We present an approach to image deconvolution in active incoherent millimeter-wave (AIM) imaging. While traditional incoherent imaging systems capture thermal radiation from the scene, AIM imaging uses the transmission of noise signals to increase the signal-to-noise ratio (SNR) while maintaining the necessary space–time incoherence required for image reconstruction. Images formed by any imaging technique are corrupted by the impulse response, or point spread function (PSF), of the imaging system; however, the degradation of the image due to the PSF can be alleviated significantly via deconvolution if the PSF is characterized. Typically, estimation of the PSF is challenging due to spatial undersampling and the impact of noise. In this work, we experimentally demonstrate an approach to estimate the PSF of AIM imaging systems by averaging PSF estimates from multiple point targets using a shift-and-add method in a 38-GHz imaging system. We demonstrate image deconvolution using the CLEAN algorithm to reconstruct a scene with multiple targets.

中文翻译：

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主动非相干毫米波成像的非相干点扩展函数估计和多点反卷积

我们提出了一种在主动非相干毫米波 (AIM) 成像中进行图像反卷积的方法。传统的非相干成像系统从场景中捕获热辐射，而 AIM 成像使用噪声信号的传输来提高信噪比 (SNR)，同时保持图像重建所需的必要时空不相干性。任何成像技术形成的图像都会被成像系统的脉冲响应或点扩散函数 (PSF) 破坏；然而，如果对 PSF 进行表征，则可以通过反卷积显着减轻由 PSF 引起的图像退化。通常，由于空间欠采样和噪声的影响，PSF 的估计具有挑战性。在这项工作中，我们通过在 38-GHz 成像系统中使用移位和相加方法对来自多个点目标的 PSF 估计值进行平均，通过实验证明了一种估计 AIM 成像系统的 PSF 的方法。我们演示了使用 CLEAN 算法重建具有多个目标的场景的图像反卷积。