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

机译:稀疏分解在海杂波微动目标检测中的应用

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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:介绍了稀疏分解原理,提出了一种在海杂波中嵌入微动目标的检测算法,该算法可以在低信杂比环境下检测和提取微多普勒(m-D)信号。首先,建立了来自微动目标的雷达回波的三维模型,其中包括3-D旋转运动(俯仰,横摇和偏航运动)。然后,根据m-D信号的形式,利用线性调频字典提出了一种基于匹配追踪稀疏分解的检测算法。分级迭代法用于快速计算。最后,利用来自智能像素处理雷达的数据集进行的仿真验证了其与基于傅立叶变换字典的常用检测器相比的有效性和优越性。

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