A Maximum Likelihood Time Delay Estimation Algorithm Using Monte Carlo Method

doi:10.7652/xjtuxb201508005

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A Maximum Likelihood Time Delay Estimation Algorithm Using Monte Carlo Method

更新时间：2025-07-09

- A Maximum Likelihood Time Delay Estimation Algorithm Using Monte Carlo Method
- Vol. 49, Issue 8, Pages: 24-30(2015)
- 作者机构：
  
  解放军信息工程大学导航与空天目标工程学院,郑州,450001
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201508005
  CLC： TN911.7
- Online First：10 August 2015，
  
  Published：2015
- 稿件说明：
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A Maximum Likelihood Time Delay Estimation Algorithm Using Monte Carlo Method[J]. 2015, 49(8): 24-30.
DOI：

A Maximum Likelihood Time Delay Estimation Algorithm Using Monte Carlo Method[J]. 2015, 49(8): 24-30. DOI： 10.7652/xjtuxb201508005.

摘要

针对最大似然时延估计算法的峰值搜索计算复杂度较高且容易陷入局部收敛

造成估计误差较大的问题。提出了一种利用蒙特卡罗的最大似然时延估计(MCML)算法。首先利用信道频域响应估计矢量建立似然函数; 然后把时延估计问题转化为求解随机变量的期望问题

将采用指数化似然函数构造的标准化概率密度函数趋近于冲激函数

使得随机变量的方差趋近于零; 最后采用蒙特卡罗方法对随机变量进行抽样

从而利用抽样的均值估计出时延。较之传统方法

蒙特卡罗方法避免了网格搜索

降低了计算复杂度

保证了全局收敛性和估计精度。仿真结果表明:在信噪比0～25 dB的条件下

MCML算法均能始终逼近克拉美罗界; 当信噪比为25 dB时

MCML算法的时延估计分布范围缩小为马尔科夫链蒙特卡罗算法的34%。

Abstract

A maximum likelihood time delay estimation algorithm using Monte Carlo method(MCML)is proposed to solve the problems that the maximum likelihood delay algorithm has high computational complexity due to peak searching and is easy to fall into local convergence. A likelihood function is constructed by using the channel response estimation vector in frequency domain. Then the MCML translates the time delay estimation into the expectation of a random variable

and a standardization probability density function is built from the index likelihood function to approximate an impulse function

and to make the variance of the random variable approach zero. Finally

the random variable is sampled using the Monte Carlo method

and the time delay is estimated from sampling mean. Compared with the traditional methods

the MCML avoids the grid search

reduces the computational complexity

and ensures the global convergence and estimation accuracy. Simulation results show that the MCML is always close to Cramer-Rao bound

and the time delay estimation range of the MCML is 34% of the MCMC's range when the signal to noise ratio is from 0 dB to 25 dB.

关键词

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references

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