Research On The Technologies Of Fragment Velocity Parameter Measurement Based On Millimeter-wave Array Radar

The measurement of start velocity and coefficient of velocity attenuation of fragments from static explosion test of fragment warhead is an important and complicated test item at shooting range. To realize the velocity measurement of shooting range fragments, a methodology using millimeter-wave array radar to obtain the velocity parameter measurement and estimation of near-field moving fragments is presented in this dissertation. Five main subjects have been researched, which are the spatial specrum estimation techniques, the optimization of linear array, array manifold calibration, the velocity parameter estimation algorithm of moving fragments and the realization of the millimeter-wave velocity measurement system for shooting range fragments.Firstly, the research background and significance is introduced, and the shooting range velocity measuring system, the development of millimeter-wave continuous wave radar and spatial specrum estimation techniques are reviewed. The advantages and disadvantages of the common shooting range velocity measurement methods at home and abroad are compared and analyzed in detail. The problems of these methods in measuring velocity parameters of the fragments are pointed out.The mathematical models of far-field and near-field narrowband signal are deduced. Two subspace-based spatial spectrum estimation methods, maximum likelihood method and the Cramér-Rao bound for spatial spectrum are introduced.In order to solve the optimization of linear array, a novel array optimization method is presented, which takes the improvement of the direction-of-arrival angle(DOA) estimation performance as the optimization goal. Compared with the conventional method based on the peak side lobe level (PSLL), the method presented performs more efficiently. Computer simulations verify this conclusion.The calibration methods for unequal gain and phase responses, and the small errors in element positions are researched. In order to neglect the mutual coupling and simplify the array model calibration, the physical separations of the array elements in use exceed a few wavelengths designedly. Two calibration methods are presented, which calibrate the array with large channel phase errors and small channel phase errors, respectively. When the channel phase errors are large, the DOAs of the pilot sources are calculated through rotating the array twice with the same angle, and the gain/phase perturbation matrix and element position errors can be estimated. When the channel phase errors are small, the uncalibrated DOA of the pilot source, which is located at the orthogonal direction of the array boresight, is taken for the actual DOA. Then the array model errors are estimated.A fragment velocity parameter estimation algorithm is presented, which is based on the millimeter-wave array radar. According to the different Doppler frequencies of moving fragments, the echo signals of the fragments are separated. Then the location of these fragments are estimated, respectively. Using the Doppler frequencies of each fragement relative to the array elements, the fragement velocity estimation can be obtained. Finally, the start velocity and coefficient of velocity attenuation of fragment are estimated according to the velocities of different times. Several frequency estimation algorithms along with signal separation methods are introduced. The Cramér-Rao bounds of frequency estimation and fragement location estimation are also deduced. According to the simulation results, use ML method to estimate the frequency and separate the echo signals finally. The simulation results of start velocity and coefficient of velocity attenuation estimations prove the validity of the proposed algorithm.A millimeter-wave fragment velocity parameter measurement system is designed. The measurement principle of this system is introduced. The system architecture and design of the components are also described. Finally, satisfied results are obtained through the darkroom test experiments, including the location estimation of fixed sources and the velocity estimation of moving source.