窄带雷达体制下弹道中段目标微动参数估计
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摘要
弹道中段的目标存在微动,对微动特征的提取为弹道导弹防御目标识别提供了新的解决手段。本文针对弹道中段旋转对称的目标,深入研究了窄带雷达体制下目标微动特征的提取,改进了进动周期和章动角的估计方法,提出了目标质心位置的估计方法。研究成果主要包括如下几个方面:
1.研究了基于自相关函数凸包的目标进动周期估计方法。自相关法可用于估计目标的进动周期,它需要预先给出进动周期的上下限。然而进动周期下限可能远小于真实进动周期,此时自相关法的估计性能将严重下降。本文首先定义了自相关函数的凸包,然后在此基础上提出了一种改进的自相关法。当进动周期下限和真实进动周期相差倍数不大时,该方法的估计性能接近传统的自相关法;当进动周期下限和真实进动周期相差倍数很大时,它仍然具有良好的估计性能。该方法原理简单,对先验信息的要求非常宽松,且计算量增大的倍数通常很小。因此它具有广泛的适用性。
2.研究了基于相关匹配的目标章动角估计方法。将观测的RCS序列与RCS序列模板进行最小二乘匹配,可以得到目标章动角的估计值,但由于未考虑RCS测量的系统误差,最小二乘匹配的估计性能得不到保证。本文提出了基于相关匹配的目标章动角估计方法,并给出了具体的实现算法。该方法考虑了RCS测量的系统误差,其估计性能远优于最小二乘匹配。本文分析了全姿态RCS数据的角度采样间隔对相关匹配估计性能的影响,并比较了多层相关匹配和单层相关匹配的估计性能和计算量,最后比较了进动周期已知和未知情况下相关匹配的估计性能。
3.研究了基于相位特性的目标质心位置估计方法。本文首次提出了目标质心位置估计方法:平动补偿法和非线性变换法。它们都基于窄带雷达回波的相位特性。仿真结果表明:平动补偿法和非线性变换法都是有效的质心位置估计方法;前者估计性能优于后者,但其计算量远大于后者。本文分析了全姿态散射系数数据的角度采样间隔对两种方法估计性能的影响,分别就不同方法比较了姿态角序列已知和未知情况下的估计性能。
本文提出的弹道中段目标微动参数估计方法,丰富了微动特征提取的理论体系,对弹道中段目标识别具有重要的理论意义和应用价值。
The ballistic target in midcourse undergoes micro-motion. The extraction of the micro-motion feature offers new measures for target recognition in ballistic missile defense. In this dissertation, the micro-motion feature extraction is investigated using narrow-band radar systems for rotationally symmetric ballistic target in midcourse. Precession period and nutation angle estimation methods are improved, and target centroid position estimation method is proposed. Main contributions can be summarized as follows:
1. Target precession period estimation method is studied based on the convex hull of autocorrelation function. The autocorrelation method can be used to estimate the precession period of the target, for which it is necessary that the upper and lower bounds of the precession period be given in advance. However, the lower bound of the precession period provided may be far less than the true precession period, which will seriously degrade the estimation performance. An improved autocorrelation method is proposed by defining the convex hull of the autocorrelation function (ACF). The estimation performance of the proposed method is close to that of the autocorrelation method when the lower bound is not far less than the true precession period. Moreover, the proposed method has good estimation performance when the lower bound is far less than the true precession period. The principle of the proposed method is simple. And it is very easy to meet the prior information requirement for the proposed method. Usually the increase of the computational burden of the proposed method over the autocorrelation method is small. Therefore the proposed method can be used widely.
2. Target nutation angle estimation method is studied based on correlation matching. The least square matching is performed with the measured radar cross section (RCS) series and the RCS series templates, and then the nutation angle of the target is estimated. But the estimation peformance of the least square matching cannot be guaranteed because of the systematic errors in the RCS measurement. A correlation matching based nutation angle estimation method is proposed. Also the implementation of the proposed method is detailed. The proposed method takes into consideration of the systematic errors in the RCS measurement, and the estimation performance is far superior to that of the least square matching. The angle sampling interval for the all-attitude RCS data can affect the estimation performance of the correlation matching, and its effect is analyzed. Also, the estimation performance and computational burden of the multi-stage correlation matching is compared with that of the one-stage correlation matching. Finally, the correlation matching estimation performance with priorlily known precession period is compared with that with unknown precession period.
3. Target centroid position estimation method is studied based on phase signature. Target centroid position estimation method is proposed for the first time: translation compensation method and nonlinear transform method. The proposed methods are both based on the phase signature of the narrow-band radar echo. Simulation results show that translation compensation method and nonlinear transform method are both effective centroid position estimation method. The estimation performance of the former method is superior to that of the the latter method, but the computational burden of the former method is much heavier than that of the latter method. The angle sampling interval for the all-attitude scattering coefficient data can affect the estimation performance of both methods, and its effect is analyzed. Finally, for both methods the estimation performance with known or unknown attitude angle series is compared.
