Analysis of Insect RCS Characteristics
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摘要:
昆虫雷达是观测昆虫迁飞最有效的工具。研究昆虫的雷达散射截面积(RCS)特性对于昆虫雷达目标识别有着重要意义。该文将分析昆虫的静态RCS特性和动态RCS特性。首先,基于实测的X波段全极化昆虫RCS数据,分析昆虫的静态RCS特性,包括水平和垂直极化RCS随体重变化规律以及昆虫极化方向图随体重的变化规律。其次,总结当前通过电磁仿真研究昆虫RCS特性所用到的介质和几何形状模型,并对比了水、脊髓、干皮肤和壳质与血淋巴混合物4种介质和等体型扁长椭球体、等质量扁长椭球体和三轴椭球体3种几何模型组成的12种介质模型,经过电磁仿真结果与实测数据相对比发现脊髓介质等质量扁长椭球体模型与实测昆虫RCS特性最接近。然后,基于Ku波段高分辨昆虫雷达外场实测昆虫回波数据,分析了昆虫动态RCS的起伏特性,将实测昆虫动态RCS起伏数据与4种经典的RCS起伏分布模型χ2, Log-normal, Weibull和Gamma分布分别进行了拟合分析,从最小二乘拟合误差和拟合优度检验结果可以看出,相比于其他3种模型,Gamma分布可以较好地描述昆虫目标RCS起伏的统计特性。最后,综述了昆虫RCS特性在昆虫雷达测量昆虫朝向、体重等参数测量的应用。
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关键词:
- 昆虫雷达 /
- 昆虫雷达散射截面积特性 /
- 电磁仿真 /
- 雷达散射截面积起伏
Abstract:Insect radar is the most effective tool for insect migration observation. In order to realize target recognition of insect radar, it is important to study the RCS characteristics of insects. This paper will analyze the static and dynamic Radar Cross Section (RCS) characteristics of insects. Firstly, based on the measured X-band fully-polarimetric RCS data, the static RCS characteristics of insects are analyzed, including the variations of horizontal and vertical polarization RCS with body weight respectively, and the variation of insect polarization pattern with body weight. Secondly, the dielectrics and geometric models currently used to study the RCS characteristics of insects are summarized by electromagnetic simulation. Twelve dielectric models consisting of four dielectrics (including water, spinal cord, dry skin, and chitin and hemolymph mixture) and three geometric models (including equivalent size prolate spheroid, equivalent mass prolate spheroid and triaxial prolate spheroid) are compared, and it be found that the RCS characteristics of equivalent mass prolate spheroid are closest to that of the real insects. Then, the fluctuation characteristics of insect dynamic RCS are analyzed based on the insect echo data measured in field by a Ku-band high-resolution insect radar. The measured insect dynamic RCS fluctuation data are fitted with four classical RCS fluctuation distribution models (χ2, Log-normal, Weibull and Gamma distribution), respectively. It can be seen from the least square error of fitting and goodness of fit test that Gamma distribution gives the best description of the statistical characteristics of insect RCS fluctuations. Finally, the application of insect RCS characteristics to insect orientation, mass and body length measurements for insect radars is summarized.
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表 1 实验昆虫样本信息
序号 昆虫名称 体长(mm) 体宽(mm) 体重(mg) 1 未辨识飞蛾1#1 11.1 2.8 25.6 2 未辨识飞蛾1#2 15.0 3.0 35.5 3 枯叶蛾#1 16.7 4.0 72.2 4 枯叶蛾#2 17.9 5.0 105.0 5 小地老虎 19.5 4.9 218.4 6 霜天蛾 34.8 9.1 319.7 7 未辨识飞蛾2 22.9 6.8 400.7 8 甘薯天蛾#1 38.9 9.0 530.1 9 甘薯天蛾#2 40.0 12.4 680.4 10 甘薯天蛾#3 36.8 10.2 935.3 表 2 介质密度及相对介电常数
