XX雷达杂波抑制方法研究
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摘要
作为某靶场主战装备的精密跟踪测量雷达,XX雷达目前由于工作环境的影响经常受到杂波的干扰,致使操作员不易分辨并快速捕获目标。为了解决这一问题,提出了XX雷达杂波抑制方法研究的课题,具有军事应用价值。
XX雷达是一部典型的单脉冲雷达,主要用于跟踪、测量速度及航路均已知的高速飞行物体。飞行物体的确定性所含有的先验知识是辨别、捕获目标的依据。为了有利于提取目标并抑制杂波,采用了将先验知识应用到了雷达信号处理中的思想。为了采集到真实的雷达信号以验证杂波抑制方法对XX雷达杂波抑制的有效性,对XX雷达视频信号的频率特性进行测量、分析,并在此基础上设计了基于数字存储示波器的数据采集系统,实现了对XX雷达视频信号的采集。根据小波变换能够处理非线性、非平稳雷达信号的特点,首先对小波变换工作原理、特点及小波基的选取等问题进行了研究,并应用小波变换实现了对XX雷达仿真信号的分解;接着根据先验知识在将提取的目标所在层用于信号重构的过程中,实现了目标的提取及杂波的抑制。对另一种时频信号分析工具HHT也进行了研究,并用HHT及先验知识对XX雷达仿真信号的分解与重构,实现了目标的提取和杂波抑制。
实验证明:XX雷达信号经过小波变换或者HHT处理后杂波得到了明显的抑制,在环型显示器上显示的目标回波也更加明亮、清晰,更有利于操作员的捕获及跟踪,较好地解决了XX雷达杂波抑制问题。
XX radar is a highly sophisticated target tracking and measuring device in one testing field. Because of the interference of clutter, this radar is greatly affected by the environment, which brings the human operators great difficulties in detecting and tracking the targets. To tackle this problem, studies are conducted on suppression methods of radar clutters in this paper.
XX radar is a conventional single-pulse radar for tracking flying objects of high speed and measuring their speeds under the assumption that their trajectories are known beforehand. The determinacy of the flying object provides a priori knowledge for classification and capturing of targets. To efficiently extracting target information and suppressing clutters, the idea of incorporating a priori knowledge into radar signal processing is proposed in this paper. Real-life radar data is obtained to validate our clutter suppression method on XX radar. The real-life XX radar image is sampled and analyzed based on our new design from the data extraction system in the digital storage oscillator. Considering the features that wavelet transforms is efficient in dealing with nonlinear and non-stationary radar signal, we, on one hand, study the theory of wavelet transform and its properties, and the selection of waveform basis. Waveform transform is then utilized to decompose the simulation date of XX radar afterward. On the other hand, we implement the target extraction and clutter suppression algorithm using the a priori knowledge in the process of target extraction and signal reconstruction. Another time-frequency analysis method, namely HHT, is also studied and used in the signal decomposition and reconstruction of XX radar simulation data, which also complete the target extraction and clutter suppression.
Experimental results show that when wavelet transform or HHT is employed to XX radar signal, the clutters can be obviously suppressed. The target echo shown on the PPI screen will appear brighter and clearer, which will facilitate the human operators to catch and track the target.
XX雷达是一部典型的单脉冲雷达,主要用于跟踪、测量速度及航路均已知的高速飞行物体。飞行物体的确定性所含有的先验知识是辨别、捕获目标的依据。为了有利于提取目标并抑制杂波,采用了将先验知识应用到了雷达信号处理中的思想。为了采集到真实的雷达信号以验证杂波抑制方法对XX雷达杂波抑制的有效性,对XX雷达视频信号的频率特性进行测量、分析,并在此基础上设计了基于数字存储示波器的数据采集系统,实现了对XX雷达视频信号的采集。根据小波变换能够处理非线性、非平稳雷达信号的特点,首先对小波变换工作原理、特点及小波基的选取等问题进行了研究,并应用小波变换实现了对XX雷达仿真信号的分解;接着根据先验知识在将提取的目标所在层用于信号重构的过程中,实现了目标的提取及杂波的抑制。对另一种时频信号分析工具HHT也进行了研究,并用HHT及先验知识对XX雷达仿真信号的分解与重构,实现了目标的提取和杂波抑制。
实验证明:XX雷达信号经过小波变换或者HHT处理后杂波得到了明显的抑制,在环型显示器上显示的目标回波也更加明亮、清晰,更有利于操作员的捕获及跟踪,较好地解决了XX雷达杂波抑制问题。
XX radar is a highly sophisticated target tracking and measuring device in one testing field. Because of the interference of clutter, this radar is greatly affected by the environment, which brings the human operators great difficulties in detecting and tracking the targets. To tackle this problem, studies are conducted on suppression methods of radar clutters in this paper.
