Recognition Method of Radar Signal Based on the Energy Cumulant of Choi-Williams Distribution and Improved Semi-supervised Naïve Bayes

Hongwei WANG; Pengyu DONG; You CHEN; Yipeng ZHOU; Bingsong XIAO

doi:10.11999/JEIT200127

Volume 43 Issue 3

Mar. 2021

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Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(3): 589-597

Hongwei WANG, Pengyu DONG, You CHEN, Yipeng ZHOU, Bingsong XIAO. Recognition Method of Radar Signal Based on the Energy Cumulant of Choi-Williams Distribution and Improved Semi-supervised Naïve Bayes[J]. Journal of Electronics & Information Technology, 2021, 43(3): 589-597. doi: 10.11999/JEIT200127

Citation:

Hongwei WANG, Pengyu DONG, You CHEN, Yipeng ZHOU, Bingsong XIAO. Recognition Method of Radar Signal Based on the Energy Cumulant of Choi-Williams Distribution and Improved Semi-supervised Naïve Bayes[J]. Journal of Electronics & Information Technology, 2021, 43(3): 589-597. doi: 10.11999/JEIT200127

Citation:

Hongwei WANG, Pengyu DONG, You CHEN, Yipeng ZHOU, Bingsong XIAO. Recognition Method of Radar Signal Based on the Energy Cumulant of Choi-Williams Distribution and Improved Semi-supervised Naïve Bayes[J]. Journal of Electronics & Information Technology, 2021, 43(3): 589-597. doi: 10.11999/JEIT200127

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Recognition Method of Radar Signal Based on the Energy Cumulant of Choi-Williams Distribution and Improved Semi-supervised Naïve Bayes

doi: 10.11999/JEIT200127

Aeronautics Engineering College, Aire Force Engineering University, Xi’an 710038, China

Funds: Aeronautical Science Foundation (20175596020)

Received Date: 2020-02-26
Rev Recd Date: 2020-09-30

Available Online: 2020-10-12

Publish Date: 2021-03-22

Abstract

Abstract

In order to solve incomplete prior information of radar in non-cooperative electronic countermeasure environment, a novel recognition algorithm named ISNB (Improved Semi-supervised Naïve Bayes) based on the energy cumulant of Choi-Williams Distribution(CWD) is put forward. This algorithm extracts the energy cumulant of Choi-Williams distribution of radar signals as the recognition feature. The energy cumulant of CWD is attained by calculating the accumulations of each frequency sample value with the different time samples. Before this procedure, CWD is processed by base noise reduction. Considering disadvantages of traditional Semi-supervised Naïve Bayes(SNB) which comes from repeated errors in updating sample sets, it uses ISNB to construct classifier, and then completes the recognition of tested sample sets. ISNB selects those samples with high degree of confidence which comes from generated confidence. Theoretical analysis and simulation results show that the proposed method is about 3% higher than the traditional SNB algorithm. Under the same signal-to-noise ratio, this algorithm has higher classification recognition rate and better classification performance than the traditional principal component analysis plus support vector machine.
- Radar signal recognition,
- Choi-Williams Distribution(CWD),
- Energy cumulant,
- Naïve Bayes(NB),
- Semi-supervised learning

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References(25)

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