These micro-motion parameter estimation methods enrich the theory system of micro-motion feature extraction, and have great values in theory and application for ballistic target recognition in midcourse.
1.研究了基于自相关函数凸包的目标进动周期估计方法。自相关法可用于估计目标的进动周期,它需要预先给出进动周期的上下限。然而进动周期下限可能远小于真实进动周期,此时自相关法的估计性能将严重下降。本文首先定义了自相关函数的凸包,然后在此基础上提出了一种改进的自相关法。当进动周期下限和真实进动周期相差倍数不大时,该方法的估计性能接近传统的自相关法;当进动周期下限和真实进动周期相差倍数很大时,它仍然具有良好的估计性能。该方法原理简单,对先验信息的要求非常宽松,且计算量增大的倍数通常很小。因此它具有广泛的适用性。
2.研究了基于相关匹配的目标章动角估计方法。将观测的RCS序列与RCS序列模板进行最小二乘匹配,可以得到目标章动角的估计值,但由于未考虑RCS测量的系统误差,最小二乘匹配的估计性能得不到保证。本文提出了基于相关匹配的目标章动角估计方法,并给出了具体的实现算法。该方法考虑了RCS测量的系统误差,其估计性能远优于最小二乘匹配。本文分析了全姿态RCS数据的角度采样间隔对相关匹配估计性能的影响,并比较了多层相关匹配和单层相关匹配的估计性能和计算量,最后比较了进动周期已知和未知情况下相关匹配的估计性能。
3.研究了基于相位特性的目标质心位置估计方法。本文首次提出了目标质心位置估计方法:平动补偿法和非线性变换法。它们都基于窄带雷达回波的相位特性。仿真结果表明:平动补偿法和非线性变换法都是有效的质心位置估计方法;前者估计性能优于后者,但其计算量远大于后者。本文分析了全姿态散射系数数据的角度采样间隔对两种方法估计性能的影响,分别就不同方法比较了姿态角序列已知和未知情况下的估计性能。
本文提出的弹道中段目标微动参数估计方法,丰富了微动特征提取的理论体系,对弹道中段目标识别具有重要的理论意义和应用价值。
The ballistic target in midcourse undergoes micro-motion. The extraction of the micro-motion feature offers new measures for target recognition in ballistic missile defense. In this dissertation, the micro-motion feature extraction is investigated using narrow-band radar systems for rotationally symmetric ballistic target in midcourse. Precession period and nutation angle estimation methods are improved, and target centroid position estimation method is proposed. Main contributions can be summarized as follows:
1. Target precession period estimation method is studied based on the convex hull of autocorrelation function. The autocorrelation method can be used to estimate the precession period of the target, for which it is necessary that the upper and lower bounds of the precession period be given in advance. However, the lower bound of the precession period provided may be far less than the true precession period, which will seriously degrade the estimation performance. An improved autocorrelation method is proposed by defining the convex hull of the autocorrelation function (ACF). The estimation performance of the proposed method is close to that of the autocorrelation method when the lower bound is not far less than the true precession period. Moreover, the proposed method has good estimation performance when the lower bound is far less than the true precession period. The principle of the proposed method is simple. And it is very easy to meet the prior information requirement for the proposed method. Usually the increase of the computational burden of the proposed method over the autocorrelation method is small. Therefore the proposed method can be used widely.
2. Target nutation angle estimation method is studied based on correlation matching. The least square matching is performed with the measured radar cross section (RCS) series and the RCS series templates, and then the nutation angle of the target is estimated. But the estimation peformance of the least square matching cannot be guaranteed because of the systematic errors in the RCS measurement. A correlation matching based nutation angle estimation method is proposed. Also the implementation of the proposed method is detailed. The proposed method takes into consideration of the systematic errors in the RCS measurement, and the estimation performance is far superior to that of the least square matching. The angle sampling interval for the all-attitude RCS data can affect the estimation performance of the correlation matching, and its effect is analyzed. Also, the estimation performance and computational burden of the multi-stage correlation matching is compared with that of the one-stage correlation matching. Finally, the correlation matching estimation performance with priorlily known precession period is compared with that with unknown precession period.
3. Target centroid position estimation method is studied based on phase signature. Target centroid position estimation method is proposed for the first time: translation compensation method and nonlinear transform method. The proposed methods are both based on the phase signature of the narrow-band radar echo. Simulation results show that translation compensation method and nonlinear transform method are both effective centroid position estimation method. The estimation performance of the former method is superior to that of the the latter method, but the computational burden of the former method is much heavier than that of the latter method. The angle sampling interval for the all-attitude scattering coefficient data can affect the estimation performance of both methods, and its effect is analyzed. Finally, for both methods the estimation performance with known or unknown attitude angle series is compared.
These micro-motion parameter estimation methods enrich the theory system of micro-motion feature extraction, and have great values in theory and application for ballistic target recognition in midcourse.
引文
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