摘要
对主动声呐混响信号进行谱估计,用高阶统计量对混响信号建立自回归模型,并建立基于高阶统计量的Yule-Walker方程,解方程得到估计系数.将高阶统计量谱估计的结果与二阶统计量估计的结果进行比较,得出髙阶统计量对自回归模型的谱估计优于二阶的结果.高阶统计量能弥补二阶统计量无法反映信号相位特性的不足,提高谱估计的一致性.
On the spectral estimation of the reverberation of the active sonar, auto-regressive model and Yule-Walker equation are established using higher-order statistics to gain the coefficient. Comparing the estimated spectral using higher-order with the estimated spectral using second-order statistics, it can be concluded that the use of higher-order statistics on the estimate of spectral is better than the use of second-order statistics. Higher-order statistics can make up for the disadvantage that the second-order statistics can not describe the phase information of signals, and improve the consistency of spectral estimation.
出处
《武汉理工大学学报（交通科学与工程版）》
2009年第3期454-457,共4页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
国家973重大基础研究项目资助(批准号:5132102ZZT32)
关键词
高阶统计量
谱估计
自回归模型
混响
higher-order statistics
spectral estimation
auto-regressive model
reverberation
