基于Vondrak-Cepek组合滤波和注意力机制加权的时间比对融合算法

doi:10.12305/j.issn.1001-506X.2025.02.34

Abstract

Abstract:

To solve the problems of the diurnal and low short-term stability in two-way satellite time and frequency transfer (TWSTFT), a Transformer weight matrix based on the attention mechanism is introduced. The Vondrak-Cepek combined filtering method is applied to fuse the TWSTFT and Global Positioning System (GPS) P3 code common view method time alignment links between the National Time Service Center (NTSC) and Physikalisch-Technische Bundesanstalt(PTB). The performance indicators of the links before and after fusion are analyzed and compared with the GPS precise point positioning (GPS PPP) time alignment reference links with no diurnal and high short-term stability. The results show that the standard deviation of Vondrak-Cepek combined filtering fusion method with the attention mechanism weight is 0.310 9 ns comparing with the reference link GPS PPP, which can reduce the diurnal of TWSTFT and enhance the overall stability of the link.

Key words: Vondrak-Cepek combined filtering, attention mechanism, time alignment, data fusion

CLC Number:

P127.1
TN713

Qiang LIU, Haoran SUN, Denghua HU, Shuang ZHANG. Time alignment fusion algorithm based on Vondrak-Cepek combined filtering and attention mechanism weighting[J]. Systems Engineering and Electronics, 2025, 47(2): 673-679.

Figures/Tables 11

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References 16

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周期	平滑系数	T/T′
周期	平滑系数	0.1	0.3	0.5	0.7	0.99
P=0.5	ε	437 540	1 687 600	3 937 800	9 188 300	389 850 000
P=0.5	ε	2 771	10 687	24 937	58 186	2 468 700
P=1	ε	6 837	26 370	61 529	143 570	6 091 400
P=1	ε	173	668	1 559	3 637	154 300
P=1.5	ε	600	2 315	5 402	12 604	534 770
P=1.5	ε	34	132	308	718	30 478

方法	最大值	最小值	标准差	均值
TW+P3	0.421 5	-4.275 9	1.234 0	-1.538 5
TW′+P3′	-0.039 4	-4.301 9	1.158 3	-1.506 5
TWSTFT	3.626 0	-7.238 0	1.756 1	-1.542 9
GPS P3	1.472 0	-5.906 0	1.403 5	-1.538 5
GPS PPP	0.613 0	-4.333 0	1.251 3	-1.542 4

方法	最大值	最小值	标准差
TW+P3-GPS PPP	0.444 9	-0.392 5	0.183 0
TW′+P3′-GPS PPP	0.751 2	-0.699 6	0.310 9
TWSTFT-GPS PPP	5.207 0	-4.200 0	1.284 9
GPS P3-GPS PPP	1.638 0	-1.991 0	0.685 2

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Time alignment fusion algorithm based on Vondrak-Cepek combined filtering and attention mechanism weighting

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