A Method for Assisting GNSS/INS Integrated Navigation System during GNSS Outage Based on CNN-GRU and Factor Graph
Abstract
:1. Introduction
2. Integrated System Solution
3. Factor Graph Integrated Navigation Framework
3.1. Factor Graph Information Fusion Theory
3.2. IMU Pre-Integration Factor Node
3.3. GNSS Factor Nodes
4. CNN-GRU Neural Network Prediction-Assisted Positioning Method
4.1. CNN-GRU Model
4.2. CNN-GRU-Based GNSS Outage Assisted Prediction
5. Experiment
5.1. Experimental Setup and Data Acquisition
- (1)
- FGO: factor graph-based integrated navigation method;
- (2)
- LSTM-FGO: factor graph-based integrated navigation method assisted by a long short-term memory (LSTM) network;
- (3)
- CNN-GRU-FGO: The proposed integrated navigation method, combining convolutional neural network (CNN) and gated recurrent unit (GRU) with factor graph assistance.
5.2. Experimental Verification and Analysis
5.2.1. Frequent Interruption Test
5.2.2. Continuous Interruption Test
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Sensor | Parameters | Accuracy |
---|---|---|
IMU | Gyroscope Bias | 20°/h |
GNSS | Gyroscope Random Walk | |
Accelerometer Bias | 50 mg | |
Sampling Frequency | 100 Hz | |
Position Accuracy | 2 m | |
Sampling Frequency | 1 Hz |
Start Time (s) | Interruption Duration (s) | Start Time (s) | Interruption Duration (s) | Start Time (s) | Interruption Duration (s) |
---|---|---|---|---|---|
70 | 4 | 450 | 2 | 616 | 6 |
96 | 2 | 465 | 5 | 650 | 6 |
156 | 8 | 471 | 3 | 662 | 8 |
168 | 14 | 474 | 4 | 686 | 12 |
183 | 25 | 482 | 10 | 717 | 6 |
241 | 25 | 511 | 7 | 730 | 5 |
320 | 6 | 543 | 5 | 775 | 7 |
366 | 2 | 597 | 11 | ||
413 | 9 | 608 | 7 |
Section 1 | Algorithm | Orientation | RMSE (m) | Maximum Error (m) |
---|---|---|---|---|
winding road | FGO | east | 3.06 | 14.91 |
north | 3.54 | 13.19 | ||
LSTM-FGO | east | 0.62 | 3.41 | |
north | 0.90 | 4.48 | ||
CNN-GRU-FGO | east | 0.27 | 1.81 | |
north | 0.40 | 1.92 | ||
long straight road | FGO | east | 0.38 | 0.99 |
north | 1.35 | 3.67 | ||
LSTM-FGO | east | 0.26 | 0.85 | |
north | 0.19 | 0.80 | ||
CNN-GRU-FGO | east | 0.05 | 0.19 | |
north | 0.12 | 0.56 | ||
all road | FGO | east | 2.34 | 14.91 |
north | 2.84 | 13.19 | ||
LSTM-FGO | east | 0.50 | 3.41 | |
north | 0.70 | 4.48 | ||
CNN-GRU-FGO | east | 0.21 | 1.81 | |
north | 0.31 | 1.92 |
Start Time (s) | Interruption Duration (s) | Start Time (s) | Interruption Duration (s) | Start Time (s) | Interruption Duration (s) |
---|---|---|---|---|---|
44 | 144 | 432 | 6 | 789 | 4 |
285 | 4 | 469 | 5 | ||
310 | 8 | 534 | 108 |
Section 2 | Algorithm | Orientation | RMSE (m) | Maximum Error (m) |
---|---|---|---|---|
winding road | FGO | east | 5.73 | 25.42 |
north | 41.48 | 141.69 | ||
LSTM-FGO | east | 0.48 | 1.66 | |
north | 1.08 | 3.62 | ||
CNN-GRU-FGO | east | 0.19 | 1.49 | |
north | 0.28 | 2.18 | ||
long straight road | FGO | east | 1.33 | 3.81 |
north | 30.79 | 98.44 | ||
LSTM-FGO | east | 0.41 | 2.58 | |
north | 0.62 | 3.54 | ||
CNN-GRU-FGO | east | 0.13 | 1.08 | |
north | 0.24 | 1.60 | ||
all road | FGO | east | 4.16 | 25.42 |
north | 36.55 | 141.69 | ||
LSTM-FGO | east | 0.45 | 2.58 | |
north | 0.88 | 3.62 | ||
CNN-GRU-FGO | east | 0.16 | 1.49 | |
north | 0.26 | 2.18 |
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Zhao, H.; Liu, F.; Chen, W. A Method for Assisting GNSS/INS Integrated Navigation System during GNSS Outage Based on CNN-GRU and Factor Graph. Appl. Sci. 2024, 14, 8131. https://doi.org/10.3390/app14188131
Zhao H, Liu F, Chen W. A Method for Assisting GNSS/INS Integrated Navigation System during GNSS Outage Based on CNN-GRU and Factor Graph. Applied Sciences. 2024; 14(18):8131. https://doi.org/10.3390/app14188131
Chicago/Turabian StyleZhao, Hailin, Fuchao Liu, and Wenjue Chen. 2024. "A Method for Assisting GNSS/INS Integrated Navigation System during GNSS Outage Based on CNN-GRU and Factor Graph" Applied Sciences 14, no. 18: 8131. https://doi.org/10.3390/app14188131