Communication emitter individual identification via 3D‐Hilbert energy spectrum‐based multiscale segmentation features. (21st October 2018)
- Record Type:
- Journal Article
- Title:
- Communication emitter individual identification via 3D‐Hilbert energy spectrum‐based multiscale segmentation features. (21st October 2018)
- Main Title:
- Communication emitter individual identification via 3D‐Hilbert energy spectrum‐based multiscale segmentation features
- Authors:
- Han, Jie
Zhang, Tao
Qiu, Zhaoyang
Zheng, Xiaoyu - Abstract:
- Summary: Specific emitter identification can detect emitters automatically by extracting and analyzing features. A novel specific emitter identification method based on 3D‐Hilbert energy spectrum‐based multiscale segmentation (3D‐HESMS) is proposed. First, the time‐frequency energy spectrum is derived via the Hilbert‐Huang transform, that is, a complicated curved surface in a 3D space, namely, the 3D‐Hilbert energy spectrum. The differential box dimension, multifractal dimension, lacunarity change rate, and 3D‐Hilbert energy entropy are extracted to compose the feature vector under multiscale segmentation using fractal theory. Subsequently, communication emitter individual identification is obtained using the 4 features. Finally, the performance and complexity of the 3D‐HESMS method are compared with those of 2 existing methods. Experiments show that the performance of the 3D‐HESMS method is better than those of the 2 other methods. The extracted features with high stability, sufficiency, and identifiability can overcome the negative effects of the changes in signal‐to‐noise ratio and the number of training samples. Abstract : The identification performance of the proposed 3D‐HESMS method is least influenced by SNR and the numbers of training samples and emitters. When the SNR is low, the 3D‐HESMS method shows an outstanding identification performance and has a high identification rate when the modulation modes of signals are the same. The features extracted by the 3D‐HESMSSummary: Specific emitter identification can detect emitters automatically by extracting and analyzing features. A novel specific emitter identification method based on 3D‐Hilbert energy spectrum‐based multiscale segmentation (3D‐HESMS) is proposed. First, the time‐frequency energy spectrum is derived via the Hilbert‐Huang transform, that is, a complicated curved surface in a 3D space, namely, the 3D‐Hilbert energy spectrum. The differential box dimension, multifractal dimension, lacunarity change rate, and 3D‐Hilbert energy entropy are extracted to compose the feature vector under multiscale segmentation using fractal theory. Subsequently, communication emitter individual identification is obtained using the 4 features. Finally, the performance and complexity of the 3D‐HESMS method are compared with those of 2 existing methods. Experiments show that the performance of the 3D‐HESMS method is better than those of the 2 other methods. The extracted features with high stability, sufficiency, and identifiability can overcome the negative effects of the changes in signal‐to‐noise ratio and the number of training samples. Abstract : The identification performance of the proposed 3D‐HESMS method is least influenced by SNR and the numbers of training samples and emitters. When the SNR is low, the 3D‐HESMS method shows an outstanding identification performance and has a high identification rate when the modulation modes of signals are the same. The features extracted by the 3D‐HESMS method complement with one another, which have high stability, sufficiency, and identifiability. … (more)
- Is Part Of:
- International journal of communication systems. Volume 32:Number 1(2019)
- Journal:
- International journal of communication systems
- Issue:
- Volume 32:Number 1(2019)
- Issue Display:
- Volume 32, Issue 1 (2019)
- Year:
- 2019
- Volume:
- 32
- Issue:
- 1
- Issue Sort Value:
- 2019-0032-0001-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2018-10-21
- Subjects:
- Telecommunication systems -- Periodicals
621.382 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/dac.3833 ↗
- Languages:
- English
- ISSNs:
- 1074-5351
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.172515
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 9190.xml