西安电子科技大学学报 ›› 2023, Vol. 50 ›› Issue (6): 21-33.doi: 10.19665/j.issn1001-2400.20231003

• 电磁空间安全专栏 • 上一篇    下一篇

外辐射源雷达互模糊函数智能快速计算方法

车吉斌(),王常龙(),贾岩(),任紫正(),刘春恒(),周峰()   

  1. 西安电子科技大学 电子信息攻防对抗与仿真技术教育部重点实验室,陕西 西安 710071
  • 收稿日期:2023-02-02 出版日期:2023-12-20 发布日期:2024-01-22
  • 通讯作者: 王常龙(1988—),男,副教授,E-mail:wangchanglong@xidian.edu.cn
  • 作者简介:车吉斌(1984—),男,西安电子科技大学博士研究生,E-mail:19022110609@stu.xidian.edu.cn;|贾岩(1998—),男,西安电子科技大学硕士研究生,E-mail:jasonjiay@stu.xidian.edu.cn;|任紫正(1999—),男,西安电子科技大学硕士研究生,E-mail:21021210744@stu.xidian.edu.cn;|刘春恒(1977—),男,教授,E-mail:chunhengliu@163.com;|周峰(1980—),男,教授,E-mail:fzhou@mail.xidian.edu.cn
  • 基金资助:
    国家自然科学基金(61801344);国家自然科学基金(61801347);国家自然科学基金(61631019);国家自然科学基金(61201418);国家自然科学基金(62001350);国家自然科学基金(62101412)

Fast algorithm for intelligent optimization of the cross ambiguity function of passive radar

CHE Jibin(),WANG Changlong(),JIA Yan(),REN Zizheng(),LIU Chunheng(),ZHOU Feng()   

  1. Key Ministry of Education Laboratory of Electronic Information Countermeasure and Simulation Technology,Xidian University,Xi’an,710071,China
  • Received:2023-02-02 Online:2023-12-20 Published:2024-01-22

摘要:

互模糊运算是外辐射源雷达系统中回波信号与参考信号相干积累的重要手段,然而,外辐射源雷达接收到的目标回波信号非常微弱,需要增加积累时间来提高估计精度;当目标速度较快时,频率搜索范围增加。为了实现一定范围的目标检测需求并兼顾数据处理的实时性,研究互模糊函数快速计算方法具有重要的意义。由于长时间积累与大范围空域搜索的客观需求,导致互模糊函数运算量极大,需要消耗大量计算资源。针对以上问题,通过分析典型静止轨道数字电视信号模糊函数的特点,以粒子群优化理论为框架,设计了一种多种群特征寻优时频差估计算法。该方法引入多种群迭代机制和收缩因子,通过设计有效的搜索策略和粒子更新方法,避免了传统方法冗余计算量大的问题。在保证计算精度的前提下,该方法大幅度减少了模糊函数的计算量,提高了互模糊函数计算搜索效率,大幅度减少了所需的计算量。

关键词: 外辐射源雷达, 互模糊函数, 粒子群优化, 目标检测

Abstract:

The passive radar system realizes the target detection by receiving the direct wave signal from the emitter and the target echo signal.The cross ambiguity function is an important means to improve the coherent accumulation of the echo signal.However,the echo signal received by the passive radar is very weak,so it is necessary to increase the accumulation time to improve the estimation accuracy.When the target speed is fast,the frequency search range increases.In order to achieve a range of target detection requirements and take into account the real-time performance of data processing,it is of great significance to study the fast calculation method of the cross ambiguity function,and due to the objective requirements of long-time accumulation and large-scale time-frequency search,the computation of the cross ambiguity function is huge,which makes it difficult for the traditional accelerated calculation method based on ergodic search to meet the real-time requirements of system processing.In order to improve the efficiency of cross ambiguity function optimization,a time-frequency difference calculation method based on multi-group feature optimization is proposed in this paper.By deeply analyzing the characteristics of typical digital TV signals,a two-stage cross ambiguity intelligent optimization fast calculation method based on target characteristics is designed in the framework of particle swarm optimization theory.By designing an effective search strategy,this method introduces the multi-population iteration mechanism and shrinkage factor,which avoids the disadvantages of the traditional method of redundant computation.On the premise of ensuring the calculation accuracy,the time-frequency point calculation is greatly reduced,and the search efficiency of cross ambiguity function is improved.

Key words: passive radar, ambiguity function, particle swarm optimization, target detection

中图分类号: 

  • TN959.16