A Study on a High-Precision 3D Position Estimation Technique Using Only an IMU in a GNSS Shadow Zone Article Swipe
Yanyun Ding
,
Yun-Sik Kim
,
Hunkee Kim
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/s25237133
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/s25237133
In Global Navigation Satellite System (GNSS)-denied environments, reconstructing three dimensional trajectories using only an Inertial Measurement Unit faces challenges such as heading drift, stride error accumulation, and gait recognition uncertainty. This paper proposes a path estimation method with a nine-axis inertial sensor that continuously and accurately estimates an agent’s path without external support. The method detects stationary states and halts updates to suppress error propagation. During motion, gait modes including flat walking, stair ascent, and stair descent are classified using vertical acceleration with dynamic thresholds. Vertical displacement is estimated by combining gait pattern and posture angle during stair traversal, while planar displacement is updated through adaptive stride length adjustment based on gait cycle and movement magnitude. Heading is derived from the attitude matrix aligned with magnetic north, enabling projection of displacements onto a unified frame. Experiments show planar errors below three percent for one-hundred-meter paths and vertical errors under two percent in stair environments up to ten stories, with stable heading maintained. Overall, the method achieves reliable gait recognition and continuous three-dimensional trajectory reconstruction with low computational cost, using only a single inertial sensor and no additional devices.
Related Topics
Concepts
Inertial measurement unit
Heading (navigation)
Computer science
Computer vision
Displacement (psychology)
Step detection
Gait
Position (finance)
Artificial intelligence
Acceleration
Trajectory
GNSS applications
Gyroscope
A priori and a posteriori
STRIDE
Global Positioning System
Geodesy
Accelerometer
Orientation (vector space)
Projection (relational algebra)
Inertial navigation system
Control theory (sociology)
Inertial frame of reference
Vertical displacement
Path (computing)
Gradient descent
Observational error
Error detection and correction
Gait analysis
Simulation
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s25237133
- https://www.mdpi.com/1424-8220/25/23/7133/pdf?version=1763796196
- OA Status
- gold
- References
- 36
- OpenAlex ID
- https://openalex.org/W7106506243
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W7106506243Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s25237133Digital Object Identifier
- Title
-
A Study on a High-Precision 3D Position Estimation Technique Using Only an IMU in a GNSS Shadow ZoneWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-11-22Full publication date if available
- Authors
-
Yanyun Ding, Yun-Sik Kim, Hunkee KimList of authors in order
- Landing page
-
https://doi.org/10.3390/s25237133Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/25/23/7133/pdf?version=1763796196Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1424-8220/25/23/7133/pdf?version=1763796196Direct OA link when available
- Concepts
-
Inertial measurement unit, Heading (navigation), Computer science, Computer vision, Displacement (psychology), Step detection, Gait, Position (finance), Artificial intelligence, Acceleration, Trajectory, GNSS applications, Gyroscope, A priori and a posteriori, STRIDE, Global Positioning System, Geodesy, Accelerometer, Orientation (vector space), Projection (relational algebra), Inertial navigation system, Control theory (sociology), Inertial frame of reference, Vertical displacement, Path (computing), Gradient descent, Observational error, Error detection and correction, Gait analysis, SimulationTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
36Number of works referenced by this work
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| abstract_inverted_index.angle | 95 |
| abstract_inverted_index.based | 109 |
| abstract_inverted_index.below | 139 |
| abstract_inverted_index.cost, | 177 |
| abstract_inverted_index.cycle | 112 |
| abstract_inverted_index.error | 24, 63 |
| abstract_inverted_index.faces | 17 |
| abstract_inverted_index.halts | 59 |
| abstract_inverted_index.modes | 68 |
| abstract_inverted_index.paper | 31 |
| abstract_inverted_index.paths | 144 |
