Research on the detection method of ship wake weak signal based on synchronous accumulation method
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摘要:目的
为适应复杂动态变化尾流气泡场环境，提高水下探测装置对舰船尾流微弱信号探测信噪比与检出率。
方法本文提出了一种基于同步累积法的舰船尾流微弱信号检测方法，利用周期信号的重复性与噪声的随机性，对连续多个周期信号做累积归一化处理，降低随机噪声对探测性能的干扰，提升了探测信噪比；建立了针对舰船尾流微弱信号多时间尺度检测能力评估模型，评估本方法在多参量耦合下的探测性能。
结果通过在室内水池、室外湖泊条件下开展大量模拟舰船尾流探测实验，验证了该方法适配稀疏微小的远场尾流气泡至高湍流扰动下的大尺度近场气泡检测，
结论可实现全时域舰船尾流跟踪检测，有效提升水下兵器打击能力，为舰船尾流激光探测识别工程实践提供支撑。
Abstract:ObjetiveIn order to adapt to the complex dynamic changing wake bubble field environment, the detection signal-to-noise ratio and detection rate of ship wake weak signal are improved, and the detection range is expanded.
MethodIn this paper, a detection method of ship wake weak signals based on synchronous accumulation method is proposed. By taking advantage of the repeatability of periodic signals and the randomness of noise, cumulative normalization is performed on successive periodic signals, which can effectively improve the detection signal-to-noise ratio and reduce the interference of random signals on detection performance. In order to evaluate the detection performance of the algorithm under multi-parameter coupling, a multi-time scale detection capability evaluation model for ship wake weak signals is established.
ResultBy conducting a large number of simulated ship wake detection experiments in indoor large pools and outdoor typical lakes, it is verified that the algorithm is suitable for the detection of sparse and discrete tiny far-field wake bubbles to large-scale near-field bubbles under high turbulence disturbance, thus realizing the full-time ship wake tracking and detection and effectively improving the underwater weapon strike capability.
ConclusionIt can provide support for ship wake laser detection and identification engineering practice.
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Key words:
- laser acquisition /
- ship wake /
- signal processing
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图 2 实验装置图；(a)探测装置；(b)气泡发生装置
Figure 2. Experimental setup; (a) detection devices; (b) Bubble generator
图 4 不同累积周期数对应信号幅值以及整体信号变化趋势变化情况：(a)原始信号；(b)10周期累积信号；(c)30周期累积信号；(d)50周期累积信号
Figure 4. The variation of signal amplitude corresponding to the number of different superposition periods:(a)The original signal;(b)10-cycle cumulative signal;(c)30-cycle cumulative signal;(d)50-cycle cumulative signal;
图 5 湖泊实验探测装置安装状态
Figure 5. Installation state of lake experimental detection equipment
图 7 湖泊条件激光回波信号幅值变化情况
Figure 7. Changes in amplitude of laser echo signal under lake conditions
图 8 不同累积周期数对应信号幅值变化情况：(a)原始信号；(b)10周期累积信号；(c)50周期累积信号；(d)100周期累积信号；(e)500周期累积信号；(f)1000周期累积信号
Figure 8. The amplitude of the signal corresponding to the number of different superposition periods; (a) The original signal; (b) 10-cycle cumulative signal; (c) 50-cycle cumulative signal; (d) 100-cycle cumulative signal; (e) 500-cycle cumulative signal; (f) 1000-cycle cumulative signal
表 1 评估模型处理结果
Table 1. Results of evaluation model processing
累积
周期数信噪比 信背比 检出率 小气泡 大气泡 小气泡 大气泡 全探测过程 原始 0.3182 14.0000 1.0493 3.1690 65.36% 10 0.7905 34.2381 1.0549 3.3792 72.50% 30 1.8034 57.8258 1.0743 3.3815 84.62% 50 2.1925 75.6432 1.0655 3.2582 87.50% 
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表 2 评估模型处理结果
Table 2. Evaluation model processing results
叠加周
期数信噪比 信背比 检出率
全过程2 min 4 min 6 min 8 min 2 min 4 min 6 min 8 min 1 3.9828 6.0263 4.9828 1.7403 0.9240 0.9872 0.9049 1.0188 79.88% 10 7.0033 8.1485 7.3742 5.9902 0.9348 0.9430 0.9266 0.9442 89.26% 50 11.7589 12.5028 11.7459 6.0344 0.9147 0.9413 0.9238 0.9463 89.32% 100 11.7314 18.4155 11.7865 7.6769 0.9242 0.9322 0.9208 0.9439 89.19% 500 15.9158 19.0482 12.9746 12.0893 0.9288 0.9151 0.9321 0.9337 89.06% 1000 15.9447 17.6144 11.6551 13.0707 0.9248 0.9168 0.9383 0.9351 88.97%
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