Study On Radar Target Recognition And Its Evaluation In Ballistic Midcourse

In missile defense program, the midcourse of trajectory is the most difficult phase for alleging fraud. As the main sensor, the ground-based radar represents the classification capability of the missile defence system to a great extent. Making researche on radar target recognition and evaluation in midcourse is provided with great significance not only for developing new-type radar, but also for promoting the surviving and penetrating ability for our ballistic missile.This dissertation is sponsored by several funds, including the fund of national excellent dissertation, the 973 momentous foundation fund of nation security and the advance research fund of general equipment office. Under the background of ballistic missiles' penetration, a series of key technique of radar target recognition are invested systematically, including the radar signature of midcourse objects, the method of feature extraction, the method of pattern recognition and the method of evaluation. By using static measurement data and simulating the real scene of recognition, the dissertation establishes a platform of dynamic recognition, on which recognition and evaluation for typical scenario of ballistic missile penetration in midcourse are investigated and valuable results are obtained.The study on signature of radar target is a foundation for feature extraction. So, the radar signatures of midcourse objects are studied at first. After the movement feature of midcourse objects analyzed in theory, a novel approach is proposed, which can silmulate the dynamic scattering feature of midcourse objects. Lastly, the narrowband signatures and wideband signatures of warhead and decoy are analyzed through the proposed method.Feature extraction plays a key role in radar target recognition, and is thoroughly analyzed in this dissertation. A series of feature extraction methods are put forward, including the RCS periodicity estimation algorithms based on narrowband echoes, the moving feature extraction algorithms based on narrowband and wideband echoes, the shape feature extraction algorithms based on wideband echoes. Through those methods, many features of midcourse objects are obtained, such as the length, the nutation rate, the velocity and range of object relative to radar, and so on, which facilitate subsequent alleging fraud.ISAR imaging of ballistic target is an important means of distinguishing decoy. Based on the signature analysis of wideband echo of moving objects with high velocity in midcourse, the compensation methods for high-resolution rangeprofile (HRRP) and for residual video phase (RVP) are presented detailedly. And then, a new ISAR imaging algorithm is proposed based on the unitary ESPRIT technique, which improves ISAR imaging evidently with a reduced computational burden. After estimating the range and rotation angle of ISAR imaging, the dissertation analyzes the ISAR image characteristic of warhead, by using measurement experimental data. Lastly, the approach to extraction ISAR image feature of warhead is presented.The design and evaluation on classifier are pivotal steps in target recognition. Two classifiers, the fuzzy classifier based on multi-feature fusion and the classifier based on decision tree, are proposed for alleging fraud in view of the absence of apriori information.On the other hand, two evaluation approaches, the evaluation approach based on separability criterion and the evaluation approach based on fuzzy theory are put forward to evaluate the extracted features. Furthermore, the dissertation also makes contributions towards the evaluation of radar target recognition classification systems.The work of the dissertation is focused on research of radar target rcognition and evaluation in midcourse. Some valuable results which bring forth new ideas are achieved. The main creativeness is listed as the following:1. After the kinetic characteristic of target in midcourse anlyzed thoroughly, by using static measurement data, a novel simulation approach to dynamic scattering signature of radar target is proposed, which provides a solution to the absence of real recognition data;2. On the basis of feature extraction study of midcourse objects in the round, many new feature extraction methods are presented, including the methods of extracting movement feature and the methods of extracting shape feature of objects, which facilitate later alleging fraud;3. The dissertation makes a deep research on ISAR imaging of ballistic objects in midcourse. After the range and coherent accumulating time for imaging are discussed, the. dissertation analyzes the peculiarity of warhead image and presentes the corresponding feature extraction method. In addition, a new ISAR imaging algorithm is proposed based on the unitary ESPRIT;4. Considering the absence of apriori information, the dissertation designs the fuzzy classifer based on multi-feature fusion and the classifier based on decision tree, both of which are suitable for discriminating decoy because they only need simple apriori information;5. Multiple evaluation methods are demonstrated for feature and classifier evaluation, such as the feature evaluation method based on separability criterion and the classifer evaluation method based on confidence. Those methods provide theoretic support and feasible means for designing, choosing and combining classifiers. The dissertation not only attaches lots of importance to theory research, at the same time, by taking the advantage of measurement data and simulation means, it also performs lots of simulation experimentation to test the proposed theories and methods.At last, we must point out that the research in the dissertation stems from practical projects, and its conclusion and methods are mostly applied in practice with fairly good effects.