基于相似性传播聚类算法的机会信号选择

介绍了复杂低空环境下的机会信号导航方法,并提出了一种机会信号选择方法,解决了机会导航信号源类型多、数量多难以选择的问题.由于信号源的几何精度因子(GDOP,Geometry Dilution of Precision)越小则定位精度越高,同一区域信号对GDOP影响相似,因此采用聚类的方法选择信号.首先,将各信号间的距离作为相似度测量参数,通过相似性传播聚类算法获得相似类组;然后,依据类组的中心点确定所选类组;最后,从中选择组内的机会信号.经仿真,分析了不同分布的机会信号聚类特点,通过对汶川震区机会信号选择的仿真,验证了相似性传播聚类算法的有效性.另外,该方法在复杂低空飞行应用中将大大提高信号选择的效率.

Selection for signals of opportunity based on affinity propagation clustering method

The navigation method with signals of opportunity(SOOP) in the complex low airspace was introduced.Then a selection algorithm for SOOP was presented to solve the problem,which was hard to choose for the types of SOOP were various and the number of SOOP was so many.More less geometry dilution of precision(GDOP) for signals,the positioning accuracy would be higher.Consequently,the clustering method was considered to choose navigation signals because the signals in the same area influenced GDOP similarly.Firstly,each similarity between arbitrary two SOOP was expressed by their distance.Similar groups were acquired through the affinity propagation clustering method.Then,the groups were selected according to the centers of similar groups.Lastly,for navigation signals were chosen from the determinate groups.The simulation analyzed the rule of clustering for SOOP with different distributions.Then the algorithm simulation,which was applied in Wenchuan of Sichuan Province,proved the signal selection method effective.Meantime,this algorithm will greatly improve the efficiency of signal selection in the complex low airspace.