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Application of the sparse decomposition to micromotion target detection embedded in sea clutter

机译:稀疏分解在海杂波中嵌入微调目标检测

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The sparse decomposition principle is introduced and a detection algorithm of target with micro-motion embedded in sea clutter is proposed, which can detect and extract micro-Doppler (m-D) signals in low signal-to-clutter ratio environment. Firstly, the three dimensional model of radar echo from micro-motion target is established including the 3-D rotated movements (pitch, roll, and yaw movements). Then, the detection algorithm based on matching pursuit sparse decomposition is proposed with chirp dictionary according to the form of m-D signals. The grading iterative method is employed for fast computation. In the end, simulations with dataset from the intelligent pixel processing radar verify the effectiveness as well as superiority over the commonly used detector based on Fourier transform dictionary.
机译:提出了稀疏分解原理,并提出了一种嵌入在海杂波中的微型运动的目标的检测算法,其可以检测和提取低信令到杂波比环境中的微多普勒(M-D)信号。首先,建立了来自微观运动目标的雷达回波的三维模型,包括3-D旋转运动(俯仰,卷和偏航运动)。然后,根据M-D信号的形式提出了基于匹配追踪稀疏分解的基于匹配追踪分解的检测算法。用于快速计算的分级迭代方法。最后,使用来自智能像素处理雷达的数据集的模拟验证了基于傅里叶变换字典的常用探测器的有效性以及优越性。

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