基于Kalman滤波的UWB的TOA估计

提出了一种基于卡尔曼滤波的TOA估计算法,充分利用了卡尔曼滤波的预测功能,以预测值为中心对接收信号进行加窗处理,对此窗口内的接收信号作主成份分析得到测量值,然后对预测值进行修正.实验结果表明,与传统的TOA估计算法相比,该算法不仅使信噪比提高了约8～12 dB、均方误差降低了3～4个数量级,而且更便于实时实现.

Abstract：

In this paper,we propose a TOA estimation algorithm based on the Kalman filter in UWB systems.With the predictive function of the Kalman filter,this method processes the received signals in a window whose center is the predictive value.After we get the measured TOA from the received signals of this window by PCA,the estimated TOA can be revised.Extensive experiment results show that not only does the proposed algorithm increase the signal to noise ratio(SNR)by about 8-12 dB and decrease the mean square error by 3～4 orders compared with the traditional algorithms,it also is suitable for real-time implementation.

TOA Estimation Based on Kalman Filtering in UWB Systems