Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (4): 537-548.doi: 10.23940/ijpe.20.04.p5.537548
• Orginal Article • Previous Articles Next Articles
Dan Bo*, Shan Gao, and Zhihong Ji
Submitted on
;
Revised on
;
Accepted on
Contact:
Dan Bo
About author:
Shan Gao is an associate research fellow at the Naval Aviation University of China. His research interests include semi-supervised machine learning and information analysis.Bo Dan, Shan Gao, and Zhihong Ji. Ship Target Recognition Technology of Radar High Resolution Range Profile based on Machine Learning [J]. Int J Performability Eng, 2020, 16(4): 537-548.
Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks
1. | H. J.Li and S. H. Yang, “Using Range Profile as Feature Vectors to Identify Aerospace Objects,” Journal of IEEE Transactions on Antennas and Propagation, Vol. 41, No. 3, pp. 261 - 268, March 1993 |
2. | A. Zyweck and R. E. Bogner, “Radar Target Classification of Commercial Aircraft,” Journal of IEEE Transactions on Aerospace and Electronics Systems,Vol. 32, No. 2, pp. 598-606, April 1996 |
3. | P. Kosir, R. DeWall,R. A. Mitchell, “A Multiple Measurement Approach for Feature Alignment”, inProceedings of the IEEE 1995 National Aerospace and Electronics Conference, pp. 22-26, Dayton, USA, May 1995 |
4. | S. P. Jacobs, “Automatic Target Recognition using Sequences of High Resolution Radar Profiles,” Journal of IEEE Transactions on Aerospace and Electronic Systems, Vol. 36, No. 2, pp. 364-381, April 2000 |
5. | A. R. Webb, “Gamma Mixture Models for Target Recognition,” Journal of Pattern Recognition, Vol. 33, No. 12, pp. 2045-2054, June 2000 |
6. | X. Zhang, Y. Shi,Z. Bao, “A New Feature Vector using Selected Bispectra for Signal Classification with Application in Radar Target Recognition,” Journal of IEEE Transactions on Signal Processing, Vol. 49, No. 9, pp. 1875-1885, September 2001 |
7. | L. Du, H. W. Liu,Z. Bao, “Radar HRRP Target Recognition by the Higher-Order Spectra Features,” Journal of IEEE Transactions on Signal Processing, Vol. 53, No. 7, pp. 627-632, July 2005 |
8. | X. J. Liao, P. Runkle,L. Carin, “Identification of Ground Targets from Sequential High-Range-Resolution Radar Signatures,” Journal of IEEE Transactions on Aerospace and Electronic Systems, Vol. 38, No. 4, pp. 1230-1242, October 2002 |
9. | P. R. Runkle, P. K. Bharadwaj,L. Couchman, “Hidden Markov Models for Multiaspect Target Classification,” Journal of IEEE Transactions on Singal Processing, Vol. 47, No. 7, pp. 2035-2040, July 1999 |
10. | B. Dan, Y. H. Jiang, J. J. Li,Y. Lu, “Adaptive Angular-Sector Segmentation Method for Radar HRRP,” Journal of Systems Engineering and Electronics, Vol. 36, No. 11, pp. 2178-2185, 2014 |
11. | N. Luo, “Research on the Recognition Method of Radar Target One-Dimensional Range Profile,” University of Electronic Science and Technology of China, Chengdu, 2009 |
12. | J. X. Qin, “High Resolution Radar Target Recognition Method based on Scattering Center Model,” National University of Defense Technology, Changsha, 2008 |
13. | Z. W. Zhuang, X. S. Wang,X. Li, “Recognition of Radar Target,” 2nd Edition, Higher Education Press, 2015 |
14. | L. Du, H. W. Liu,Z. Bao, “Radar HRRP Target Recogniyion by the Higher Order Spectra,” Journal of IEEE Transactions on Signal Processing, Vol. 53, No. 7, pp. 2359-2368, 2005 |
[1] | Shuang Liu, Xing Cui, Jiayi Li, Hui Yang, and Niko Lukač. Pedestrian Detection based on Faster R-CNN [J]. Int J Performability Eng, 2019, 15(7): 1792-1801. |
[2] | Xin Zhang, Jianmin Zhao, Xianglong Ni, Haiping Li, and Fucheng Sun. Degradation Index Extraction and Degradation Trend Prediction for Rolling Bearing [J]. Int J Performability Eng, 2019, 15(5): 1334-1342. |
[3] | Pawan Kumar Upadhyay and Satish Chandra. Salient Bag of Feature for Skin Lesion Recognition [J]. Int J Performability Eng, 2019, 15(4): 1083-1093. |
[4] | Xinliang Wang, Zhigang Guo, Jianlin Chen, Na Liu, and Wei Fang. Detection Algorithm of Friction and Wear State of Large Mechanical and Electrical Equipment in Coal Mine based on C-SVC [J]. Int J Performability Eng, 2019, 15(3): 813-821. |
[5] | Yanan Liu and Xinghao Guo. Modulation Recognition based on Wavelet Transform and Fractal Theory [J]. Int J Performability Eng, 2019, 15(3): 998-1004. |
[6] | Yao Yao. A Cloud Computing Load Algorithm [J]. Int J Performability Eng, 2019, 15(12): 3151-3160. |
[7] | Yanhua Wang, Yaqiu Liu, and Weipeng Jing. Hadoop-based Parallel Algorithm for Data Mining in Remote Sensing Images [J]. Int J Performability Eng, 2019, 15(11): 2860-2870. |
[8] | Cheng Peng, Jing He, Hao Chi, Xinpan Yuan, and Xiaojun Deng. Icing Prediction of Fan Blade based on a Hybrid Model [J]. Int J Performability Eng, 2019, 15(11): 2882-2890. |
[9] | Wei Huang, Xiao Dong, Wenqian Shang, Weiguo Lin, and Menghan Yan. An Improved Optimal Method for Classification Problem [J]. Int J Performability Eng, 2019, 15(11): 3031-3041. |
[10] | Guoqiang Xie, Yi Zhao, Shiyi Xie, Miaofen Huang, and Ying Zhang. Multi-Classification Method for Determining Coastal Water Quality based on SVM with Grid Search and KNN [J]. Int J Performability Eng, 2019, 15(10): 2618-2627. |
[11] | Shaohui Zhang, Man Wang, Canyi Du, and Edgar Estupinan. Local and Global SR for Bearing Sensor-based Vibration Signal Classification [J]. Int J Performability Eng, 2019, 15(10): 2657-2666. |
[12] | Shaohua Yang, Guoliang Lu, Aiqun Wang, and Peng Yan. High-Level Feature Extraction based on Correlogram for State Monitoring of Rotating Machinery with Vibration Signals [J]. Int J Performability Eng, 2019, 15(1): 220-229. |
[13] | Hanqing Ding, Shuaichao Wei, Yan Zhang, and Qiuwen Zhang. Fast 3D-HEVC Coding based on Support Vector Machine [J]. Int J Performability Eng, 2018, 14(9): 1968-1974. |
[14] | Chenyang Zhao and Junling Wang. Autonomic Cloud Resource Allocation Method based on LS-SVM and Virtual Allocation [J]. Int J Performability Eng, 2018, 14(9): 1958-1967. |
[15] | Wei Jiang, Huiqiang Wang, and Keke Wu. Method for Detecting Javascript Code Obfuscation based on Convolutional Neural Network [J]. Int J Performability Eng, 2018, 14(12): 3167-3173. |
|