摘要
研究了时延估计算法在超宽带(Ultra Wide Band)定位中的应用,其广义相关自适应时间延迟估计算法的收敛速度慢,在低信噪比条件下时间延迟估计精度较低。针对低信噪比条件下的收敛特性,提出一种最大似然加权的广义相关自适应时间延迟估计算法,并进一步提出了改进的基于最大似然(Maximum Likelihood)加权函数的广义互相关时延估计算法。改进的算法采用加窗法和自适应时变干扰删除滤波法,弥补了原算法计算量大及无法消除时变信号干扰的不足。仿真结果表明,改进的算法计算复杂度明显降低,能够有效地消除其他信号干扰,具有较高的时延估计精度和鲁棒性。
In this paper we study the time delay estimate algorithm in the application of ultra wide band （UWB） localization. The convergence rate based on the generally-correlated auto-adapted time delay estimate algorithm is slow and the time delay estimate precision is low under the low signal-to-noise ratio condition. In view of restrains characteristic under the low signal to noise ratio condition, we propose one kind of generalized correlation auto-adapted time delay estimate algorithm based on the maximum likelihood （ML） weighting function, and further propose the improved generalized mutual correlation time delay estimate algorithm based on the maximum likelihood （ML） weighting function.The improved algorithm uses the adding window law and auto-adapted time varying disturbance deletion filter law, making up the insufficiency of the large original algorithm computation quantity and unable elimination of the changed meaconing. The simulation results indicate that the computation complication of this improved algorithm is obviously reduced and it can effectively eliminate other meaconings, having the higher time delay estimate precision and robustness.
出处
《无线电通信技术》
2009年第2期43-45,55,共4页
Radio Communications Technology
基金
西南科技大学科研基金项目(06zx7107)
关键词
时延估计
最大似然权函数
UWB
加窗
自适应时变干扰删除滤波法
time delay estimate
maximum likelihood （ML） weighted function
UWB
adding window law
auto-adapted time varying disturbance deletion filter law
