弹头表面磨损形貌的分形研究

应用分形理论对弹头磨损表面形貌进行了研究,研究表明,其表面磨损形貌的不规则和随机分布性具有分形特征。应用轮廓仪对不同枪支发射子弹的弹头磨损表面进行数据采集并计算出其分形维数,其研究结果表明:不同枪支发射子弹时,造成弹头表面磨损程度不同,其分形维数也不同。因此可将其分形维数作为描述弹头表面磨损程度特征量,会比较有效、方便地分析弹头表面形貌变化的特点,为推断发射子弹枪支提供了依据,也为弹头痕迹的量化检验进行了一种新的探索。

Range Profile Target Recognition Using Sparse Representation Based on Feature Space

A novel method is presented to improve the recognition rate of warhead in this paper. Firstly, a tool for electromagnetic calculation, like CST Microwave Studio, is used to simulate the frequency response of the electromagnetic scattering. Secondly, the echo and further the range profile are acquired from the frequency response by further processing. Thirdly, a set of discriminative features is extracted from the range profiles of the target. Fourthly, these features are used to construct a dictionary for the sparse representation classifier. Finally, the sample of the target can be classified by solving the sparsest coefficients. Since the reconstruction result is determined by a linear combination of the training samples, this method has a good robustness for the variable features. By formulating the problem within a feature-based sparse representation framework, the presented method combines the discriminative features of each sample during the sparse recovery process rather than in a postprocessing manner. Moreover, based on the feature representation space rather than a single feature or image pixel, the constructed dictionary exhibits both strong expressive and discriminative powers that can enhance the classification performance of the test sample. A series of test results based on the simulated data demonstrates the effectiveness of our method. © 2017, Shanghai Jiaotong University and Springer-Verlag GmbH Germany.