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摘要: 机载扫描雷达前视成像可广泛应用于态势感知、自主导航和地形跟随。在雷达扫描过程中受到不经意的电磁脉冲干扰或设备性能异常等影响时，雷达回波数据出现异常值。已有的超分辨方法可以抑制回波中的异常值、提高角度分辨率，但没有考虑计算实时性问题。针对上述问题，该文提出了一种机载雷达超分辨方法实现回波数据异常时的快速前视成像。为了更好地拟合回波噪声，引入对异常值更加鲁棒的学生t分布，并采用期望最大化方法对成像参数进行估计。受截断奇异值分解方法的启发，将截断的酉矩阵引入目标散射系数的估计公式中。通过矩阵变换降低了求逆矩阵的尺寸，从而降低了参数估计的计算复杂度。仿真结果表明该文提出加速方法可以用更短的时间提高前视成像的角度分辨率，抑制回波数据中的异常值。Abstract: Forward-looking imaging of airborne scanning radar is widely used in situation awareness, autonomous navigation and terrain following. When the radar is influenced by unintentional temporally sporadic electromagnetic interference or abnormal equipment performance, the echo signal contains outliers. Existing super-resolution methods can suppress outliers and improve azimuth resolution, but the real-time computing problem is not considered. In this study, we propose an airborne scanning radar super-resolution method to achieve fast forward-looking imaging when echo data are abnormal. First, we propose using the Student-t distribution to model noise. Then, the expectation-maximization method is used to estimate the parameters. Inspired by the truncated singular value decomposition method, we introduce the truncated unitary matrix into the estimation formula of the target scattering coefficient. Finally, the size of inverse matrix is reduced and the computational complexity of parameter estimation is reduced through matrix transformation. The simulation results show that the proposed method can improve the azimuth resolution of forward-looking imaging in a shorter time, and suppress outliers in echo data.
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Key words:
- Forward-looking imaging /
- Super-resolution /
- Abnormal echo data /
- Matrix transformation
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图 2 高斯分布和学生t分布的比较
Figure 2. Comparison of Gaussian distribution and student-t distribution
图 12 受电磁干扰时面目标仿真结果
Figure 12. Area target simulation results with electromagnetic interference
图 13 设备性能异常时面目标仿真结果
Figure 13. Area target simulation results with abnormal equipment performance
图 15 受电磁干扰时半实测数据仿真结果
Figure 15. Processed results of semi-real data with electromagnetic interference
图 16 设备性能异常时半实测数据仿真结果
Figure 16. Processed results of semi-real data with abnormal equipment performance
表 1 仿真系统参数
Table 1. System parameters of simulation
参数 数值 参数 数值 扫描速度$\left( {{{^ \circ } \mathord{\left/ {\vphantom {{^ \circ } {\text{s}}}} \right. } {\text{s}}}} \right)$ $50$ 载波频率$ \left( {{\text{GHz}}} \right) $ $ 9.5 $ 扫描范围$ \left( {^ \circ } \right) $ $ \pm 10$ 信号带宽$ \left( {{\text{MHz}}} \right) $ $ 40 $ 脉冲重复频率$\left( {{\text{Hz}}} \right)$ $1000$ 平台速度$\left( {{{\text{m}} \mathord{\left/ {\vphantom {{\text{m}} {\text{s}}}} \right. } {\text{s}}}} \right)$ $30$ 主瓣波束宽度$\left( {^ \circ } \right)$ 3 
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表 2 面目标仿真系统参数
Table 2. System parameters of area target simulation
参数 数值 参数 数值 扫描速度$\left( {{{^ \circ } \mathord{\left/ {\vphantom {{^ \circ } {\text{s}}}} \right. } {\text{s}}}} \right)$ $50$ 载波频率$ \left( {{\text{GHz}}} \right) $ $ 9.5 $ 扫描范围$ \left( {^ \circ } \right) $ $ \pm 10$ 信号带宽$ \left( {{\text{MHz}}} \right) $ $ 40 $ 脉冲重复频率$\left( {{\text{Hz}}} \right)$ $1000$ 平台速度$\left( {{{\text{m}} \mathord{\left/ {\vphantom {{\text{m}} {\text{s}}}} \right. } {\text{s}}}} \right)$ $30$ 主瓣波束宽度$\left( {^ \circ } \right)$ 5
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表 3 受电磁干扰时面目标仿真的MSE和运行时间
Table 3. MSE and running time of area target simulation with electromagnetic interference
方法 MSE 运行时间(s) LRIAA方法 6.15×10–3 4.90 MBSD方法 0.65×10–3 23.14 AMBSD方法 0.70×10–3 3.82
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表 4 设备性能异常时面目标仿真的MSE和运行时间
Table 4. MSE and running time of area target simulation with abnormal equipment performance
方法 MSE 运行时间(s) LRIAA方法 1.09×10–3 4.80 MBSD方法 0.80×10–3 23.03 AMBSD方法 0.81×10–3 3.90
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表 5 半实测数据运行时间(s)
Table 5. Running time of semi-real data (s)
方法 受电磁干扰时运行时间 设备性能异常时运行时间 LRIAA方法 1.98 1.89 MBSD方法 4.57 4.58 AMBSD方法 1.18 1.19
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