鱼雷被动检测的盲分离对抗干扰方法

赵 伟; 郝保安; 杨向锋; 肖 霖

doi:10.11993/j.issn.1673-1948.2012.03.005

鱼雷被动检测的盲分离对抗干扰方法

doi: 10.11993/j.issn.1673-1948.2012.03.005

1.
西北工业大学航海学院, 陕西西安, 710072
2.
中国船舶重工集团公司第705研究所, 陕西西安, 710075

详细信息

作者简介:
赵伟(1968-), 男, 在读博士, 高工, 从事水声信号与信息处理以及数字、模拟电路等方向的研究.

中图分类号: TJ630.34
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- 被引次数: 0
出版历程
- 收稿日期: 2011-07-25
- 修回日期: 2011-09-20
- 刊出日期: 2012-06-20

Anti-interference Method for Torpedo Passive Target Detection with Blind Source Separation

1.
College of Marine Engineering, Northwestern Polytechnical University, Xi′an 710072, China
2.
The 705 Research Institute, China Shipbuilding Industry Corporation, Xi′an 710075, China

摘要

摘要: 近年来由于海洋环境噪声级的不断提高, 目标隐身性能以及水声对抗能力的不断提升, 使得鱼雷被动目标检测方式的有效性受到极大的挑战。为了解决被动目标检测的抗干扰问题, 采用近年来发展起来的盲信号处理方法, 利用目标信号与干扰相互统计独立的原理, 将目标与干扰盲分离, 从而实现在强干扰条件下的被动抗干扰目标检测; 在生成目标辐射噪声与模拟辐射噪声、冲击以及扫频干扰信号后, 建立了多重干扰条件下的含噪信号混合模型, 然后采用4种复盲分离算法进行了被动目标盲分离抗干扰仿真试验, 并作了对比分析。仿真结果表明, 通过盲分离方式可以有效地实现多种干扰的分离, 提高了目标信号的信干比(SIR), 从而改善了被动目标的检测性能。
- 鱼雷 /
- 被动检测 /
- 盲分离 /
- 抗干扰
Abstract: Enhancement of ocean environment noise level, improvements in target noise elimination and acoustic counter-measure bring great challenge to the torpedo passive target detection. To suppress interference in torpedo passive detection, we adopt the developing blind source separation (BSS) technique to separate interference from target signal by using independ-ence principle of target and interference, thus realize passive target detection in the condition of strong inference. We generate target radiation signal, simulated radiation noise, impulse and chirp interferences, then set up multi-interference noisy mixed model, and then adopt the four kinds of complex BSS algorithms to simulate interference suppression in passive target detec-tion. Simulation results show that BSS passive detection can effectively realize multi-interference separation, enhance signal to interference ratio (SIR), and improve passive target detection performance.
- torpedo /
- passive detection /
- blind source separation(BSS) /
- anti-interference

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参考文献(13)

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