LiDAR has become a key technology for autonomous driving. However, with the popularization of LiDAR, the laser signals emitted by multiple LiDAR at the same time in road environment will cause mutual interference, also known as crosstalk. Overcoming crosstalk has been a challenge that must be faced. Firstly, this paper analyzes the photon arrival time histogram characteristics of Time-Correlated Single Photon Counting LiDAR in the case of crosstalk. Then, the basic principle of interference suppression methods based on Pseudo-Random Pulse Position Modulation is introduced. Finally, we use interference suppression ratios to analyze the interference suppression effectiveness under different cumulative cycles and different random dynamic ranges. The simulation results show that when the laser repetition rates of the two LiDAR are the same, the larger the cumulative cycle number, the greater the interference suppression ratio; With the same cumulative number of cycles, the larger the random dynamic range of pulse position modulation, the greater the interference suppression ratio.
In order to remove or at least significantly reduce the interference caused by incident laser, the detection for the laser spot in infrared image is indispensable. According to the shape and gray distribution characteristics of laser spots, the laser spot is identified and located in the infrared image by using the SIFT feature matching algorithm. In order to verify the effectiveness of this method, interference laser irradiation experiments with different laser powers are carried out. The experimental results show that this method can accurately detect laser spots in infrared images, and can adapt to different sizes of laser spots.
Compared with the image target detection system of single infrared band , the target detection system of double infrared band image fusion has higher performance. However, the target detection of dual band image fusion requires higher real-time and stability of data processing. Aiming at the characteristics of large amount of data and complex algorithm of dual band image fusion target detection system, a dual band infrared image target detection system based on DSP+FPGA architecture is designed. This system has the advantage that DSP is good at realizing complex image processing algorithms and FPGA has high speed parallel processing capacity. This design meets the system's requirements for real time and stability.
KEYWORDS: Solar cells, Infrared radiation, Solar radiation, Solar radiation models, Sun, Solar energy, Temperature metrology, Atmospheric modeling, Thermal modeling
The infrared characteristics of the target is very important for target recognition. The infrared radiation characteristics are different between damaged solar panel and normal working solar panel. It is the characteristic position for the solar panels’ nondestructive fault testing. In this paper, the temperature model of solar panels is established, and the numerical calculation is carried out. The calculated results and the measured data matching well verify the correctness of the calculation model. The results also show that the temperature of solar panels which are damaged are higher than the temperature of those who are normal working. On the basis of the temperature calculation, the infrared radiation characteristics of solar panels are calculated .The result shows also that the infrared radiation intensity of those damaged solar panels are higher than the normal working solar panels. This provides the theoretical support for the infrared nondestructive testing of solar panels.
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