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Adaptive Near-Field Imaging with Robotic Arrays

机译:机器人阵列的自适应近场成像

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In this paper, we are interested in phased-array imaging of an unknown area using narrowband RF signals and arrays synthesized by an unmanned vehicle. Typical phased array imaging approaches use fixed or pre-determined array configurations for imaging, which are not usually informative for the whole area. In this paper, we then propose an iterative adaptive imaging approach where we identify the uncertain regions in an initial image that need to be sensed better, find the optimal array location and orientation for such a sensing task and finally combine the new image with the initial image to obtain a better overall imaging quality. Such an approach is easily enabled by using robots to synthesize arrays. We validate our proposed approach with numerical simulations and show that an adaptive approach improves the imaging quality as compared to imaging with fixed arrays.
机译:在本文中,我们对使用窄带RF信号和无人飞行器合成的阵列的未知区域进行相控阵成像感兴趣。典型的相控阵成像方法使用固定或预定的阵列配置进行成像,通常对整个区域没有帮助。然后,在本文中,我们提出了一种迭代自适应成像方法,其中,我们在初始图像中识别需要更好地感测的不确定区域,找到用于此类感测任务的最佳阵列位置和方向,最后将新图像与初始图像结合起来。图像以获得更好的整体成像质量。通过使用机械手合成阵列,可以轻松实现这种方法。我们通过数值模拟验证了我们提出的方法,并表明与采用固定阵列成像相比,自适应方法可提高成像质量。

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