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UWB- based weighted adaptive Kalman filtering indoor positioning algorithm
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uwb-based-weighted-adaptive-kalman-filtering-indoor-positioning-algorithm
Aiming at the problems of low accuracy , poor anti interference ability , and poor stability of traditional indoor Kalman filter positioning algorithm in complex indoor environments, a weighted adaptive Kalman filtering ( WKF )time difference of arrival ( TDOA ) positioning algorithm, based on ultra- wideband ( UWB) is proposed.Firstly, establish a four- anchor ultra- bandwidth positioning system, intrduce wireless clock synchronization technology to eliminate dlock erors. Secondly,compensate the original data to reduce positioning error caused by human reflection and multipeath effect and other influencing factors.
Then,recursively update the noise covariance and dynamically adjust the weights to enhance the stability of the filter. Finally , dynamic real- time positioning of moving target is realized. The results show that WKF-TDOA can reduce positioning errors caused by multipath effet,and achieve dynamic real- time high-precision positioning of moving targets. Compared with other existing positioning methods,the experimental results show that this method has higher precision and better robustness.
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基于UWB的加权自适应卡尔曼滤波室内定位算法.pdf
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ultra -wideband, UWB, indoor complex positioning, weighted adaptive Kalman filtering, WKF, error compensation, time difference of armival, TDOA
UWB- based weighted adaptive Kalman filtering indoor positioning algorithm
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