基于改进Cao算法的奇异谱分析法及其在北斗多路径去噪中的应用

研究了基于奇异谱分析的北斗恒星日滤波算法,采用相空间重构Cao算法来确定奇异谱嵌入维度,并针对Cao算法的不足进行改进,提高奇异谱分析法的准确性和计算效率。分析北斗系统不同星座卫星的轨道重复周期特性,通过计算确定北斗系统多路径误差的周期约为86 160s。利用奇异谱分析法和传统小波分析法对北斗短基线解算结果进行恒星日滤波处理。结果表明,本文提出的奇异谱分析法多路径滤波效果优于小波滤波法,能较好地消除原始坐标序列中的多路径误差。

Singular Spectrum Analysis Based on Improved Cao Algorithm and Its Application in Beidou Multipath Filtering

In this paper, we study Beidou sidereal filtering algorithm based on improved SSA. The embedding dimension is determined by phase space reconstitution Cao algorithm, and we propose an improvement for the shortcomings of Cao algorithm. Thus, the computational efficiency and accuracy of the SSA method are improved. The repetitive cycle characteristics of different constellation satellites of Beidou system are analyzed, and the repeat cycle of the Beidou multipath error is estimated to be 86 160 s. The results of Beidou short baseline solution are processed by sidereal filtering based on singular spectrum analysis method and traditional wavelet method. The results indicate that the effect of SSA multipath filtering method are better than the wavelet method, and the multipath error in original coordinate sequence can be eliminated well.