功率约束下低相关旁瓣的通导一体化波形研究

通信导航一体化是未来无线系统的发展趋势,可以更加充分地利用频谱资源。设计了一种新的一体化波形,在实现通信符号传递的同时,利用其进行时延测距进而实现相应的定位导航功能。一种联合的优化目标函数被提出,其中以星座图上的范数误差衡量通信性能,以自相关函数的加权积分旁瓣电平衡量波形的定时性能。结合一体化系统的实际,在问题求解时同时考虑了波形总功率约束和波形恒模约束,并采用变量交替迭代优化的算法进行迭代求解。最后利用数值仿真验证了算法的有效性。     

功率约束下低相关旁瓣的通导一体化波形研究

通信导航一体化是未来无线系统的发展趋势，可以更加充分地利用频谱资源。设计了一种新的一体化波形，在实现通信符号传递的同时，利用其进行时延测距进而实现相应的定位导航功能。一种联合的优化目标函数被提出，其中以星座图上的范数误差衡量通信性能，以自相关函数的加权积分旁瓣电平衡量波形的定时性能。结合一体化系统的实际，在问题求解时同时考虑了波形总功率约束和波形恒模约束，并采用变量交替迭代优化的算法进行迭代求解。最后利用数值仿真验证了算法的有效性。     

基于遗传算法的寻优解卫星星座优化设计策略

卫星星座优化设计与直接部署卫星或普通迭代计算后部署卫星等方法不同,目的 是在有限的资源中达到更好的星座观测效果.通过使用遗传算法(Genetic Algorithm),在卫星星座构型模型的基础上,得到星座种群内对目标观测实效性较强、重访周期较短的卫星个体,并使用较优的卫星个体生成Walker星座组网,实现了生成的星座对目标区域的高精度观测与覆盖.这种方法避免了复杂的计算与主观上的加权计算,在经济成本和观测效果相互制约的前提下,得到了更加高效的卫星星座构型设计策略.将此优化设计策略用于选定的卫星星座构型中,通过仿真实验表明,基于遗传算法优化后的"深圳一号"卫星星座相较于其优化前的部署,其对目标区域及全球区域的整体观测性能提升了90％以上.     

Low Earth orbit constellation design using a multi-objective genetic algorithm for GNSS reflectometry missions

Spaceborne global navigation satellite system reflectometry (GNSS-R) is an innovative bistatic radar remote sensing technique utilizing low Earth orbit (LEO) based GNSS-R instruments to acquire GNSS L-band opportunistic signals for measuring geophysical parameters. A GNSS-R LEO constellation with an optimization design for its specialized missions is very significant and necessary. However, the constellation design involves multi-parameter and multi-objective optimization, and the classical analytic solution is not capable of such a complicated issue. This study proposes a multi-objective LEO constellation design method with a genetic algorithm (GA) and presents a framework for designing two GNSS-R LEO constellations, termed “lower-latitude constellation” for typhoons and hurricanes observation in the tropics and “global constellation” for global geophysical parameter measurements. Then, the observation capability of both designed constellations is evaluated in terms of the number of reflection points, spatial coverage density, and revisit time to verify the GA efficiency in LEO constellation design. Results show that the two designed LEO constellations with high fitness function values possess optimal orbit parameter set configuration and outperform the existing CyGNSS constellations in observation performance. Compared with CyGNSS, the number of reflection points observed by the lower-latitude constellation and the global constellation increases by 38% and 45%, as well as the spatial coverage density increases by 28% and 36%. The revisit time for the lower-latitude constellation is reduced by 0.29 h, whereas the revisit time for the global constellation increases by one hour.