XX radar is a conventional single-pulse radar for tracking flying objects of high speed and measuring their speeds under the assumption that their trajectories are known beforehand. The determinacy of the flying object provides a priori knowledge for classification and capturing of targets. To efficiently extracting target information and suppressing clutters, the idea of incorporating a priori knowledge into radar signal processing is proposed in this paper. Real-life radar data is obtained to validate our clutter suppression method on XX radar. The real-life XX radar image is sampled and analyzed based on our new design from the data extraction system in the digital storage oscillator. Considering the features that wavelet transforms is efficient in dealing with nonlinear and non-stationary radar signal, we, on one hand, study the theory of wavelet transform and its properties, and the selection of waveform basis. Waveform transform is then utilized to decompose the simulation date of XX radar afterward. On the other hand, we implement the target extraction and clutter suppression algorithm using the a priori knowledge in the process of target extraction and signal reconstruction. Another time-frequency analysis method, namely HHT, is also studied and used in the signal decomposition and reconstruction of XX radar simulation data, which also complete the target extraction and clutter suppression.
Experimental results show that when wavelet transform or HHT is employed to XX radar signal, the clutters can be obviously suppressed. The target echo shown on the PPI screen will appear brighter and clearer, which will facilitate the human operators to catch and track the target.
引文
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[18]水鹏朗,焦李成.混沌、噪声背景中信号的滤波检测方法.系统工程与电子技术. 1997(5): 1~4.
[19]李士伟. XX雷达角编码器与数据接口系统研究, [硕士学位论文].长春:吉林大学, 2007.
[20]周林,殷侠等.数据采集与分析技术.西安:西安电子科技大学出版社, 2005.
[21]马明建.数据采集与处理技术.西安:西安电子科技大学出版社, 2005. [22云雷.靶场测量雷达视频信号的采集、记录、传输与显示关键技术的研究, [硕士学位论文].长沙:国防科学技术大学, 2001.
[23] TDS1000B和TDS2000B系列数字存储示波器用户手册[Z]. Tektronix Inc, 2006.
[24]张亚标,程家明,阎世强等.一种雷达弱信号处理的视频回波数据采集系统.空军雷达学院学报, 2003, 17(1): 31~33.
[25]孙海善.基于DSP的雷达视频信号数字采集与检测.单片机与嵌入式系统应用, 2005, (6): 17-20.
[26]任太姝,李景文.天基雷达杂波谱估计及特性分析.雷达科学技术, 2007, 5(5): 324~328.
[27] Daubechies I, orthonormal.Bases of compactly supported wavelet.Common Pure ang Appl.Math, 1988, 41: 809-996.
[28]王国秋,全宏跃.最优多进Haar小波及在图像压缩中的应用.计算数学, 2009, 31(1): 99~109.
[29] Meyer Y. ondeletteset Operateurs.Pairs:Herman Press, 1991.1-175.
[30]徐义贤,王家映.基于连续小波变换的大地电磁信号谱估计方法.地球物理学报, 2000, 43(5): 677-683.
[31]程涛,厉鲁卫.基于小波变换的医学图像压缩技术.计算机与数字工程, 2009, 37(2) : 136~138.
[32]尹向宝.小波变换在激光超声无损检测信号去噪中的应用.实验室研究与探索, 2009, 28(1): 39~41.
[33]段虞荣,颜新祥,郑继明.运用多重分形和小波变换预测油气储量及确定勘探井位.高等学校应用数学学报, 1997, 12(1): 99-106.
[34]訾艳阳,何正嘉,张周锁.小波分形技术及其在机械设备非平衡故障诊断中的应用.西安交通大学学报, 2000, 34(9): 82-87.
[35]虞和济,陈长征等.基于神经网络的智能诊断.重庆:冶金工业出版社, 2000.
[36]张素萍,刘桥,王代强等.小波变换在雷达目标识别中的应用.机械与电子, 2009(1): 61~64. [37 ]彭玉华.小波变换与工程应用.北京:科学出版社, 1999.
[38]杨福生.小波变换的工程分析与应用.北京:科学出版社, 1999.
[39]秦前清.实用小波分析.西安:西安电子科技大学出版社, 1994.
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