Evidence map›Paper›PMID 42281038›Full record

ArticleSensors (Basel, Switzerland)2026

High-Precision Laser Time-Frequency Synchronization in Space Based on an Improved Kalman Filtering Method.

Boao Sun, Xiaoqing Wang, Zhibin Sun, Fu Zheng

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Boao SunNational Space Science Center, Chinese Academy of Sciences, Beijing 100190, China.
Xiaoqing WangNational Space Science Center, Chinese Academy of Sciences, Beijing 100190, China.
Zhibin SunNational Space Science Center, Chinese Academy of Sciences, Beijing 100190, China.
Fu ZhengNational Space Science Center, Chinese Academy of Sciences, Beijing 100190, China.ORCID 0000-0001-6635-8767

Funding

National Key Research and Development Program of China Grant 2023YFF07198
6 · The paper itself

Abstract

To provide a ground-based experimental reference for free-space optical time-frequency synchronization in future space applications, this paper investigates the impact of beam drift and dynamic link-state variations on free-space laser links. A bidirectional free-space laser time-frequency synchronization and ranging system is established and the synchronization process is uniformly modeled. An improved Kalman filtering method based on innovation consistency is proposed in which a strong tracking mechanism enhances adaptability to model mismatch and abnormal observations; at the same time, an adaptive observation noise modeling strategy based on online statistical estimation characterizes the time-varying noise properties of free-space optical links. Experimental validation is conducted using an equivalent free-space laser link of approximately 321 m. The results show that the proposed method improves the time synchronization accuracy from 78.32 ps to 45.64 ps, corresponding to an enhancement of about 41%. In terms of time stability, the time deviation (TDEV) is reduced from 7.14×10-11 s to 4.33×10-11 s at an averaging time of τ=1 s, and from 4.20×10-12 s to 7.01×10-13 s at τ=800 s. For ranging performance, the system achieves an average measured distance of 321.56 m with a ranging standard deviation of 15.2 mm. These results demonstrate that the proposed approach enables high-precision and stable state estimation for integrated free-space laser time-frequency synchronization and ranging systems.

Indexed as

free-spaceKalman filteringlaser rangingspace laser communicationtime–frequency synchronization

Identifiers

PMID42281038
PMCPMC13259332

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.