数据采集与处理2024，Vol.39Issue(6)：1326-1332,7.DOI:10.16337/j.1004-9037.2024.06.003
一种基于相对熵的雷达测距估计方法
A Radar Ranging Estimation Method Based on Relative Entropy
摘要
Abstract
The maximum a posteriori(MAP)algorithm is the most commonly used parameter estimation method.However,the MAP algorithm focuses on the position of the maximum peak of the posterior distribution and does not fully utilize the complete information of the posterior distribution.This article proposes a minimum divergence(MD)radar ranging estimation method based on relative entropy.Firstly,the posterior distribution of the parameters is derived.Secondly,a distribution similar to them is constructed.Therefore,the value is estimated by finding the minimum value of their divergence.Simulation results indicate that in radar ranging scenarios,the MD algorithm achieves approximately 1 dB gain in performance compared to the MAP algorithm,demonstrating its superior estimation performance.关键词
参数估计/最小散度/最大后验/雷达测距Key words
parameter estimation/minimum divergence(MD)/maximum a posteriori(MAP)/radar ranging分类
信息技术与安全科学引用本文复制引用
鞠美玉,徐大专,许欢..一种基于相对熵的雷达测距估计方法[J].数据采集与处理,2024,39(6):1326-1332,7.基金项目
国家自然科学基金(62271254). （62271254）
