In order to improve the performance of the traditional hybrid time-of-arrival（TOA）/angle-of-arrival（AOA）location algorithm in non-line-of-sight（NLOS）environments,a new hybrid TOA/AOA location estimation algorith...In order to improve the performance of the traditional hybrid time-of-arrival（TOA）/angle-of-arrival（AOA）location algorithm in non-line-of-sight（NLOS）environments,a new hybrid TOA/AOA location estimation algorithm by utilizing scatterer information is proposed.The linearized region of the mobile station（MS）is obtained according to the base station（BS）coordinates and the TOA measurements.The candidate points（CPs）of the MS are generated from this region.Then,using the measured TOA and AOA measurements,the radius of each scatterer is computed.Compared with the prior scatterer information,true CPs are obtained among all the CPs.The adaptive fuzzy clustering（AFC）technology is adopted to estimate the position of the MS with true CPs.Finally,simulations are conducted to evaluate the performance of the algorithm.The results demonstrate that the proposed location algorithm can significantly mitigate the NLOS effect and efficiently estimate the MS position.展开更多
基金The National High Technology Research and Development Program of China(863Program)(No.2008AA01Z227)the National Natural Science Foundation of China(No.60872075)
文摘In order to improve the performance of the traditional hybrid time-of-arrival（TOA）/angle-of-arrival（AOA）location algorithm in non-line-of-sight（NLOS）environments,a new hybrid TOA/AOA location estimation algorithm by utilizing scatterer information is proposed.The linearized region of the mobile station（MS）is obtained according to the base station（BS）coordinates and the TOA measurements.The candidate points（CPs）of the MS are generated from this region.Then,using the measured TOA and AOA measurements,the radius of each scatterer is computed.Compared with the prior scatterer information,true CPs are obtained among all the CPs.The adaptive fuzzy clustering（AFC）technology is adopted to estimate the position of the MS with true CPs.Finally,simulations are conducted to evaluate the performance of the algorithm.The results demonstrate that the proposed location algorithm can significantly mitigate the NLOS effect and efficiently estimate the MS position.
