Based on the principle of statistical linear regression, a set of n ＋ 2 sigma points instead of 2n ＋ 1 sigma points used in the unscented Kalman filter （UKF）, is constructed to approximate the system state. And fi...Based on the principle of statistical linear regression, a set of n ＋ 2 sigma points instead of 2n ＋ 1 sigma points used in the unscented Kalman filter （UKF）, is constructed to approximate the system state. And filter accuracy is second order. Real-time of modified UKF is improved. In order to describe accurately the maneuvering target, the ＂current＂ statistical model is used. And the equation of acceleration error covariance is modified at every sample time of the filter. The modified adaptive UKF is presented for estimating the position, velocity and acceleration of maneuvering target. Monte Carlo simulations show the modified adaptive UKF acquires good performance for tracking position of maneuvering target. The modified adaptive UKF has better computational efficiency than UKF.展开更多
Ultra-Wide Bandwidth(UWB)localization based on time of arrival(TOA)and angle of arrival(AOA)has attracted increasing interest owing to its high accuracy and low cost.However,existing localization methods often fail to...Ultra-Wide Bandwidth(UWB)localization based on time of arrival(TOA)and angle of arrival(AOA)has attracted increasing interest owing to its high accuracy and low cost.However,existing localization methods often fail to achieve satisfactory accuracy in realistic environments due to multipath effects and non-line-of-sight(NLOS)propagation.In this paper,we propose a passive anchor assisted localization(PAAL)scheme,where the active anchor obtains TOA/AOA measurements to the agent while the passive anchors capture the signals from the active anchor and agent.The proposed method fully exploits the time-difference-of-arrival(TDOA)information from the measurements at the passive anchors to complement single-anchor joint TOA/AOA localization.The performance limits of the PAAL system are derived as a benchmark via the information inequality.Moreover,we implement the PAAL system on a low-cost UWB platform,which can achieve 20 cm localization accuracy in NLOS environments.展开更多
基金the National Natural Science Foundation of China (413090503)
文摘Based on the principle of statistical linear regression, a set of n ＋ 2 sigma points instead of 2n ＋ 1 sigma points used in the unscented Kalman filter （UKF）, is constructed to approximate the system state. And filter accuracy is second order. Real-time of modified UKF is improved. In order to describe accurately the maneuvering target, the ＂current＂ statistical model is used. And the equation of acceleration error covariance is modified at every sample time of the filter. The modified adaptive UKF is presented for estimating the position, velocity and acceleration of maneuvering target. Monte Carlo simulations show the modified adaptive UKF acquires good performance for tracking position of maneuvering target. The modified adaptive UKF has better computational efficiency than UKF.
文摘Ultra-Wide Bandwidth(UWB)localization based on time of arrival(TOA)and angle of arrival(AOA)has attracted increasing interest owing to its high accuracy and low cost.However,existing localization methods often fail to achieve satisfactory accuracy in realistic environments due to multipath effects and non-line-of-sight(NLOS)propagation.In this paper,we propose a passive anchor assisted localization(PAAL)scheme,where the active anchor obtains TOA/AOA measurements to the agent while the passive anchors capture the signals from the active anchor and agent.The proposed method fully exploits the time-difference-of-arrival(TDOA)information from the measurements at the passive anchors to complement single-anchor joint TOA/AOA localization.The performance limits of the PAAL system are derived as a benchmark via the information inequality.Moreover,we implement the PAAL system on a low-cost UWB platform,which can achieve 20 cm localization accuracy in NLOS environments.
