This paper presents an FPGA-based lightweight and real-time infrared image processor based on a series of hardware-oriented lightweight algorithms. The two-point correction algorithm based on blackbody radiation is introduced to calibrate the non-uniformity of the sensor. With precomputed gain and offset matrices, the design can achieve real-time non-uniformity correction with a resolution of $640\times 480$. The blind pixel detection algorithm employs the first-level approximation to simplify multiple iterative computations. The blind pixel compensation algorithm in our design is constructed on the side-window-filtering method. The results of eight convolution kernels for side windows are computed simultaneously to improve the processing speed. Due to the proposed side-window-filtering-based blind pixel compensation algorithm, blind pixels can be effectively compensated while details in the image are preserved. Before image output, we also incorporated lightweight histogram equalization to make the processed image more easily observable to the human eyes. The proposed lightweight infrared image processor is implemented on Xilinx XC7A100T-2. Our proposed lightweight infrared image processor costs 10,894 LUTs, 9367 FFs, 4 BRAMs, and 5 DSP48. Under a 50 MHz clock, the processor achieves a speed of 30 frames per second at the cost of 1800 mW. The maximum operating frequency of our proposed processor can reach 186 MHz. Compared with existing similar works, our proposed infrared image processor incurs minimal resource overhead and has lower power consumption.

With the continuous development of science and technology, laser ranging technology will become more efficient, convenient, and widespread, and it has been widely used in the fields of medicine, engineering, video games, and three-dimensional imaging. A time-of-flight (ToF) camera is a three-dimensional stereo imaging device with the advantages of small size, small measurement error, and strong anti-interference ability. However, compared to traditional sensors, ToF cameras typically exhibit lower resolution and signal-to-noise ratio due to inevitable noise from multipath interference and mixed pixels during usage. Additionally, in environments with scattering media, the information about objects gets scattered multiple times, making it challenging for ToF cameras to obtain effective object information. To address these issues, we propose a solution that combines ToF cameras with single-pixel imaging theory. Leveraging intensity information acquired by ToF cameras, we apply various reconstruction algorithms to reconstruct the object’s image. Under undersampling conditions, our reconstruction approach yields higher peak signal-to-noise ratio compared to the raw camera image, significantly improving the quality of the target object’s image. Furthermore, when ToF cameras fail in environments with scattering media, our proposed approach successfully reconstructs the object’s image when the camera is imaging through the scattering medium. This experimental demonstration effectively reduces the noise and direct ambient light generated by the ToF camera itself, while opening up the potential application of ToF cameras in challenging environments, such as scattering media or underwater.

微流量传感器用于精确测量和控制流经推力器的气体流量, 其性能直接影响冷气推力器系统的整体表现. 针对当前微流量传感器分辨率低、噪声大和响应时间慢的问题, 研制了一种基于恒温差原理的MEMS微流量传感器系统. 该传感器采用了4个MEMS铂电阻构成恒温差架构, 通过高精度恒温差驱动电路实现温差恒定, 经过测温电桥将温度变化信号经过高精度程控放大器输入到24位高精度模数转换器(ADC)进行采样, 实现了低噪声和高精度的微流量信号采集. 测试结果显示, 该微流量传感器在50～1000 Hz等效输出噪声小于0.126 μL·s^–1每根号赫兹, 分辨率达到0.06 μL·s^–1, 量程为0～1000 μL·s^–1, 响应时间为1.2 ms. 其测量分辨率高、噪声低、响应速度快, 为空间引力波探测中的冷气推力器系统提供了关键的技术支持.

To provide a ground-based experimental reference for free-space optical time–frequency synchronization in future space applications, this paper investigates the impact of beam drift and dynamic link-state variations on free-space laser links. A bidirectional free-space laser time–frequency synchronization and ranging system is established and the synchronization process is uniformly modeled. An improved Kalman filtering method based on innovation consistency is proposed in which a strong tracking mechanism enhances adaptability to model mismatch and abnormal observations; at the same time, an adaptive observation noise modeling strategy based on online statistical estimation characterizes the time-varying noise properties of free-space optical links. Experimental validation is conducted using an equivalent free-space laser link of approximately 321 m. The results show that the proposed method improves the time synchronization accuracy from 78.32 ps to 45.64 ps, corresponding to an enhancement of about 41%. In terms of time stability, the time deviation (TDEV) is reduced from $7.14\times {10}^{-11}$ s to $4.33\times {10}^{-11}$ s at an averaging time of $\tau =1$ s, and from $4.20\times {10}^{-12}$ s to $7.01\times {10}^{-13}$ s at $\tau =800$ s. For ranging performance, the system achieves an average measured distance of 321.56 m with a ranging standard deviation of 15.2 mm. These results demonstrate that the proposed approach enables high-precision and stable state estimation for integrated free-space laser time–frequency synchronization and ranging systems.