The infrared imaging system represents the culmination of modern science and technology, finding extensive applications in aerospace, weapon electronics, security, industrial testing, and other fields. Target detection probability is a crucial parameter for evaluating the performance of an infrared imaging system and is closely linked to its design. While the Johnson criterion considers minimum resolvable temperature difference (MTRD) to assess the performance of infrared imaging systems, there exists an issue regarding low accuracy when applying infrared focal plane array (FPA) detectors. This paper proposes utilizing the targeting task performance (TTP) metric, that incorporates system sensitivity by considering a partial weighted integral of target background contrast exceeding the system contrast threshold function as a measure of information quantity within the system for simulating target detection performance in an infrared photoelectric system. In this study, we selected an uncooled infrared FPA detector and employed night vision integrated performance model (NV-IPM) software, along with control variable analysis to investigate how changing various system parameters affects the imaging performance of our proposed infrared photoelectric system. The purpose of this study to provide fundamental parameters for infrared imaging system optimizing future designs before research and development.
With the improvement of computer computing power, the object detection algorithms based on deep neural network has ushered in vigorous development, and has been widely used in industry, agriculture, medicine, military and other fields. One-stage object detection algorithms shows the superiority in real-time detection compared to other object detection algorithms such as two-stage object detectors or ViT-based detectors. At the same time, more and more anchor-free detectors show the advanced nature of anchor-free algorithms compared to anchor-based detectors. In this paper, we review the one-stage anchor-free real-time object detection algorithms in recent years, and analyze the application scenarios and optimization strategies of future object detection algorithms. Firstly, the principle and advantages of anchor-free object detection algorithms and one-stage object detection algorithm are introduced. Secondly, the network structure and innovation of anchor-free object detection algorithms in recent years are summarized. Finally, the possible development direction and trend of one-stage anchor-free real-time object detection algorithms in the future are proposed.
Under thermal loading, low stress assembly is one of the key factors to ensure the pointing stability of the splitting prism assembly in a multiband optical mechanical system. By analyzing the common bonding methods of prism assembly, the factors affecting the bonding stability include the transverse stress of multi-point bonding, the internal stress of the adhesive and the longitudinal stress perpendicular to the bonding surface. Then, the optimization methods are proposed, e.g., reducing the span of bonding surface, increasing the free end area of bonding and adding longitudinal constraints. The simulation results show that the variety of all surfaces of the prism is restrained under the temperature load of - 45 ℃ to 60 ℃, the change of surface shape is reduced from 0.381µm to 0.148µm at 60 ℃ and from 0.982µm to 0.553µm at - 45 ℃, which improves the pointing stability of the splitting prism. It’s indicated that this bonding technology can effectively improve the pointing stability of splitting prism and can be applied to the engineering design of the precision optical system.
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