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.
L ¨U Wentao1* (吕文涛), WANG Junfeng2 (王军锋), YU Wenxian2 (郁文贤), BAO Xiaomin1 (包晓敏)
. Range Profile Target Recognition Using Sparse Representation Based on Feature Space[J]. Journal of Shanghai Jiaotong University(Science), 2017
, 22(5)
: 615
-623
.
DOI: 10.1007/s12204-017-1879-4
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