Aspheric lenses help meet the most demanding optical requirements while the precision injection molding technique hits the target for precision and cost. We developed a method of analyzing aberration terms in the transmitted “wavefront measurement,” determined by Shack–Hartmann wavefront sensing to estimate the fabrication errors of injection-molded aspheric elements. Considering aspheric element fabrication using a small training data set and F-measure fuzzy cluster analysis, an unsupervised learning method was applied to extract typical aberration terms from the wavefront polynomial. The experimental results suggest that these aberration terms, which are related to spherical (third-, fifth-, and seventh-order) and coma (third-order) aberration terms in the transmitted wavefront polynomial expansion, can be employed to estimate the surface error and decenter, respectively, of a lens from a specific mold cavity. The sampling lenses evaluated in the proposed measuring process were collected from different mold cavities according to their total working performance in the modulated transfer function measurement for the whole camera module. The performances of the typical aberration terms were discussed by comparing to the ones obtained from an interferometer and a profilometer. The proposed method could provide high detection efficiency and can thus be applied for the quality control of aspheric elements for mobile phones, where the existing errors are mainly spherical, coma, and astigmatism aberrations.
Laser imaging radar is the combination of four technologies, laser, radar, optical scanning control, and high-speed computer processing. It is extensively used in both military and civilian applications. Non-scanning imaging radar, which works without a scanning device, is characterized by high frame rate, wide field of view, and high reliability and has become the focus of research in recent years. The objective of this study is to firstly, elaborate the structure of non-scanning imaging laser radar and basic principle of plane array ranging. Next, it focuses on the latest developments in the non-scanning laser 3D imaging radar systems. Thereafter, it categorizes and summarizes various non-scanning laser 3D imaging radar systems, such as flash, polarization modulation, and gain modulation. From the comprehensive coverage of these systems presented in this study, it can be inferred that the laser 3D imaging has the advantages of high resolution, high energy utilization, and high signal-to-noise ratio. In addition, a discussion of their disadvantages is presented. Finally, this study concludes with some challenges and possible future research directions in this field.
Compressive sensing (CS), which breaks the classical Nyquist limit and does not require a high sampling rate, can be used to recover a complete signal by using much less information and an optimization strategy. Further, it reduces the calculations required for signal reconstruction, and requires simpler signal collection and processing than other sensing techniques. It can reduce the data rate of high-resolution imaging radar systems and the amount of sampling, storage, and transmission data effectively. In this study, we first describe the basic theory model of CS. Then, we review the latest developments in radar imaging algorithms based on CS, followed by a comprehensive review of CS applications in high resolution radars, including SARs/ISARs, through-the-wall (TTW) radars, MIIMO radars, and ground-penetrating (GP) radars. This review highlights the importance of CS in simplifying radar hardware, overcoming data limitations, and improving the radar imaging performance. Next, an in-depth discussion and analysis of the advantages and disadvantages of CS-based radar imaging are presented. Finally, we highlight some of the challenges and research directions in this field.
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