| Autor: |
Shitong LI, Daying QUAN, Zeyu TANG, Yun CHEN, Xiaofeng WANG, Xiaoping JIN |
| Jazyk: |
čínština |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Dianxin kexue, Vol 38, Pp 84-91 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1000-0801 |
| DOI: |
10.11959/j.issn.1000-0801.2022024 |
| Popis: |
Aiming at improving the accuracy of radar signal recognition under a low signal-to-noise ratio, a radar signal recognition algorithm based both on time-frequency image and high-order spectrum feature was proposed.Firstly, the time-frequency image was obtained by Choi-Williams distribution (CWD) transform, based on which the time-frequency image was preprocessed and the texture features were extracted by gray level co-occurrence matrix (GLCM) in sequence.Meanwhile, the symmetrical holder coefficient was used to extract the high-order spectral features of the signal.Then, the texture features and high-order spectrum features were form a new set of joint feature vectors.Finally, with the proposed feature vector the classification and recognition of radar signals were implemented by a support vector machine.The algorithm was verified on the data set with eight typical radar signals.Experimental results show that the recognition accuracy of different radar signals can achieve higher than 90% when the signal-to-noise ratio is -8 dB. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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