The atmospheric wind field is closely related to human activities, and airborne wind lidar is a critical tool for obtaining atmospheric wind field data. During flight, airborne platforms undergo continuous changes in three attitude angles: yaw, roll, and pitch. These variations alter the line-of-sight wind speed values during measurement integration time, leading to measurement errors. Compensating for airborne platform attitude deviations is therefore of significant practical importance for atmospheric wind field measurements. This study proposes a mechanical motion device-based attitude compensation method. To meet practicality and system simplification requirements, an FPGA (field programmable gate array)-controlled compensation algorithm is introduced, building on the existing dual-axis scanning device and FPGA system of the wind lidar. This system achieves real-time, high-precision compensation for airborne platform attitude angle changes.

To reduce directional errors of the emitted laser beam, we combine an FPGA control algorithm with a dual-axis compensation device to correct yaw, roll, and pitch deviations of the airborne platform. The attitude measurement unit employs an MEMS (micro-electro-mechanical system) inertial/satellite integrated navigation module (equipped with a triaxial gyroscope and accelerometer) to acquire platform attitude information with an accuracy of 0.03°. Azimuth and pitch motors are connected to angle encoders for position feedback. The FPGA receives IMU (inertial measurement unit) measurement data every 60 ms. The motors operate in a variable-speed stepping mode, completing each compensation motion within 60 ms, achieving a system compensation bandwidth of 16 Hz. After parsing IMU attitude data, dual-axis compensation angles are calculated to control motor movements. Physical equivalence experiments were conducted to test motor repeatability positioning accuracy and compensation angle errors, determining the actual compensation error of the dual-axis scanning mirror system. Additionally, radial wind speed errors caused by the interaction between attitude angle changes and wind speed during integration time in a single direction were analyzed. Finally, simulations were performed to evaluate radial wind speed errors induced by compensation system errors under specific flight conditions.

To validate the compensation effectiveness of the device on airborne platform attitude changes, equivalent experiments were conducted for azimuth and pitch compensation angles in laser pointing adaptive control. The rotation angle derived from encoder monitoring values was used as the basis for laser pointing compensation. Attitude change angles and laser pointing compensation angles were measured multiple times at varying angular velocities, with a turntable motion range of 0°?21°. Through semi-physical experimental simulations and combined with pointing repeatability positioning accuracy, when the platform attitude angular velocity was below 20 (°)/s, the azimuth and pitch compensation accuracies of laser pointing reached 0.048° and 0.043°, respectively, with compensation error ranges of -0.1° to 0.1°. The dual-axis compensation accuracy of the laser pointing system was 0.064°, with a compensation error range of -0.141° to 0.141°. We compare the final motion compensation results with other classic compensation methods, further compare the effectiveness of motion correction methods and post-processing correction methods, and analyze the propagation of attitude-related errors to horizontal wind speed errors.

An FPGA-controlled adaptive scanning mirror pointing scheme for airborne wind lidar is designed. The FPGA acquires platform attitude information via an IMU, dynamically adjusts motion parameters using attitude compensation and variable-speed stepping algorithms, and achieves adaptive control of the dual-axis compensation device to complete laser pointing compensation. The system exhibits a compensation speed range of 0?20 (°)/s, a bandwidth of 16 Hz, a compensation accuracy of 0.064°, and a compensation error range of -0.141° to 0.141°. Under conditions of a platform attitude angular velocity of 3 (°)/s, a relative wind speed of 10 m/s, and a 1-min measurement duration, the horizontal wind speed measurement accuracy improved from 5.223 m/s to 0.023 m/s, and the horizontal wind direction deviation decreased from 176.2° to 0.28° after implementing adaptive pointing control. This scheme provides an effective approach for stabilizing laser pointing in airborne wind lidar systems.