介质 密度ρ(g/cm3) X波段相对介电常数 水 1.000 60.30-33.10j 脊髓 1.038 23.80-10.84j 干皮肤 1.045 31.30-14.41j 壳质与血淋巴混合物 1.260 34.30-18.60j 表 3 等尺寸椭球体模型质量百分比误差(%)
昆虫序号 水 脊髓 干皮肤 壳质混合物 1 –77.99 –84.75 –86.00 –124.27 2 –99.12 –106.68 –108.08 –150.88 3 –93.78 –101.14 –102.49 –144.16 4 –123.15 –131.63 –133.19 –181.17 5 –12.25 –16.51 –17.30 –41.43 6 –371.97 –389.91 –393.21 –494.69 7 –38.37 –43.63 –44.59 –74.34 8 –211.23 –223.05 –225.23 –292.14 9 –373.30 –391.29 –394.60 –496.36 10 –114.34 –122.48 –123.98 –170.06 平均误差 –151.55 –161.11 –162.87 –216.95 表 4 等质量椭球体模型体长百分比误差(%)
昆虫序号 水 脊髓 干皮肤 壳质混合物 1 17.48 18.50 18.69 23.60 2 20.51 21.49 21.67 26.41 3 19.79 20.78 20.96 25.74 4 23.48 24.42 24.59 29.15 5 3.78 4.97 5.18 10.91 6 40.38 41.12 41.25 44.80 7 10.26 11.37 11.57 16.91 8 31.51 32.35 32.51 36.59 9 40.44 41.18 41.31 44.86 10 22.44 23.40 23.57 28.19 平均误差 23.01 23.96 24.13 28.72 表 5 三轴椭球体模型高度百分比误差(%)
昆虫序号 水 脊髓 干皮肤 壳质混合物 1 43.82 45.87 46.23 55.41 2 49.78 51.62 51.94 60.14 3 48.39 50.28 50.62 59.04 4 55.19 56.83 57.12 64.43 5 10.91 14.17 14.75 29.29 6 78.81 79.59 79.72 83.18 7 27.73 30.37 30.84 42.64 8 67.87 69.05 69.25 74.50 9 78.87 79.65 79.78 83.23 10 53.34 55.05 55.35 62.97 平均误差 51.47 53.25 53.56 61.49 表 6 等质量椭球体模型RCS百分比误差(%)
介质 极化方向平行
体轴RCS极化方向垂直
体轴RCS水 224.3 22.1 脊髓 65.9 19.7 干皮肤 101.2 6.7 壳质与血淋巴混合物 68.8 32.8 表 7 分布函数表达式
分布函数 表达式 参数 ${\chi ^2}$ $p\left( \sigma \right) = \dfrac{m}{ {\varGamma \left( m \right)\bar \sigma } }{\left[ {\dfrac{ {m\sigma } }{ {\bar \sigma } } } \right]^{m - 1} }\exp \left[ {\dfrac{ { - m\sigma } }{ {\bar \sigma } } } \right]$ $\bar \sigma $为平均值,$2m$为自由度 Log-normal $p\left( \sigma \right) = \dfrac{1}{{\sigma \sqrt {4{\pi }\ln \rho } }}\exp \left\{ {\dfrac{{ - {{\left( {\ln \sigma - {\sigma _0}} \right)}^2}}}{{4\ln \rho }}} \right\}$ ${\sigma _0}$为中值,$\rho $为平均中值比 Gamma $p\left( \sigma \right) = \dfrac{1}{ { {\beta ^\alpha }\varGamma \left( \alpha \right)} }{\sigma ^{\alpha - 1} }\exp \left( { - \dfrac{\sigma }{\beta } } \right)$ $\alpha $是形状参数,$\beta $是尺度参数 Weibull $p\left( \sigma \right) = \dfrac{b}{a}{\left( {\dfrac{\sigma }{a}} \right)^{b - 1}}\exp \left( { - {{\left( {\dfrac{\sigma }{a}} \right)}^b}} \right)$ $a$是尺度参数,$b$是形状参数 表 8 昆虫RCS起伏PDF分布拟合误差
昆虫序号 RCS起伏
样本点数Log-normal ${\chi ^2}$ Gamma Weibull 1 1500 0.0812 0.3870 0.0747 0.0960 2 1250 0.1288 0.5774 0.1204 0.1307 3 1280 0.0724 0.7709 0.0710 0.1102 4 1340 0.0992 0.5652 0.0960 0.1262 5 1460 0.0861 0.3555 0.0765 0.0903 均值 0.0935 0.5312 0.0877 0.1107 表 9 昆虫RCS起伏PDF分布K-S检验参数D值
昆虫序号 RCS起伏
样本点数Log-normal χ2 Gamma Weibull 1 1500 0.0221 0.2141 0.0181 0.0370 2 1250 0.0306 0.2045 0.0169 0.0266 3 1280 0.0195 0.2094 0.0096 0.0342 4 1340 0.0211 0.1831 0.0181 0.0356 5 1460 0.0258 0.1583 0.0145 0.0271 均值 0.0238 0.1939 0.0154 0.0321 -
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