Evidence map›Paper›PMID 31963286›Full record

ArticleSensors (Basel, Switzerland)2020

A New In-Flight Alignment Method with an Application to the Low-Cost SINS/GPS Integrated Navigation System.

Zhenglong Lu, Jie Li, Xi Zhang, Kaiqiang Feng, Xiaokai Wei, Debiao Zhang, Jing Mi, Yang Liu

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
15.7field-weighted citation impact, top 2% of its field
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

3 citing papers in PubMed, 17 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Zhenglong LuNational Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, China.
Jie LiNational Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, China.
Xi ZhangSchool of Electrical Control Engineering, North University of China, Taiyuan 030051, China.
Kaiqiang FengNational Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, China.
Xiaokai WeiNational Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, China.
Debiao ZhangNational Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, China.
Jing MiNational Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, China.
Yang LiuNational Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, China.
North University of China · CN

Funding

National Natural Science Foundation of China No.51575500National Natural Science Foundation of China No.51705477National Natural Science Foundation of China No.61973280the National Natural Science Funds for Distinguished Young Scholars No.51225504
6 · The paper itself

Abstract

The optimization-based alignment (OBA) methods, which are implemented by the optimal attitude estimation using vector observations-also called double-vectors-have proven to be effective at solving the in-flight alignment (IFA) problem. However, the traditional OBA methods are not applicable for the low-cost strap-down inertial navigation system (SINS) since the error of double-vectors will be accumulated over time due to the substantial drift of micro-electronic- mechanical system (MEMS) gyroscope. Moreover, the existing optimal estimation method is subject to a large computation burden, which results in a low alignment speed. To address these issues, in this article we propose a new fast IFA method based on modified double-vectors construction and the gradient descent method. To be specific, the modified construction method is implemented by reducing the integration interval and identifying the gyroscope bias during the construction procedure, which improves the accuracy of double-vectors and IFA; the gradient descent scheme is adopted to estimate the optimal attitude of alignment without complex matrix operation, which results in the improvement of alignment speed. The effect of different sizes of mini-batch on the performance of the gradient descent method is also discussed. Extensive simulations and vehicle experiments demonstrate that the proposed method has better accuracy and faster alignment speed than the related traditional methods for the low-cost SINS/global positioning system (GPS) integrated navigation system.

Indexed as

in-flight alignmentintegrated navigation systemoptimization-based alignment

Identifiers

PMID31963286
PMCPMC7014501
OpenAlexW3000093403

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.