一种频域自适应最大似然时延估计算法

A Frequency Domain Adaptive Maximum Likelihood Delay Estimation Algorithm

提出了一种基于平方相干函数的频域自适应最大似然时延估计算法。该算法构造了一种广义相位数据最大似然加权函数,并通过自适应估计输入信号的平方相干函数加以实现。算法的性能分析和仿真实验表明,该算法有更好的时延估计精度、收敛速度和跟踪性能,能够有效提高低信噪比环境下的低空目标被动声探测的时延估计性能。

A frequency domain adaptive maximum likelihood (ML) time delay estimation algorithm based on squared coherence function is proposed. The method is realized through the estimation of the squared coherence function of input signals by two frequency domain adaptive filters. A new maximum likelihood weighting function of generalized phase data is constructed. By the analysis, it is shown that the estimation variance of the new algorithm is half of that of the frequency domain adaptive ML delay estimator. Finally, simulations on the noise data from a helicopter are conducted, which demonstrate that the new method provides more efficient estimation than the frequency domain adaptive ML delay estimator.\;