An Initial Alignment Algorithm Based on RSKF Single-Axis Rotational Inertial Navigation System

The problem of poor initial alignment anti-interference ability of the vehicle-mounted single-axis rotating inertial navigation system in complex environments leading to poor navigation accuracy. In this article, we combine the reverse navigation with the improved Sega-Husa filtering algorithm and propose an initial alignment method based on reverse navigation Sega-Husa Kalman filtering (RSKF). First, coarse alignment is performed, and key data are stored at the same time. After coarse alignment, the initial posture of coarse alignment and stored data are used for adaptive filtering alignment based on forward and reverse navigation. This method can fully mine and use the data. The experimental results show that compared with traditional algorithms, the method significantly augments the accuracy of alignment, thereby elevating the navigation precision of the vehicle’s single-axis rotational inertial guidance system.

Authors

Institutions

Publication Details

Journal
IEEE Sensors Journal
Published
2024-08-29
DOI
https://doi.org/10.1109/jsen.2024.3407063
Citations
3
Primary Topic
Inertial Sensor and Navigation
Type
article
Field-Weighted Citation Impact
3.90
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Initial Alignment Algorithm Based on RSKF Single-Axis Rotational Inertial Navigation System

Xiafu Peng, Gongliu Yang, Pengchao Yao, Jincheng Peng
3 citations
IEEE Sensors Journal
Inertial Sensor and Navigation
3.90
article

An Initial Alignment Algorithm Based on RSKF Single-Axis Rotational Inertial Navigation System

Xiafu Peng, Gongliu Yang, Pengchao Yao, Jincheng Peng
article en
3 citations

Abstract

The problem of poor initial alignment anti-interference ability of the vehicle-mounted single-axis rotating inertial navigation system in complex environments leading to poor navigation accuracy. In this article, we combine the reverse navigation with the improved Sega-Husa filtering algorithm and propose an initial alignment method based on reverse navigation Sega-Husa Kalman filtering (RSKF). First, coarse alignment is performed, and key data are stored at the same time. After coarse alignment, the initial posture of coarse alignment and stored data are used for adaptive filtering alignment based on forward and reverse navigation. This method can fully mine and use the data. The experimental results show that compared with traditional algorithms, the method significantly augments the accuracy of alignment, thereby elevating the navigation precision of the vehicle’s single-axis rotational inertial guidance system.

IEEE Sensors JournalVol. 24(19)
Xiamen University (CN)
Affordable and clean energy
Openalex Percentile: Top 6%
Inertial Sensor and Navigation
3.90
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

An Initial Alignment Algorithm Based on RSKF Single-Axis Rotational Inertial Navigation System — Xiafu Peng, Gongliu Yang, et al. · IEEE Sensors Journal (2024) | TGRS Research Map | TGRS