A Comprehensive Estimation Method for Kernel Function of Radar Signal Classifier

XU Jing; HE Minghao; HAN Jun; CHEN Changxiao

Article Contents

Article Navigation > Chinese Journal of Electronics > 2015 > 24(1): 218-222

XU Jing, HE Minghao, HAN Jun, et al., “A Comprehensive Estimation Method for Kernel Function of Radar Signal Classifier,” Chinese Journal of Electronics, vol. 24, no. 1, pp. 218-222, 2015,

Citation:

XU Jing, HE Minghao, HAN Jun, et al., “A Comprehensive Estimation Method for Kernel Function of Radar Signal Classifier,” Chinese Journal of Electronics, vol. 24, no. 1, pp. 218-222, 2015,

XU Jing, HE Minghao, HAN Jun, et al., “A Comprehensive Estimation Method for Kernel Function of Radar Signal Classifier,” Chinese Journal of Electronics, vol. 24, no. 1, pp. 218-222, 2015,

Citation:

XU Jing, HE Minghao, HAN Jun, et al., “A Comprehensive Estimation Method for Kernel Function of Radar Signal Classifier,” Chinese Journal of Electronics, vol. 24, no. 1, pp. 218-222, 2015,

PDF( 291 KB)

A Comprehensive Estimation Method for Kernel Function of Radar Signal Classifier

Air Force Early Warning Academy, Wuhan 430019, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61201123, No.61302194).

Received Date: 2013-12-01
Rev Recd Date: 2014-01-01
Publish Date: 2015-01-10

Abstract

Abstract

The current electromagnetism environment is fast changing and levity, the methods for evaluation Suppont vector machine (SVM) kernel functions which are used in radar signal recognition can not suit it. So kernel space separate, stability and
- Radar emitter,
- Support vector machine (SVM),
- Kernel function,
- Comprehensive estimation

FullText(HTML)

References(13)

References

J. Han, M. He, Z. Tang, et al., "Estimating in-pulse characteristics of radar signal based on multi-index", Chinese Journal of Electronics, Vol.20, No.1, pp.187-191, 2011.

J. Xu, M.H. He, J. Han, et al., "Estimating the stability of characteristic parameters based on single-element analysis of variance", 11th International Conference on Signal Processing, Beijing, China, pp.1804-1807, 2012.

C.S. Shieh and C.T. Lin, "A vector network for emitter identification", IEEE Transaction on Antennas and Propagation, Vol.50, No.8, pp.1120-1127, 2002.

V. Vapnik, The Nature of Statistical Learning Theory, Springer Verlag, New York, 1998.

G. Zhang, W. Jin and L. Hu, "A hybird classifier based on rough set theory and support vector machines", Lecture Notes in Computer Science, pp.1287-1296, 2005.

G. Zhang, K. Huang, Y. Zhou, et al., "A method of radiator identification based on weighted AVA technique", Signal processing, Vol.22, No.3, pp.357-360, 2006.

M. Ren, Y. Zhu and T. Shen, "Approach on radar emitter signal classification based on FSVMs", Journal of System Simulation, Vol.21, No.4, pp.1043-1046, 2009.

X. Song, et al., "Evaluating the generalization performance of SVMs based on the advanced joachims bound", ACTA Electronica Sinica, Vol.39, No.6, pp.1379-1383, 2011.

Y. Wang and B. Hu, "A study on integrated evaluation kernel classification performance using statistical method", Chinese Journal of Computers, Vol.31, No.6, pp.942-952, 2008.

T. Wang and J. Chen, "Survey of research on kernel function evaluation", Application Research on Computers. No.28, Vol.1, pp.25-28, 2011.

J. Han, et al., "Sorting unknown radar emitter signal based on the complexity characteristic", Journal of Electronics & Information Technology, Vol.31, No.11, pp.2552-2555, 2009.

J. Han, et al., "A new method for recognizing radar radiatingsource", ICWAPR’2007, Vol.4, pp.1665-1668, 2007.

J. Han, et al., "Sorting radar signal based on the resemblance coefficient of bispectrum two dimensions characteristic", Chinese Journal of Radio Science, Vol.24, No.5, pp.848-851, 2009.

Relative Articles

Supplements(0)

Cited By

Proportional views