A New Technique for INS/GNSS Attitude and Parameter Estimation Using Online Optimization
About
Integration of inertial navigation system (INS) and global navigation satellite system (GNSS) is usually implemented in engineering applications by way of Kalman-like filtering. This form of INS/GNSS integration is prone to attitude initialization failure, especially when the host vehicle is moving freely. This paper proposes an online constrained-optimization method to simultaneously estimate the attitude and other related parameters including GNSS antenna's lever arm and inertial sensor biases. This new technique benefits from self-initialization in which no prior attitude or sensor measurement noise information is required. Numerical results are reported to validate its effectiveness and prospect in high accurate INS/GNSS applications.
Yuanxin Wu, Jinling Wang, Dewen Hu• 2014
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Accelerometer Bias Estimation | Simulated Data 50 Monte Carlo runs | Final Estimate Error (µg)2 | 2 | |
| Attitude Estimation | Simulated Data 50 Monte Carlo runs | Final Estimate Error (0.001 deg)1 | 2 | |
| GPS Lever Arm Estimation | Simulated Data 50 Monte Carlo runs | Final Estimate Error (mm)0.1 | 2 |
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