Based on electromagnetic scattering mechanism, Mie scattering theory and Monte Carlo method are used to analyze the radiation characteristics of SiC particle swarm with different distribution forms. The study find that the form of particle size distribution has a significant impact on the spectral transmittance of particle swarms. The proportion of particles of different sizes in the particle size distribution, the dispersion of particle size distribution, and the span of particle size scale all affect the infrared extinction performance of particle swarms in varying degrees. Among them, the proportion of particles of specific size in the particle size distribution is the most one, which is a necessary factor to ensure the existence and amplitude of particle characteristic spectra. The relationship between particle size distribution and radiation characteristics was deeply analyzed, and the results showed that increasing the proportion of particles in the 0.16~2.5 µm particle size range of SiC particle swarm can comprehensively improve the extinction performance of SiC particle swarm, this is of practical significance for optimizing the infrared radiation performance of particle swarms.
Improving the centroid and grayscale extraction accuracy of point targets is of great significance to the long distance detection system. There is a drop in centroid accuracy due to pixel sampling. For point targets, due to the small number of target pixels, the positioning accuracy is generally sub-pixel, and the use of optical dispersion to increase the number of target point pixels will reduce the signal-to-noise ratio of the point target, thereby reducing the detection distance of the system. In addition, there is a gap between the pixels of the infrared detector, and the grayscale response of the detector cannot reflect the real radiation intensity of the target. This paper simulates the point spread function based on the Gaussian function .The four parameters(the center coordinate, the width and the peak value) of the Gaussian function are estimated by a proposed optimization algorithm based on the obtained grayscale information of the point target. The results show that the grayscale extraction error is reduced from 35% of the grayscale summation algorithm to less than 10%, and the centroid error is also improved compared with the traditional centroid calculation algorithm.
Based on Mg/Na (NO3) 2 and Mg/Sr (NO3) 2, the combustion and radiation characteristics of pyrotechnics in vacuum were studied. The burning rate and visible light radiation characteristics of different samples were obtained, and the relationship between combustion performance (visible light intensity and burning rate) of the sample and vacuum environment pressure were further obtained. The results show that: 1) the linear burning rate and mass burning rate of the two formulations decrease with the decrease of pressure, and the burning rate has an exponential relationship with the pressure, and the sensitivity of Mg/Sr (NO3) 2 to ambient pressure is slightly higher than that of Mg/Na (NO3) 2; 2) Under the same vacuum pressure, the visible radiation intensity of Mg/Sr (NO3) 2 is significantly higher than that of Mg/Na (NO3) 2; 3) With the decrease of vacuum pressure, the visible light radiation intensity of the two formulations of pyrotechnic composition decreased. 4) According to the test data, the light intensity pressure index of Mg / Na (NO3) 2 is 1.07, which is more sensitive to environmental pressure than that of Mg/Sr (NO3) 2 system 0.598; 5) Based on the fitting formula, it is estimated that the visible light radiation intensity of Mg/Na (NO3) 2 system is 16cd, which is much less than that of Mg/Sr (NO3) 2 system 443cd.
Recently, ℓ1-based image deconvolution has demonstrated superior restoration performance to other regularizers, and thus, receives considerable attention. However, the restoration quality is generally sensitive to the selection of regularization parameter. The key contribution of this paper is to develop a novel data-driven scheme to optimize regularization parameter, such that the resultant restored image achieves minimum mean squared error (MSE). First, we develop Stein's unbiased risk estimate (SURE)--an unbiased estimate of MSE--for image degradation model. Then, we propose a recursive evaluation of SURE for the basic iterative shrinkage/thresholding (IST), which enables us to find the optimal value of regularization parameter by global search. The numerical experiments show that the proposed SURE-based optimization leads to nearly optimal deconvolution performance in terms of peak signal-to-noise ratio (PSNR).
For adapting to performance requirement of ultra wide-band and ultra high-speed signal processing in radar countermeasures equipment, a forwarding architecture of delay-superposition based on microwave photonics is suggested. Simultaneously, the method of delay-superposition modulation is researched and simulated. The interference effect is obtained briefly, which validated the effectiveness of microwave photonics delay-modulation in radar countermeasures.
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