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The signal acquisition and processing ability of distributed temperature sensors based on Raman scattering (DTS-Raman) directly determines the accuracy, spatial resolution, temperature resolution, and other key indicators of the entire system. Real-time and effective processing is the key to ensuring the practicability of the field system. Owing to the long distance of the distributed temperature sensors (DTS) system, the energy of the weak Raman scattering is further reduced when it reaches the avalanche photodiode (APD) detector because of fiber loss, which results in a decrease in the signal-to-noise ratio (SNR) and an increase in the temperature measurement error. To improve the SNR and ensure the accuracy of the demodulation temperature, the signal acquisition and processing module must be able to perform real-time and fast processing of large amounts of data. The existing processing structure based on the acquisition board requires a special personal computer (PC) and host processing software, which limits the application of DTS system. Therefore, a real-time acquisition and processing scheme based on field-programmable gate array (FPGA) is proposed in this paper. A set of cyclic shift register sequence (CSRS) with Ping-Pang functions is designed to improve the storage efficiency. According to the period of the laser source, the accumulated results stored in the CSRS and echo pulse data are accumulated and shifted in real time to realize circular utilization of storage resources. A DTS-Raman system prototype and test platform are built to verify the effects of the proposed scheme. The experimental results show that the scheme can realize a temperature accuracy within ±0.475°C in real time and has a high resource utilization efficiency.

Compared with land and air target detection, the background of video image sequence of sea moving target is more complex and changeable. In addition to considering illumination variation, shoreline targets occlusion, digital swing and other problems, interference factors such as irregular wave fluctuation and a large number of near-shore breaking waves need to be considered. Because of the size, shape, moving speed and the color correlation between the sea background, it is very difficult to detect moving targets of the sea surface. This paper analyzes the sea moving target detection method based on the mixed multi-Gaussian difference model and applies it to the offshore sea-surface video surveillance. By analyzing the characteristics of near-shore sea-surface target image, the complex scene of ocean dynamic change, the characteristics of inter-frame difference and background difference, the real-time updating strategy of mixed multi-Gaussian background models is studied on the basis of traditional frame difference and mixed Gaussian difference target detection methods, and a mixed multi-Gaussian difference detection model is designed. Through theoretical simulation, the traditional interframe difference method, mixed Gaussian difference method and the proposed method is compared and verified. The simulation results show that the improved algorithm model can detect the outline and detail features of moving targets at sea, especially for fast target detection. In addition, the algorithm does not need the prior knowledge of the scene and can update the background model adaptive in real time, has good environmental robustness.