Abstract
In the presence of interference, the recognition performance of underwater target radiated noise severely degrades due to waveform distortion after array beanforming. Based on constant-beamwidth and interference-suppression, a new method of underwater target recognition algorithm is proposed to improve the fidelity of waveform in this paper. In this method, the second-order cone programming (SOCP) is exploited to deal with signal distortion of broadband constant-beamwidth beamforming. Combining SOCP with auditory filtering techniques, we extract intrinsic features of the targets to effectively distinguish them from each other. Based on array signal simulated from the ship-radiated noise collected by a hydrophone, the results and their analysis demonstrate preliminarily the effectiveness of the proposed algorithm in target classification.
| Original language | English |
|---|---|
| Pages (from-to) | 843-848 |
| Number of pages | 6 |
| Journal | Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University |
| Volume | 33 |
| Issue number | 5 |
| State | Published - Oct 2015 |
Keywords
- Array processing
- Backpropagation algorithms
- Beamforming
- Computer simulation
- Constant beamwidth
- DEMON analysis
- Discrete Fourier transforms
- Efficiency
- Feature extraction
- Filter banks
- Hydrophones
- Interference suppression
- Second-order cone programming (SOCP)
- Target tracking
- Underwater target recognition