An Inter-Frequency Cross-Validation Approach for Pseudo-Range Fault Detection in GNSS Relative Positioning.

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Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

3 authors.

Zhaoyang LiCollege of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China.ORCID 0000-0001-7202-152X

Dingjie WangCollege of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China.ORCID 0000-0003-3827-8449

Jie WuCollege of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For Global Navigation Satellite System (GNSS) relative positioning, faulty pseudorange measurements may lead to over-bounded relative positioning errors, which entails high-performance fault detection and exclusion (FDE). This paper proposes an effective fault detection and exclusion method for pseudorange-based GNSS relative positioning utilizing the technique of the inter-frequency cross-validation (IFCV). Multi-frequency differenced pseudorange measurements are utilized to establish multiple inter-frequency test statistics for efficient detection of multiple outliers; the conservative strategy is adopted to exclude multiple faults for robust position determination. Compared with conventional ARAIM (Advanced Receiver Autonomous Integrity Monitoring) method, the experimental results indicate that the proposed IFCV method exhibits lower false alarm rates (0.03% vs. 1.88%) and missed detection rates (0% vs. 1.02%). By artificially injecting random faults into GNSS measurements, conventional differential pseudorange-based method shows a significant decrease in positioning accuracy by 354%, while both IFCV and ARAIM methods improve positioning accuracy by 78% and 55%, respectively. Apart from advantages in accuracy over ARAIM method, the proposed IFCV demonstrates a computational efficiency improvement of 10

Indexed as

cross-validationdifferential pseudorange relative positioningfault detection and exclusionmulti-frequency multi-GNSS

Identifiers

PMID40871769

DOI10.3390/s25164908

PMCPMC12390501

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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.