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Research on Super-resolution Methods for Radar Targets Based on Bat-inspired Spectrogram Correlation and Transformation Models
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摘要: 传统雷达分辨能力主要利用模糊函数来进行分析，其极限分辨力一般用瑞利限表征。自然界中蝙蝠具有相当敏锐的听觉系统，学者提出谱相关及变换(SCAT)模型对蝙蝠听觉系统建模，探索了蝙蝠的超分辨原理，为突破雷达目标常规(瑞利)分辨力提供了一个可能的途径。为了进一步提高SCAT模型的分辨性能，通过抑制距离像负半轴和原点处多余的波瓣，改进了基向量解卷积法和基带SCAT (BSCT)两种蝙蝠超分辨模型，同时提出可靠分辨力概念及计算方法，统一了SCAT分辨力与瑞利分辨力的衡量标准，对比验证了可靠分辨力概念的合理性以及改进算法的有效性。仿真与实测实验表明，改进超分辨算法均获得了可观的分辨力提升，其中改进基向量解卷积法性能最佳，将原基向量解卷积法的分辨力提高约2 dB，同时将匹配滤波分辨力提高约5 dB。Abstract: The resolving power of traditional radar is mainly analyzed using the ambiguity function, and its limit is generally characterized by the Rayleigh limit. Bats have a rather sensitive auditory system. Researchers have proposed the Spectrogram Correlation And Transformation (SCAT) model to represent the auditory system of bats, explored their super-resolution principle, and provided a possible means to break through the conventional (Rayleigh) resolving power limit of radar targets. To further enhance the discriminative performance of the SCAT model, two bat-auditory-system-based super-resolution models, namely the base vector deconvolution method and baseband SCAT (BSCT), are improved by suppressing redundant wave flaps at the negative semiaxis of the range profile and at the origin. Meanwhile, the concept and computation method of reliable discriminative power are proposed to unify the measurements of SCAT and Rayleigh discriminative powers. Further, a comparison is made to validate the rationality of the concept of reliable discriminative power, and the effectiveness of the improved models is verified. Simulation and real experiments show that the improved super-resolution models achieve a sizable increase in the resolving power. Notably, the improved base vector deconvolution method performs the best, improving the resolving power of the original method by ～2 dB while enhancing the matched filtering resolving power by ～5 dB.
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图 1 目标间距为0.5倍瑞利分辨力时基向量解卷积仿真图
Figure 1. Simulation of basis vector deconvolution when the target spacing is 0.5 times the Rayleigh resolution
图 3 目标间距为0.2倍瑞利分辨力时基向量解卷积仿真图
Figure 3. Simulation of basis vector deconvolution with target spacing of 0.2 times the Rayleigh resolution
图 4 BSCT的分辨效果随两目标相对距离变化
Figure 4. The resolution of BSCT varies with relative distance of two targets
图 5 BSCT的改进算法分辨效果随两目标相对距离变化
Figure 5. The resolution effect of the improved BSCT algorithm varies with relative distance of two targets
图 6 基向量解卷积法的分辨效果随两目标相对距离变化
Figure 6. The resolution effect of the basis vector deconvolution method varies with the relative distance of two targets
图 9 幅度比和相位差对不同信号处理方式分辨效果的影响
Figure 9. The effect of amplitude ratio and phase difference on the resolution of different signal processing methods
表 1 仿真参数设置
Table 1. Simulation parameter settings
参数 数值 脉冲脉宽${T_{\text{p}}}$ 10 μs 脉冲带宽${B_{\text{c}}}$ 40 ${\text{MHz}}$ 耳蜗单元滤波器组数目N 81 相邻滤波器中心频率差异$\Delta {f_i}$ 0.5 ${\text{MHz}}$ 滤波器阶数 128 滤波器带通宽度B 1 ${\text{MHz}}$ 
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表 2 不同信号处理方法的对比
Table 2. Comparison of different signal processing methods
信号处理方法 无相位差 有相位差 幅度差异对分辨的影响 分辨力 可靠分辨力 分辨力 可靠分辨力 匹配滤波处理 ${1 / {{B_{\text{c}}}}}$ ${1 / {{B_{\text{c}}}}}$ 与相位差有关，等幅反相时为无穷小 与相位差有关，大于瑞利分辨力 幅度差越大，分辨效果越差 BSCT $ < {1 / {{B_{\text{c}}}}}$ ${1 / {{B_{\text{c}}}}}$ $ < {1 / {{B_{\text{c}}}}}$ ${1 / {{B_{\text{c}}}}}$ 无影响 改进BSCT $ < {{0.7} / {{B_{\text{c}}}}}$ ${{0.7} / {{B_{\text{c}}}}}$ $ < {{0.7} / {{B_{\text{c}}}}}$ ${{0.7} / {{B_{\text{c}}}}}$ 无影响 基向量解卷积 $ < {{0.5} / {{B_{\text{c}}}}}$ ${{0.5} / {{B_{\text{c}}}}}$ 效果变差 无影响 改进基向量解卷积 $ < {{0.31} / {{B_{\text{c}}}}} $ $ {{0.31} / {{B_{\text{c}}}}} $ 效果变差 无影响
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表 3 实测雷达参数
Table 3. Measured radar parameters
参数 数值 脉冲脉宽${T_{\text{p}}}$ 1 μs 脉冲带宽${B_{\text{c}}}$ 100 MHz 中心频率${f_0}$ 19 GHz 采样率${f_{\text{s}}}$ 80 GHz 耳蜗单元滤波器组数目N 81 相邻滤波器中心频率差异$\Delta {f_i}$ 1.25 MHz 滤波器阶数 128 滤波器带通宽度B 2.5 MHz
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