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Cognitive Space-time Adaptive Processing Technology for Airborne Radar in Complex Environments
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摘要: 中国边境线地貌类型丰富，电磁信号密布，导致机载雷达在实际工作中面临的环境非常复杂。机载雷达在复杂地形环境和复杂电磁环境下探测性能严重下降，无法满足作战需求。认知空时自适应处理是一种有效的技术途径。该文提出了认知空时自适应处理架构，并在该架构基础上分别介绍了数据库、算法库、认知STAP技术和反馈控制等。仿真数据分析表明，相对于传统STAP技术，认知空时自适应处理技术可显著提升机载雷达在复杂环境下的运动目标检测性能。Abstract: China has one of the longest land borders in the world and features a diverse range of terrain types and a dense electromagnetic environment. Therefore, in practical applications, airborne radar faces complex environments. The efficacy of detecting airborne radar is severely deteriorated in regions with complex terrains and electromagnetic environments, limiting the ability to meet military operational requirements. Cognitive Space-Time Adaptive Processing (STAP) is an effective technical approach for addressing this problem. In this study, a cognitive STAP architecture is proposed, and based on this architecture, the database, algorithm library, cognitive STAP technology, and feedback control are introduced. Analysis of the simulated data reveals that compared to traditional STAP technology, cognitive space-time adaptive processing technology can significantly enhance the efficacy of detecting moving targets using airborne radar in complex environments.
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图 1 认知STAP技术实现架构框图
Figure 1. Implementation architecture diagram of cognitive STAP technology
图 5 非均匀杂波抑制方法处理流程
Figure 5. Processing flow of non-homogeneous clutter suppression method
图 7 非平稳杂波抑制方法处理流程
Figure 7. Processing flow of non-stationary clutter suppression method
图 8 共形阵机载雷达杂波功率谱补偿效果
Figure 8. Space-time clutter power spectrum compensation performance for conformal array airborne radar
图 12 机载雷达抗主瓣无意干扰方法实现流程框图
Figure 12. Implementation flowchart of airborne radar mainlobe unintentional jamming suppression method
图 13 杂波与目标在极化域上的分布情况
Figure 13. Clutter and target distribution characteristics in polarization domain
图 15 主瓣无意干扰抑制前后距离-多普勒谱图
Figure 15. Range-Doppler spectra before and after mainlobe unintentional jamming suppression
图 16 非平稳杂波抑制后的距离-多普勒谱图
Figure 16. Range-Doppler spectra before and after non-stationary clutter suppression
图 18 非均匀杂波抑制后的距离-多普勒谱图
Figure 18. Range-Doppler spectra before and after non-homogeneous clutter suppression
图 20 风电场杂波抑制后的距离-多普勒谱图
Figure 20. Range-Doppler spectra before and after wind farm clutter suppression
表 1 GLC_FCS30-2020数据包含的地表覆盖类型
Table 1. Surface cover types included in GLC_FCS30-2020 data
属性值 地表覆盖类型 属性值 地表覆盖类型 10 雨水灌溉农田 121 常绿灌木林 11 草本植物覆盖 122 落叶灌木林 12 果园 130 草原 20 未开垦耕地 140 地衣和苔藓 51 开放常绿阔叶林 150 稀疏植被 52 郁闭常绿阔叶林 152 稀疏灌木林 61 开放(郁闭度0.15～0.40)落叶阔叶林 153 稀疏草本 62 郁闭度大于0.4落叶阔叶林 180 湿地 71 开放(郁闭度0.15～0.40)常绿针叶林 190 不透水表面 72 郁闭度大于0.4常绿针叶林 200 裸露地区 81 开放(郁闭度0.15～0.40)落叶针叶林 201 固结裸露区域 82 郁闭度大于0.4落叶针叶林 202 未固结裸露区域 91 开放混合叶林 210 水体 92 封闭混合叶林 220 永久性冰雪 120 灌木林 
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表 3 机载雷达仿真参数
Table 3. Airborne radar simulation parameters
名称 符号 数值 载机高度 H 8 km 载机速度 V 140 m/s 脉冲数 K 100 接收机带宽 B 2.5 MHz 波长 λ 0.1 m 主波束方位角 θ0 90° 主波束俯仰角 $\varphi_0 $ 12° 脉冲重复频率 fr 12000 Hz占空比 D 0.1
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表 4 干扰及目标仿真参数
Table 4. Jamming and target simulation parameters
分类 名称 指标 干扰参数 调制方式 AM, OFDM, FM, PM 干扰信号个数 4 干扰方位角(°) 88, 89, 90, 91 干扰俯视角(°) 17.4, 17.1, 16.8, 16.1 基带频率(MHz) 0.3, 0.4, 0.5, 0.6 目标参数 目标方位角 88°≤θ≤92° 目标俯视角 16°≤$\varphi $≤17° 目标个数 8
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表 5 风电场参数
Table 5. Wind farm parameters
名称 叶片数量 叶片长度 风轮机高度 叶片转速 初相 风轮机1 3 20 m 60 m 0.52 r/s 10° 风轮机2 3 20 m 60 m 0.58 r/s 20° 风轮机3 3 20 m 60 m 0.56 r/s 20°
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表 6 风电场区域虚警点统计比较
Table 6. Wind farm clutter-induced false alarm points statistical comparison
方法 虚警点数 虚警占比 PD方法 67 0.037 传统STAP方法 47 0.026 认知STAP方法 25 0.013
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