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Improvement in Moving Target Detection Based on Hough Transform and Wavelet

机译:基于霍夫变换和小波的运动目标检测方法的改进

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The most fundamental problem in radar signal is the detection of a moving object or a physical phenomenon. This problem became more challenging to the signal processing and radar communities under severe interference. In order to effectively detect moving targets in strong noise conditions, we proposed a new method based on wavelet and Hough transform for multiple moving targets detection. First, the noise is removed from the received signal by the wavelet technique. We propose an improved wavelet threshold function. The new threshold function not only reduces constant error of soft thresholding but also improves the discontinuity of hard thresholding. Second, the image processing technique of the Hough transform is used. The benefits of this method include improved performance of detection and implementation flexibility, which indicates the effectiveness and robustness of the algorithm.
机译:雷达信号中最基本的问题是对运动物体或物理现象的检测。对于严重干扰的信号处理和雷达社区来说,这个问题变得更具挑战性。为了有效地检测强噪声条件下的运动目标,提出了一种基于小波和霍夫变换的多目标运动检测方法。首先,通过小波技术从接收信号中去除噪声。我们提出了一种改进的小波阈值函数。新的阈值功能不仅减少了软阈值的恒定误差,而且改善了硬阈值的不连续性。第二,使用霍夫变换的图像处理技术。该方法的优点包括改进的检测性能和实现灵活性,这表明该算法的有效性和鲁棒性。

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