LQE (Linear Quadratic Estimator) is an optimal state estimation algorithm used in inertial navigation systems (INS) to reduce errors and improve accuracy. It is similar to the Kalman filter but focuses on minimizing estimation error variance while balancing system stability and performance.
How LQE Works in INS?
Sensor Data Input – IMU (gyroscope & accelerometer) data is fed into the estimator.
Error Minimization – LQE calculates the best estimate of position, velocity, and orientation by minimizing estimation errors.
Adaptive Correction – The system continuously updates based on feedback from GNSS, LiDAR, or external sensors.
Applications of LQE in Inertial Navigation
✔ High-Precision Navigation – Used in aircraft, missiles, and autonomous vehicles for accurate positioning.
✔ Sensor Fusion – Improves INS performance by integrating GNSS, radar, and LiDAR data.
✔ GNSS-Denied Environments – Helps maintain accuracy when GPS signals are unavailable.
Advantages of LQE in INS
✔ Minimizes Navigation Errors – Enhances position estimation by reducing sensor drift.
✔ Fast & Efficient Computation – Works in real-time, making it ideal for high-speed navigation.
✔ Stable & Adaptive Filtering – Adjusts to changing conditions for robust navigation performance.
