极浅海环境中时间分集MIMO声呐高清晰成像方法

翟清越; 刘雄厚; 杨益新

doi:10.11993/j.issn.2096-3920.2026-0072

极浅海环境中时间分集MIMO声呐高清晰成像方法

doi: 10.11993/j.issn.2096-3920.2026-0072

翟清越^{1, 2, 3,},
刘雄厚^{1, 2, 3, ,},
杨益新^4,

1.
西北工业大学航海学院, 陕西西安, 710072
2.
陕西水下信息技术重点实验室, 陕西西安, 710072
3.
汉江国家实验室, 武汉, 430061
4.
南京理工大学电子工程与光电技术学院, 南京, 210094

基金项目: 国家自然科学基金(U2341203; 12274346); 国家重点研发计划(2016YFC1400200).

详细信息

作者简介:
翟清越(2002-), 女, 硕士在读, 主要研究方向为水声信号处理

通讯作者:
刘雄厚(1985-), 男, 博士, 教授, 主要研究方向为水下小目标探测与识别.

中图分类号: TN929.3; U666.7
计量
- 文章访问数: 4
- HTML全文浏览量: 1
- PDF下载量: 1
- 被引次数: 0
出版历程
- 收稿日期: 2026-04-13
- 修回日期: 2026-05-14
- 录用日期: 2026-05-18
- 网络出版日期: 2026-06-11

High-Resolution Imaging Method for Time-Diversity MIMO Sonar in Extremely Shallow Water Environments

ZHAI QingYue^{1, 2, 3
,},
LIU Xionghou^{1, 2, 3
, ,},
YANG Yixin^4
,

1.
School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China
2.
Shaanxi Key Laboratory of Underwater Information Technology, Xi’an 710072, China
3.
Hanjiang National Laboratory, Wuhan 430061, China
4.
School of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology, Nanjing 210094, China

摘要

摘要: 传统多输入多输出(MIMO)声呐在极浅海强混响环境下, 受同步正交波形互相关干扰影响, 其距离维高旁瓣会显著抬升混响背景, 导致自适应波束形成算法性能大幅下降。为此, 文中提出一种适用极浅海环境的时间分集MIMO声呐高清晰成像方法, 通过时分机制依次发射相同线性调频信号, 利用脉冲周期实现时域回波分离, 消除互相关干扰; 结合时域截断与数据重组, 构建孔径加倍的等效均匀虚拟线列阵, 完整保留MIMO体制的高角度分辨率。仿真结果表明, 在信混比低至-20dB的强混响背景下, 该方法有效抑制了距离维旁瓣, 使最小方差无畸变响应算法的自适应滤波能力得以充分发挥。与传统正交MIMO声呐相比, 其−3 dB主瓣宽度、旁瓣级与积分旁瓣比显著优化, 为极浅海小目标高分辨成像提供了一种兼顾虚拟孔径与强抗干扰能力的可行方案。
- 极浅海 /
- MIMO声呐 /
- 时间分集 /
- 互相关干扰 /
- 高清晰成像
Abstract: In extremely shallow water environments with strong reverberation, traditional MIMO sonar is affected by cross-correlation interference from synchronous orthogonal waveforms. The high range sidelobes significantly raise the reverberation background, leading to severe performance degradation of adaptive beamforming algorithms. To solve this problem, this paper proposes a high-resolution imaging method for time-diversity MIMO sonar suitable for extremely shallow water environments. The method transmits the same linear frequency modulation signals sequentially through a time-division mechanism, and separates echo signals in the time domain by using pulse repetition intervals, thus eliminating cross-correlation interference. Combined with time-domain truncation and data reconstruction, an equivalent uniform virtual linear array with doubled aperture is constructed, which fully retains the high angular resolution of the MIMO system. Simulation results show that the proposed method effectively suppresses range sidelobes under a strong reverberation background with a signal-to-reverberation ratio as low as −20 dB, and fully exerts the adaptive filtering capability of the MVDR algorithm. Compared with traditional orthogonal MIMO sonar, its half power beam width, side lobe level and integration side lobe rate are significantly optimized, providing a feasible scheme for high-resolution imaging of small targets in extremely shallow water that takes into account both virtual aperture and strong anti-interference ability.
- Extremely shallow water /
- MIMO sonar /
- Time diversity /
- Cross-correlation interference /
- High-resolution imaging

HTML全文

图 1 多途传播示意图

Figure 1. Schematic diagram of multipath propagation

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图 2 基于时间分集的2发$ K $收MIMO声呐示意图(其中$ K $为接收阵元数)

Figure 2. Schematic diagram of 2-transmit K-receive MIMO sonar based on time diversity(where K denotes the number of receiving array elements)

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图 3 无干扰条件下, 两种声呐成像对比图

Figure 3. Comparison of two sonar imaging results under interference-free conditions

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图 4 2 m水深, 传统MIMO声呐成像结果

Figure 4. Imaging performance of traditional MIMO sonar in 2 m-deep water

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图 5 10 m水深, 传统MIMO声呐成像结果

Figure 5. Imaging performance of traditional MIMO sonar in 10 m-deep water

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图 6 2 m水深, 时间分集MIMO声呐成像结果

Figure 6. Imaging performance of time-diversity MIMO sonar in 2-m-deep water

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图 7 10 m水深, 时间分集MIMO声呐成像结果

Figure 7. Imaging performance of time-diversity MIMO sonar in 10-m-deep water

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图 8 不同SRR条件下, 传统MIMO声呐的角度维成像性能

Figure 8. Imaging performance of conventional MIMO sonar in angular dimension at various SIR levels

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图 9 不同SRR条件下, 时间分集MIMO声呐的角度维成像性能

Figure 9. Imaging performance of time-diversity MIMO sonar in angular dimension at various SRR levels

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