GPS and INS Integrated Navigation with Algorithm Implementation

GPS and INS integrated navigation is a widely adopted hybrid navigation approach that combines the high-precision positioning capability of the Global Positioning System (GPS) with the autonomy and high-frequency characteristics of the Inertial Navigation System (INS). In the tightly coupled integration scheme, GPS raw measurement data (such as pseudorange and Doppler shift) is directly fused with INS outputs, rather than relying solely on GPS position solutions.

This MATLAB implementation features a tightly coupled navigation algorithm comprising several core components:

Inertial Navigation Solution: The algorithm processes accelerometer and gyroscope data through numerical integration to compute position, velocity, and attitude. Due to inherent error accumulation in inertial navigation, external correction mechanisms are required for compensation.

GPS Data Processing: The system receives satellite signals and extracts pseudorange, carrier phase, and other navigation parameters, implementing error corrections for ionospheric delays, clock biases, and other measurement errors.

Kalman Filter Fusion: The implementation employs either Extended Kalman Filter (EKF) or Unscented Kalman Filter (UKF) to estimate navigation errors, including position, velocity, and attitude deviations. In tightly coupled mode, GPS pseudorange and pseudorange rate measurements serve as direct observations, which are compared with INS-predicted values to optimize system state estimation.

Feedback Correction: The filter-estimated errors are fed back to compensate the INS, forming a closed-loop correction system that enhances long-term navigation accuracy.

Simulation results demonstrate that this program effectively models GPS/INS integrated performance, particularly maintaining navigation continuity during temporary GPS signal outages while GPS information suppresses INS divergence. This method is suitable for applications requiring high navigation reliability, such as unmanned aerial vehicles and autonomous driving systems.