High-Resolution Imaging Method of Deconvolution MIMO Sonar Based on Acoustic Homing Platform
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摘要: 针对水下航行器对目标期望导引部位精确成像的需求, 首次尝试将多输入多输出(MIMO)声呐成像应用于水下航行器的声自导平台, 旨在有限孔径条件下提高水下航行器声自导平台主动成像的分辨率, 获取清晰图像以引导水下航行器判断目标期望导引部位。结合声自导平台对MIMO声呐收发基阵进行讨论, 并通过仿真证明了MIMO声呐可等效为更大孔径的虚拟单输入多输出(SIMO)声呐, 兼具高于传统SIMO声呐的角度分辨率与小体积的优势。使用解卷积处理可以有效提高MIMO声呐的角度分辨率和距离分辨率, 同时显著抑制角度维和距离维旁瓣。文章创新点在于根据声自导平台设计收发阵型和Costas编码发射信号, 对目标散射回波进行处理, 验证了解卷积MIMO声呐高分辨成像方法在声自导平台上的可行性, 为MIMO声呐高分辨成像提供了新的技术参考和实现路径。Abstract: To address the demand for precise imaging of the desired guidance part of a target by an undersea vehicle, this paper attempted to apply multiple-input multiple-output(MIMO) sonar imaging to the acoustic homing platform of an underwater vehicle for the first time. The paper aimed to improve the resolution of active imaging of the acoustic homing platform under limited aperture conditions and obtain clear images to guide the underwater vehicle in determining the desired guidance part of the target. The MIMO sonar transceiver array configuration was discussed in combination with the acoustic homing platform. Simulation results demonstrate that the MIMO sonar can be equivalent to a virtual single-input multiple-output(SIMO) sonar with a larger aperture, possessing both higher angular resolution than traditional SIMO sonar and the advantage of compact size. Deconvolution processing can effectively improve the angular and range resolutions of the MIMO sonar while significantly suppressing sidelobes in both angular and range dimensions. In this paper, the transceiver array and Costas-coded transmission signals are designed based on the acoustic homing platform to process target scattering echoes. The feasibility of the high-resolution imaging method for deconvolution MIMO sonar on the acoustic homing platform is validated. This paper provides a new technical reference and implementation path for high-resolution imaging of MIMO sonar.
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Key words:
- acoustic homing /
- undersea vehicle /
- MIMO sonar /
- SIMO sonar /
- deconvolution /
- resolution
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图 5 实际阵列与等效虚拟阵列位置对比
Figure 5. Comparison of positions between actual array and equivalent virtual array
图 16 不同信噪比下两步R-L算法成像结果
Figure 16. Imaging results of two-step R-L algorithm under different signal-to-noise ratio
表 1 22位Costas编码
Table 1. 22-bit Costas code
发射信号 编码序列 信号1 1, 5, 2, 10, 4, 20, 8, 17, 16, 11, 9,
22, 18, 21, 13, 19, 3, 15, 6, 7, 12, 14信号2 1, 14, 12, 7, 6, 15, 3, 19, 13, 21, 18,
22, 9, 11, 16, 17, 8, 20, 4, 10, 2, 5
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表 2 散射点坐标
Table 2. Coordinates of scattered points
目标 角度/(°) 距离/m 目标 角度/(°) 距离/m 散射点1 −25 99 散射点15 0 102 散射点2 −20 98 散射点16 5 98 散射点3 −20 100 散射点17 5 100 散射点4 −15 98 散射点18 5 102 散射点5 −15 100 散射点19 10 98 散射点6 −10 98 散射点20 10 100 散射点7 −10 100 散射点21 10 101 散射点8 −10 101 散射点22 10 102 散射点9 −10 102 散射点23 15 98 散射点10 −5 98 散射点24 15 100 散射点11 −5 100 散射点25 20 98 散射点12 −5 102 散射点26 20 100 散射点13 0 98 散射点27 25 99 散射点14 0 100
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表 3 角度维半功率波束宽度和旁瓣级对比
Table 3. Comparison of half-power beamwidth and sidelobe level in angular dimension
成像方法 半功率波束宽/(°) 旁瓣级/dB 1发26收SIMO成像 4.07 −13.25 1发50收SIMO成像 2.03 −13.25 2发25收MIMO成像 2.03 −13.25 解卷积MIMO成像 0.43 —
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表 4 角度维的半功率波束宽度和旁瓣级对比
Table 4. Comparison of half-power beamwidth and sidelobe level in angular dimension
成像方法 半功率波束宽/rad 旁瓣级/dB 1发26收SIMO成像 0.10 −4.60 2发25收MIMO成像 0.08 −5.46 解卷积MIMO成像 0.03 −8.33
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