Feature Extraction of Rotor Blade Targets Based on Phase Compensation in a Passive Bistatic Radar
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摘要: 全球定位导航系统(GNSS)作为一种覆盖广泛的稳定信号源,对于微动目标特性识别具有相当大的实用价值。针对外辐射源旋翼目标识别问题,该文提出基于相位补偿的旋翼特征提取新思路。通过分析旋翼目标时频域内闪烁分布的数学形成机理,提出利用相位补偿的方法将相同叶片的闪烁聚焦到特定多普勒频率,进而估计旋翼的叶片数。然后依据闪烁中心频率距离基准频率最近的原则从参数矩阵中估计叶片转速等参数,并利用闪烁占据的带宽计算叶片的长度。最后仿真实验结果验证该方法对参数空间设置的适用性更强,估计精度也更高,并且可以在回波域实现旋翼目标的叶片分离。Abstract: As a stable and widely covered signal resource, a Global Navigation Satellite System (GNSS) plays an important part in micro-Doppler extraction in a near field. This paper aims at the problems associated with rotor blade target recognition and proposes a novel solution based on phase compensation. First, the mathematical mechanism of flicker distribution in a time-frequency field is analyzed, and phase compensation is used to achieve the Doppler focusing, and then the blade number can be estimated. Second, according to the that the minimum delta frequency principle between the center frequency and standard frequency, the rotation velocity of the rotor blade is obtained. Next, blade lengths can be calculated through the flicker bandwidth in the time-frequency domain. Finally, the simulation experiments validate the effectiveness of the proposed method.
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Key words:
- Passive bistatic radar /
- Micro-motion /
- Time-frequency flicker /
- Phase compensation /
- Center frequency
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表 1 仿真实验参数
Table 1. The parameters in simulation experiments
参数 数值 频段 1575.42 MHz 叶片数 3, 4 叶片长度 7.3 m 旋转速率fr 4.8 r/s 信噪比 –10 dB 采样率 2.046 MHz 表 2 非对称旋翼结构基准闪烁的更新
Table 2. The update of standard flashes in asymmetry rotor target
迭代次数 基准闪烁位置 1 (0.067 s) 2 (0.067 s, 0.171 s) 3 (0.067 s, 0.171 s, 0.275 s) 4 (0.067 s, 0.171 s, 0.275 s, 0.379 s) 表 3 对称旋翼结构基准闪烁的更新
Table 3. The update of standard flashes in symmetry rotor target
迭代次数 基准闪烁/位置 1 (0.067 s) 2 (0.067 s, 0.275 s) 3 (0.067 s, 0.275 s, 0.483 s) 表 4 OMP算法实验条件
Table 4. The experiment condition of OMP algorithm
方法 叶片数 叶片长度L (m) 初相角 (°) 实验a 1, 3, 5, 7 5:0.01:8 0:2.4:120 实验b 1, 3, 5, 7 6:0.01:8 0:2.4:120 实验c 1, 3, 5, 7 6:0.01:8 0:12:120 表 5 参数估计结果对比
Table 5. The parameter estimation result of different algorithms
方法 叶片数$ \hat Q $ (个) 长度$ \hat L $ (m) 角速度$ \hat w $ (rad/s) 本方法,Q=3 3 7.34 $ 2\pi \times 4.80 $ 本方法,Q=4 4 7.38 $ 2\pi \times 4.80 $ Hough,Q=3 3 7.35 $ 2\pi \times 4.77 $ OMP,实验a 无效 5.82 $ 2\pi \times 11.21 $ OMP,实验b 3 7.45 $ 2\pi \times 4.80 $ OMP,实验c 无效 7.05 $ 2\pi \times 6.73 $ -
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