| abstract_inverted_index.stair | 72, 75, 97, 152 |
| abstract_inverted_index.three | 8, 140 |
| abstract_inverted_index.under | 148 |
| abstract_inverted_index.using | 11, 79, 178 |
| abstract_inverted_index.while | 99 |
| abstract_inverted_index.During | 65 |
| abstract_inverted_index.Global | 1 |
| abstract_inverted_index.System | 4 |
| abstract_inverted_index.drift, | 22 |
| abstract_inverted_index.during | 96 |
| abstract_inverted_index.errors | 138, 147 |
| abstract_inverted_index.frame. | 134 |
| abstract_inverted_index.length | 107 |
| abstract_inverted_index.matrix | 122 |
| abstract_inverted_index.method | 36, 54, 164 |
| abstract_inverted_index.north, | 126 |
| abstract_inverted_index.planar | 100, 137 |
| abstract_inverted_index.sensor | 41, 183 |
| abstract_inverted_index.single | 181 |
| abstract_inverted_index.stable | 159 |
| abstract_inverted_index.states | 57 |
| abstract_inverted_index.stride | 23, 106 |
| abstract_inverted_index.Heading | 116 |
| abstract_inverted_index.aligned | 123 |
| abstract_inverted_index.ascent, | 73 |
| abstract_inverted_index.derived | 118 |
| abstract_inverted_index.descent | 76 |
| abstract_inverted_index.detects | 55 |
| abstract_inverted_index.dynamic | 83 |
| abstract_inverted_index.heading | 21, 160 |
| abstract_inverted_index.motion, | 66 |
| abstract_inverted_index.pattern | 92 |
| abstract_inverted_index.percent | 141, 150 |
| abstract_inverted_index.posture | 94 |
| abstract_inverted_index.through | 104 |
| abstract_inverted_index.unified | 133 |
| abstract_inverted_index.updated | 103 |
| abstract_inverted_index.updates | 60 |
| abstract_inverted_index.without | 50 |
| abstract_inverted_index.Inertial | 14 |
| abstract_inverted_index.Overall, | 162 |
| abstract_inverted_index.Vertical | 85 |
| abstract_inverted_index.achieves | 165 |
| abstract_inverted_index.adaptive | 105 |
| abstract_inverted_index.attitude | 121 |
| abstract_inverted_index.devices. | 187 |
| abstract_inverted_index.enabling | 127 |
| abstract_inverted_index.external | 51 |
| abstract_inverted_index.inertial | 40, 182 |
| abstract_inverted_index.magnetic | 125 |
| abstract_inverted_index.movement | 114 |
| abstract_inverted_index.proposes | 32 |
| abstract_inverted_index.reliable | 166 |
| abstract_inverted_index.stories, | 157 |
| abstract_inverted_index.support. | 52 |
| abstract_inverted_index.suppress | 62 |
| abstract_inverted_index.vertical | 80, 146 |
| abstract_inverted_index.walking, | 71 |
| abstract_inverted_index.Satellite | 3 |
| abstract_inverted_index.agent’s | 48 |
| abstract_inverted_index.combining | 90 |
| abstract_inverted_index.estimated | 88 |
| abstract_inverted_index.estimates | 46 |
| abstract_inverted_index.including | 69 |
| abstract_inverted_index.nine-axis | 39 |
| abstract_inverted_index.Navigation | 2 |
| abstract_inverted_index.accurately | 45 |
| abstract_inverted_index.additional | 186 |
| abstract_inverted_index.adjustment | 108 |
| abstract_inverted_index.challenges | 18 |
| abstract_inverted_index.classified | 78 |
| abstract_inverted_index.continuous | 170 |
| abstract_inverted_index.estimation | 35 |
| abstract_inverted_index.magnitude. | 115 |
| abstract_inverted_index.projection | 128 |
| abstract_inverted_index.stationary | 56 |
| abstract_inverted_index.trajectory | 172 |
| abstract_inverted_index.traversal, | 98 |
| abstract_inverted_index.Experiments | 135 |
| abstract_inverted_index.Measurement | 15 |
| abstract_inverted_index.dimensional | 9 |
| abstract_inverted_index.maintained. | 161 |
| abstract_inverted_index.recognition | 28, 168 |
| abstract_inverted_index.thresholds. | 84 |
| abstract_inverted_index.acceleration | 81 |
| abstract_inverted_index.continuously | 43 |
| abstract_inverted_index.displacement | 86, 101 |
| abstract_inverted_index.environments | 153 |
| abstract_inverted_index.propagation. | 64 |
| abstract_inverted_index.trajectories | 10 |
| abstract_inverted_index.uncertainty. | 29 |
| abstract_inverted_index.(GNSS)-denied | 5 |
| abstract_inverted_index.accumulation, | 25 |
| abstract_inverted_index.computational | 176 |
| abstract_inverted_index.displacements | 130 |
| abstract_inverted_index.environments, | 6 |
| abstract_inverted_index.reconstructing | 7 |
| abstract_inverted_index.reconstruction | 173 |
| abstract_inverted_index.one-hundred-meter | 143 |
| abstract_inverted_index.three-dimensional | 171 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile |