Aircraft Optoelectronic Payload Transfer Alignment and Dynamic Error Compensation Algorithm Research

This paper proposes a multi-source dynamic error compensation algorithm for the transfer alignment of airborne optoelectronic payloads. This method addresses performance limitations of micro-inertial navigation systems (micro-INS) in complex dynamic environments, specifically those arising from accumulated device noise and the inability to perform static alignment due to installation errors. The algorithm’s core is the Extended Kalman Filter (EKF) technology. By constructing a “velocity + attitude” matching model between the UAV’s master inertial navigation system (MINS) and the optoelectronic payload’s slave inertial navigation system (SINS), it leverages high-precision MINS navigation information to correct SINS errors. Utilizing a 21-dimensional state space equation and measurement equation, the algorithm achieves real-time estimation and compensation of various errors, including attitude misalignment angles, sensor biases, installation errors, and flexure deformation. Simulation results demonstrate significant alignment accuracy improvement. Post-lever arm effect compensation, velocity errors are stably controlled within 0.01 m/s. Concurrently, flexure deformation angle compensation substantially reduces misalignment angle fluctuations across all directions, enhancing system stability and maintaining low misalignment angles. These findings validate the proposed error compensation strategy’s effectiveness.