高级检索

基于数据流的漂移性多光斑聚类算法研究

Research on drifting multi spot clustering algorithm based on data stream

  • 摘要: 为了降低多接入通信系统误比特率,基于四象限探测器的多目标光斑分辨技术,分析了通信激光光斑数据流的特点,对3种传统聚类算法进行了比较。对在多光斑分辨方面表现出更好综合效果的k均值聚类算法进行了扩展,提出了基于数据流的漂移性多光斑聚类算法。首先通过初始聚类自适应选择最优簇数,然后对新光斑数据进行实时漂移检测和聚类,并对算法的分类判决参数进行实时更新。结果表明, 该算法解决了光斑漂移下的多光斑分辨问题,光斑分辨精确度相比传统算法有显著提高,稳定在90%以上。该研究提高了通信质量, 为多接入通信的实现提供了算法支撑。

     

    Abstract: In order to reduce the bit error rate of multi access communication systems, the multi-target spot resolution technology based on four quadrant detectors was used to analyze the characteristics of communication laser spot data streams, and three traditional clustering algorithms were compared. The k-means clustering algorithm, which exhibited better comprehensive performance in multi spot resolution, was extended to propose a drift based multi spot clustering algorithm based on data streams. The optimal number of clusters was selected through initial clustering first adaptively, then real-time drift detection and clustering were performed on new spot data, and the classification decision parameters of the algorithm were updated in real time. The results show that, the problem of multi spot resolution under spot drift is solved by this algorithm, and the spot resolution accuracy is significantly improved compared to traditional algorithms, stabilizing at over 90%. This study has improved communication quality and provided algorithm support for the implementation of multi access communication.

     

/

返回文章
返回