Back projection algorithm (BPA) and range migration algorithm (RMA) are two common approaches for image reconstruction in synthetic aperture radar (SAR) imaging. Imaging is implemented in spatial domain and spatial frequency domain, respectively and these two methods are often considered to generate the same results. This is true in normal microwave/millimeter wave SAR imaging systems, since the object of interests is located far away and the applied wavelength is long. In this case, the location of the object is the most important issue and there is no impetus to image the object with very fine details. In case of terahertz (THz) imaging, we have found some differences by using the two algorithms above, including the position of the object and resolution in 2D and 3D imaging. Some insights are given and we believe there should be some guidelines regarding the pros and cons before choosing the exact algorithm, especially when high-performance imaging is pursued. INDEX TERMS Ambient environment sensing, THz imaging, image reconstruction.
Compressive sensing (CS) is a novel sampling modality, which indicates the signals can be sampled at a rate much below the Nyquist sampling rate. CS has increasing interest recently due to high demand of rapid, efficient, and in‐expensive signal processing applications in the μmWave and mmWave frequencies, such as communication and imaging. There have been a lot of theoretical studies on this topic, but there is a lack of systematic experimental analysis of the implementation method itself. In this paper, we have investigated the influencing factors of terahertz compressive sensing based on experimental results, including illumination and the size of the pixel. Besides, to differentiate from current approaches, which generally make full use of the data, we propose to sort the data first and select a part of them based on amplitude, which might deliver a better image by prompting the mathematical calculations compulsively. We believe that such considerations given above would help to make a better system design and improve the performance of compressive imaging, and these results will also be helpful in the application of terahertz communication.
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