Fast Parameter Estimation of Multi-function Radar Based on Syntactic Derivation of Parse Chart

DAI Li-peng; WANG Bu-hong; SHEN Hai-ou; JIA Yue-ling

doi:10.3969/j.issn.0372-2112.2016.02.021

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Fast Parameter Estimation of Multi-function Radar Based on Syntactic Derivation of Parse Chart

更新时间：2025-07-16

- Fast Parameter Estimation of Multi-function Radar Based on Syntactic Derivation of Parse Chart
- Acta Electronica Sinica Vol. 44, Issue 2, Pages: 392-397(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. 空军工程大学装备管理与安全工程学院,陕西,西安,710077
  3. 空军工程大学信息与导航学院,陕西,西安,710077
  4. 空军工程大学装备管理与安全工程学院,陕西,西安,710077
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2016.02.021
  CLC： TN918.1
- Published：2016
- 稿件说明：
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DAI Li-peng, WANG Bu-hong, SHEN Hai-ou, et al. Fast Parameter Estimation of Multi-function Radar Based on Syntactic Derivation of Parse Chart[J]. Acta Electronica Sinica, 2016, 44(2): 392-397.
DOI：

DAI Li-peng, WANG Bu-hong, SHEN Hai-ou, et al. Fast Parameter Estimation of Multi-function Radar Based on Syntactic Derivation of Parse Chart[J]. Acta Electronica Sinica, 2016, 44(2): 392-397. DOI： 10.3969/j.issn.0372-2112.2016.02.021.

摘要

随机上下文无关文法(SCFG)在多功能雷达(MFR)状态识别和威胁估计中具有良好的应用前景.为了减少常规算法的运算复杂度

本文提出一种基于解析表构造的多功能雷达参数快速估计方法.该方法通过对截获的每个雷达数据序列构造库克-杨-卡塞米(CKY)解析表

排除了大量未参与序列派生过程的产生式

随后在解析表的基础上采用改进的Inside-Outside(IO)算法对雷达文法产生式概率和多功能雷达状态进行快速估计.理论分析与实验仿真证明

该算法在参数估计精度相同的条件下

其运算时间相对于常规IO算法和Viterbi-Score(VS)算法减少了50%以上.

Abstract

Stochastic context-free grammar (SCFG) has a promising application prospect in the field of mode recognition and threat estimation of multi-function radars (MFR).The primary limitation of the existing learning algorithms is their huge computing complexity.A fast learning algorithm for the parameters of MFR grammar is proposed

in which the Cocke-Younger-Kasami(CKY) parsing chart is first pre-computed for each training sequence to delete the rules that are not involved in the signal generation.Finally

the estimation of radar grammar parameters is realized with a modified inside-outside (IO) algorithm.The computing complexity is theoretically analyzed

moreover

simulation experiments are provided to verify the algorithm efficiency.Compared with the conventional IO and Viterbi-score (VS) algorithms

more than half operation time is reduced with our proposed algorithm while the favorable estimation accuracy is maintained.

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