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71.
基于粒子群算法的绳系卫星展开与回收控制 总被引:3,自引:0,他引:3
绳系卫星的展开与回收是绳系卫星应用的基础问题,但通过改变系绳拉力来实现展开和回收的方法尚未得到充分研究.将系绳拉力作为控制力,并在时间域内离散,然后利用粒子群优化算法在整个可行域中寻找满足优化指标的最优值,从而得到控制力的变化规律.该控制方法可以使绳系卫星系统在最小摆动、最短时间等最优指标意义下,迅速展开到平衡位置,同时也适用于绳系卫星的回收.仿真结果表明:该控制方法同基于控制展开与回收速度的控制方法相比,展开和回收的时间短、侧向摆动小,具有一定优越性. 相似文献
72.
Junliang He Yong Zha Jiahua Zhang Jay Gao Qiang Wang 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2014
Aerosol optical depth (AOD) is one of the most important indicators of atmospheric pollution. It can be retrieved from satellite imagery using several established methods, such as the dark dense vegetation method and the deep blue algorithm. All of these methods require estimation of surface reflectance prior to retrieval, and are applicable to a certain pre-designated type of surface cover. Such limitations can be overcome by using a synergetic method of retrieval proposed in this study. This innovative method is based on the fact that the ratio K of surface reflectance at different angles/geometries is independent of wavelength as reported by Flowerdew and Haigh (1995). An atmospheric radiative transfer model was then established and resolved with the assistance of the ratio K obtained from two Moderate Resolution Imaging Spectroradiometer (MODIS) spectral bands acquired from the twin satellites of Terra and Aqua whose overpass is separated by three hours. This synergetic method of retrieval was tested with 20 pairs of MODIS images. The retrieved AOD was validated against the ground observed AOD at the Taihu station of the AErosol RObotic NETwork (AERONET). It is found that they are correlated with the observations at a coefficient of 0.828 at 0.47 μm and 0.921 at 0.66 μm wavelengths. The retrieved AOD has a mean relative error of 25.47% at 0.47 μm and 24.3% at 0.66 μm. Of the 20 samples, 15 and 17 fall within two standard error of the line based observed AOD data on the ground at the 0.47 μm and 0.66 μm, respectively. These results indicate that this synergetic method can be used to reliably retrieve AOD from the twin satellites MODIS images, namely Terra and Aqua. It is not necessary to determine surface reflectance first. 相似文献
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75.
《中国航空学报》2023,36(5):447-464
Person re-Identification (reID), aiming at retrieving a person across different cameras, has been playing a more and more important role in the construction of smart city and social security. For deep-learning-based reID methods, it has been proved that using local feature together with global feature could help to give robust representation for person retrieval. Human pose information can provide the locations of human skeleton to effectively guide the network to pay more attention to these key areas, and can also help to reduce the noise distractions from background or occlusions. Based on human pose, a Pose Guided Graph Attention (PGGA) network is proposed in this paper, which is a multi-branch architecture consisting of one branch for global feature and two branches for local key-point features. A graph attention convolution layer is carefully designed to re-assign the contribution weight of each extracted local feature by modeling the similarity relations. The experimental results demonstrate the effectiveness of our approach on discriminative feature learning. Our model achieves the state-of-the-art performance on several mainstream evaluation datasets. A plenty of ablation studies and different kinds of comparison experiments are conducted to prove the effectiveness of this work, including the tests on occluded datasets and cross-domain datasets. Moreover, we further design supplementary tests in practical scenario to indicate the advantage of our work in real-word applications. 相似文献