Aiming at the problem that the calculation of interception probability of tactical missile with phased array seeker is inaccurate due to the beam broadening during the scanning of phased array radar, a calculation strategy of interception probability based on wave position arrangement in sinusoidal space coordinate system is proposed. The sinusoidal space coordinate system is used to arrange the wave position, and then the obtained wave position coordinate is transformed to the radar station coordinate system. According to the main error sources affecting the interception probability and their statistical characteristics, the calculation method of the interception probability is designed, combined with the designed wave position arrangement to calculate the interception probability. The simulation results show that the calculation strategy of interception probability based on sinusoidal spatial coordinate system can effectively solve the problem of inaccurate calculation of interception probability caused by beam broadening
Speckle noise exerts a noticeable impact on the quality of synthetic aperture radar (SAR) images. It could harm their applications in the remote sensing field, for example, the land cover classification. This paper presents a SAR image despeckling method by using the variance constrained convolutional neural network (CNN). We exploit the significant distinction between speckle noise and ground truth from the viewpoint of their statistical characteristics. The estimated noise variance as well as a weighting factor is introduced into the loss function. It can drive the learning of network to produce the result with more dispersion. After the model training, the variance constrained CNN could generate the despeckled SAR image by means of noise matrix estimation from an input contaminated by strong speckle. Finally, experiments on synthetic SAR images are conducted to demonstrate its effectiveness. It indicates that the proposed method is not only independent of image background in training, but also outperforms the classical SAR despeckling CNN.
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