# GNSS/INS Integration Based on Machine Learning LightGBM Model for Vehicle Navigation
## 3 Experimental Analysis and Method  
### Data Acquisition  
A vehicle navigation data acquisition system was designed to acquire vehicle dynamics and position data before and after the GNSS outage (Figure 2A). The system consisted of a self-developed GNSS/INS integrated navigation system (Kalman-filter-based, loosely coupled integration is used), a Novatel pwrpaK7-e1 GNSS/INS integrated navigation system, and a computer. The self-developed GNSS/INS integrated navigation system  
Figure 1: PUA-based LightGBM machine learning model. (**A**) Position update architecture (PUA), \(t\)—time; \(V_{\text{INS}}(t)\)—Velocity provided by INS at \(t\); \(\theta_{\text{INS}}(t)\)—Heading angle provided by INS at \(t\); \(\delta N_{\text{PUA}}(t)\)—Latitude difference between epoch \(t\) and epoch \(t-1\); \(\delta E_{\text{PUA}}(t)\)—Longitude difference between epoch \(t\) and epoch \(t-1\); (**B**) Scheme of the LightGBM machine learning model based on the PUA. included a No. 2 satellite antenna, MEMS inertial measurement unit, data acquisition board, data fusion board, and power supply unit. The data acquisition board was equipped with an integrated UB4B0M GNSS board (accuracy: better than 1.5 m for single-point positioning). The IMU200A inertial measurement unit (IMU) consisted of a gyroscope (range, \(\pm\)300\({}^{\circ}\)/s; zero bias, 25.2\({}^{\circ}\)/hr; angular random walk, 144\({}^{\circ}\)/\(\surd\)hr) and an accelerometer (range, \(\pm\)17 g; zero bias, 0.2 mg; velocity random walk, 12 m/s/\(\surd\)hr), which were fixed to a platform in the vehicle. Foam was used as a buffer material between the IMU and the platform to minimize external interference during IMU operation. Its working process was as follows: While the vehicle was moving, the No. 2 antenna installed on the vehicle's roof searched for and tracked satellite signals. When the number of satellites searched reached four or more, the GNSS board embedded in the data acquisition board demodulated the received signals. Then, it calculated the GNSS data, which included the vehicle's position coordinates. Simultaneously, the vehicle's three-axis angular motion data and three-axis acceleration data output from the IMU were transmitted in real time to the data acquisition board, which intercepted and converted the GNSS data and INS raw data (IMU output) to the preset data format to complete the data acquisition process. Then, the pre-processed data were transferred to the data fusion board, where they were solved and fused to obtain the final GNSS and INS data. Subsequently, these data were transferred to the computer via the serial port of the data fusion board. The Novatel pwrpaK7-e1 GNSS/INS integrated navigation system consisted of No. 2 and No. 3 satellite antennas, a Novatel pwrpaK7-e1 navigation unit with an integrated satellite receiver, and an Epson G320 MEMS-IMU (gyroscope: range, \(\pm\)150\({}^{\circ}\)/s; zero bias, 3.5\({}^{\circ}\)/hr; angle random walk, 0.1\({}^{\circ}\)/\(\surd\)hr. Accelerometer: range, \(\pm\)5 g; zero bias, 0.1 mg; velocity random walk, 0.5 m/s/\(\surd\)hr). It was possible to capture a vehicle's trajectory, i.e., its location, with greater accuracy. The procedure was as follows: The No. 1 and No. 3 satellite antennas searched for and track the satellite signals. When the satellite positioning conditions were met, the Novatel pwrpaK7-e1 performed the initial alignment to establish the initial INS benchmark, then completed the process of collecting, calculating, and fusing the GNSS and INS data and finally transmitted the data to the computer via the communication interface. For the experiments, an open closed-loop urban road trajectory (perimeter x road width: 8168.0 \(\times\) 20.6 m) was first selected (Figure 2B) to ensure that GNSS outages would not occur automatically.