Micro-motion Parameter Estimation Of Ballistic Target In Midcourse For Narrow-Band Radar System

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.