Synthetic Aperture Radar Target-Recognition Method Based on Bidimensional Empirical Mode Decomposition

Xiaowen Liu; Juncheng Lei; Yanpeng Wu

doi:10.3788/LOP57.041004

Laser & Optoelectronics Progress, Volume. 57, Issue 4, 041004(2020)

Synthetic Aperture Radar Target-Recognition Method Based on Bidimensional Empirical Mode Decomposition

Xiaowen Liu¹, Juncheng Lei¹, and Yanpeng Wu^2、*

Author Affiliations

¹Departanment Information Engineering, Shaoyang University, Shaoyang, Hunan 422000, China

²Department of Information Science and Engineering, Hunan First Normal University, Changsha, Hunan 410205, China

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Figures & Tables(12)

Fig. 1. Illustration of decomposition of SAR images via BEMD. (a) Original image; (b) BIMF at first level; (c) BIMF at second level; (d) BIMF at third level

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Fig. 2. Illustration of classification principle of SVM

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Fig. 3. Basic procedure of SAR target recognition method based on BEMD

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Fig. 4. Optical and SAR images of ten targets in MSTAR data set. (a) BMP2; (b) BTR70; (c) T72; (d) T62; (e) BRDM2; (f) BTR60; (g) ZSU23/4; (h) D7; (i) ZIL131; (j) 2S1

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Fig. 5. Recognition results of proposed method under standard operating condition

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Fig. 6. Recognition performances of proposed and compared methods at different pitch angles

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Fig. 7. Recognition performances of proposed and compared methods under noise interference

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Table 1. Training and test samples under standard operating condition
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Table 1. Training and test samples under standard operating condition
Type BMP2 BTR70 T72 T62 BDRM2 BTR60 ZSU23/4 D7 ZIL131 2S1
Training 232(Sn_9566) 233 231(Sn_812) 299 298 256 299 299 299 299
Test 195(Sn_9563) 196 196(Sn_132) 273 274 195 274 274 274 274

Table 2. Training and test samples with configuration variances
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Table 2. Training and test samples with configuration variances
Type Training Test
BMP2 233(Sn_9563) 196(Sn_9566)196(Sn_c21)
BTR70 233(Sn_c71) 196(Sn_c71)
T72 232(Sn_132) 195(Sn_812)191(Sn_s7)

Table 3. Training and test samples with pitch angle difference
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Table 3. Training and test samples with pitch angle difference
Type Pitchangle /(°) 2S1 BDRM2 ZSU23/4 T72
Training 15 299 298 299 299
Test 30 288 287 288 288
45 303 303 303 303

Table 4. Recognition performance of proposed and compared methods under standard opearting condition
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Table 4. Recognition performance of proposed and compared methods under standard opearting condition
Method Average recognition rate /%
Proposed 99.12
SVM-PCA 97.26
SRC 96.36
CNN 98.68

Table 5. Recognition performance of proposed and compared methods under configuration variances
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Table 5. Recognition performance of proposed and compared methods under configuration variances
Method Average recognition rate /%
Proposed 98.06
SVM 95.43
SRC 94.88
CNN 97.03

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Xiaowen Liu, Juncheng Lei, Yanpeng Wu. Synthetic Aperture Radar Target-Recognition Method Based on Bidimensional Empirical Mode Decomposition[J]. Laser & Optoelectronics Progress, 2020, 57(4): 041004

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