnetic targets are dense,and the frequency is the same,and the UAV signal propagation path is very complicated.Therefore,an aerial surveillance and jamming system capable of identifying invading UAVs in a complex electromagnetic environment and failing them is a hot topic of research today.The critical step in the surveillance and strike system is to precisely and fast position UAVs.In dense urban canyon environments,precisely positioning a flying UAV by passive radio frequency(RF)measurements are being troubled by the NLOS bias,which is the main adverse effect of existing positioning schemes based on the received signal strength(RSS),time difference of arrival(TDOA),time of arrival(TOA),angle of arrival(AOA)method or joint method.In order to improve the positioning accuracy and control the NLOS deviation,these solutions need to deploy a large number of receivers and set a priori NLOS statistical information to deal wih the error term,which greatly increases the calculation complexity and hardware cost,which is difficult to achieve in reality.Aiming at the problem of large and uncertain NLOS deviation faced by NLOS positioning in the urban complex electromagnetic environment,the positioningaccuracy is severely reduced.This paper studies and analyzes a variety of NLOS positioning algorithms,such as FOA and TDOA positioning algorithms based on error optimization and locates the defects of these algorithms.Through the reconstructionof TDOA positioning algorithm,it is further combined with semi-definite programming(SDP)technology to make TDOA the positioning model is transformed into a TOA positioning optimization model,which can effectively overcome the above defects.Theoretical analysis and simulation verification show that under severe non-line-of-sight environments,the normalized positioning error of the algorithm is,and the positioning mean square error is close to the Cramer-Rao lower bound.Based on the above research,this paper further expands the depth of the research.Focusing on the optimization of NLOS multipath scattering and UAV mobile positioning under flight conditions,a NLOS collaborative positioning model based on SDP and TDOA and AOA is proposed.Approximately estimate the position of the scatterer through SDP,and then divide the NLOS propagation path of the signal into two LOS paths.Its intersection is the scatterer,and further estimate the position of the UAV-based on the scatterer's location.Theoretical analysis and simulation verification show that the processing method in this paper significantly improves the positioning accuracy under NLOS conditions.Under severe non-line-of-sight conditions,the normalized positioning error reaches.