Micro-motion Parameters Estimation for Truck Target Based on Dynamic Dictionary

LI Kai-ming; ZHANG Qun; LEI Lei; LUO Ying

doi:10.3969/j.issn.0372-2112.2016.11.008

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Micro-motion Parameters Estimation for Truck Target Based on Dynamic Dictionary

更新时间：2025-07-16

- Micro-motion Parameters Estimation for Truck Target Based on Dynamic Dictionary
- Acta Electronica Sinica Vol. 44, Issue 11, Pages: 2618-2624(2016)
- 作者机构：
  
  1. 空军工程大学信息与导航学院,陕西,西安,710077
  2. 空军工程大学训练部,陕西,西安,710051
  3. 西安电子科技大学雷达信号处理重点实验室,陕西,西安,710071
  4. 空军工程大学信息与导航学院,陕西,西安,710077
  5. 空军工程大学训练部,陕西,西安,710051
  6. 西安电子科技大学雷达信号处理重点实验室,陕西,西安,710071
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61471386);Shaanxi Provincial Coordinated Innovation Project - Characteristic Industry Innovation Chain Program (No.S2015TDGY0045)
- DOI：10.3969/j.issn.0372-2112.2016.11.008
  CLC： TN957
- Published Online：25 November 2016，
  
  Published：2016
- 稿件说明：
移动端阅览
LI Kai-ming, ZHANG Qun, LEI Lei, et al. Micro-motion Parameters Estimation for Truck Target Based on Dynamic Dictionary[J]. Acta Electronica Sinica, 2016, 44(11): 2618-2624.
DOI：

LI Kai-ming, ZHANG Qun, LEI Lei, et al. Micro-motion Parameters Estimation for Truck Target Based on Dynamic Dictionary[J]. Acta Electronica Sinica, 2016, 44(11): 2618-2624. DOI： 10.3969/j.issn.0372-2112.2016.11.008.

摘要

车轮旋转产生的微多普勒是轮式车辆独特的特征.卡车类目标微动参数提取，可为地面车辆目标的分类识别提供重要依据.（1）对窄带雷达信号下的卡车目标进行回波建模，推导了车身非旋转散射点多普勒和轮毂旋转散射点微多普勒的数学表达式；（2）利用旋转点的微动参数构造相应的字典库进行匹配分解，建立了噪声条件下微动参数提取的凸优化模型；（3）针对采用过完备字典方法进行参数提取时，维数过大带来的计算和存储负担问题，进一步推导出关于微动参数集的凸函数，构造出更小规模的动态字典，通过对字典的动态调整和最小二乘准则下的迭代逼近，较快实现了卡车目标微动参数的准确估计；（4）仿真验证了方法的有效性和稳健性.

Abstract

Micro-Doppler generated by rotation of wheels is a unique characteristic of wheeled vehicles.Extraction of micro-motion parameters of truck

etc.will offer important proof for classification and recognition of ground vehicles.Firstly

the echoes model of truck was established under narrowband signal

the mathematic expressions of Doppler induced by non-rotation scatterers and micro-Doppler induced by rotation scatterers were deduced.Secondly

corresponding dictionary bank consists of micro-motion parameters was constructed for matching pursuit

and convex optimization model under noisy condition was established for extraction of micro-motion parameters.Thirdly

for avoiding the heavy computation and storage burden induced by parameters extraction based on overcomplete dictionary

the smaller dynamic dictionary was structured after deduction of the convex function about micro-motion parameters set

the accurate and faster parameters estimation was obtained by dynamic adaptation of the dictionary and iterative approach to optimal solution under Least Square criteria.The effectiveness and robustness of the method were proved by the simulation results.

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Related Institution

PLANo. TroopFuzhouFujian 350000China

Key Laboratory of Wave Scattering and Remote Sensing Information (Ministry of Education)Fudan UniversityShanghai 200433China

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No.95813 Troop,Fuzhou

Key Laboratory of Wave Scattering and Remote Sensing Information (Ministry of Education),Fudan University

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