Abstract: Abstract: Precise target characteristics detection could provide important parameters for smart variable-rate sprayers. In order to diminish the influence of complex terrain conditions, 3 kinds of dynamic attitude angle deviation correction methods were proposed to mitigate the errors of Lidar-based spray target detection caused by roll angle, pitch angle and yaw angle respectively. An experimental vehicle integrated with a laser scanning sensor detection unit and an inertial measurement unit (IMU) was used to detect spray targets under complex road conditions. The laser sensor detection unit was capable of detecting spray targets with the laser scanner. The inertial measurement unit was able to detect the real-time attitude angle deviations of the vehicle. The dynamic roll correction adopted real-time measured roll angles to correct detection targets and 3-D (three-dimensional) reconstruction images using re-matching trigonometric function and laser scanning polar coordinate value. For the dynamic pitch correction, re-combination of laser scanning target frames and detection points under the guidance of pitch angle values averaged segmentally was used to diminish dynamic pitch angle deviations. The coefficient value of laser scanning depth data combined with yaw angle average values was applied for the dynamic yaw correction. According to the measured vehicle dynamic attitude angle deviations, these 3 kinds of dynamic attitude angle deviation correction methods were put forward to obtain accurate characteristics of the targets and 3-D reconstruction images. The verification experiments for the proposed correction methods to overcome complex field road conditions were divided into 3 test steps. Firstly, an artificial tree and a cuboid chosen as targets were detected with specified detection distances and laser travel speeds to verify pitch correction algorithm when single dynamic pitch angle changed under downhill or uphill terrain. Secondly, the artificial tree was selected as the laser scanning target to test the correction algorithms when dynamic pitch angles combined with roll angles existed under long wooden unilateral bridge terrain. Finally, the artificial tree and the cuboid cabinet were selected as the laser scanning target to verify the correction methods under uneven complex terrain. The data correction process and 3-D image reconstruction were conducted using MATLAB software. The experiment results of 3 steps showed that the maximum relative errors of the height and width of cuboid cabinet were 8.89% and 8.00% respectively after the correction. The relative errors of the height, width and canopy height of the artificial tree were 5.63%, 10.00% and 5.00%, respectively. The 3-D reconstruction images also had significant improvements after the correction. The test results verify the effectiveness of the proposed data correction methods for laser attitude angle deviations correction under complex road conditions.