The GaoFen-5B (GF-5B) satellite launched on September 7, 2021 can achieve comprehensive atmosphere and land observation. The visual and infrared multispectral sensor (VIMS) of the GF-5B satellite can obtain imagery data in 12 spectral bands from visible light to long wavelength infrared. With the advantages of a high signal-to-noise ratio and the ability of day and night observation, the imagery of visual and infrared multispectral sensors is widely applied to land degradation monitoring, crop growth analysis, and thermal pollution detection. GF-5B is equipped with three star sensors as the attitude measurement system to achieve high-precision attitude determination and geometric positioning. Among these star sensors, star sensors 2 and 3 have better measurement accuracy and stability performance and are often employed as conventional attitude determination modes to calculate satellite attitude parameters. However, owing to factors such as sunlight exposure and insufficient star number, there are only star sensors 1 and 2 or star sensors 1 and 3 working simultaneously to determine the satellite attitude parameters, which are named unconventional attitude determination modes. Due to the spatial thermal environment changes of satellites, the body structure and installation structure of the attitude measurement load undergo thermoelastic deformation, which causes attitude low frequency error related to the satellite orbit period. This seriously affects the consistency of attitude determination results between conventional and unconventional attitude determination modes and the stability of the geometric positioning accuracy of the image without ground control points. Therefore, we propose an improvement method of geometric positioning accuracy for visual and infrared multispectral imagery based on spatiotemporal compensation of attitude low frequency error.

Based on the optical axis angle of star sensors, the spatiotemporal characteristics of low frequency error of star sensors are analyzed in 181 d for the GF-5B satellite. The median filtering denoising processing with the sliding window is applied to separate the low frequency error and the random error between conventional and unconventional attitude determination modes. Then, due to the complex local spatial locations, the attitude low frequency error between conventional and unconventional attitude determination modes is segmented based on satellite latitude position information. According to the spatial characteristics of attitude low frequency error, the low frequency error between conventional and unconventional attitude determination modes is calibrated in each position interval using the Fourier series model with the input parameter of satellite position latitude. For solving the drift problem of attitude low frequency error over time, we propose the sequential temporal models of low frequency error to ensure high-precision low frequency error compensation. In the attitude low frequency error compensation, the compensation model of attitude low frequency error of the unconventional attitude determination mode is selected among the sequential temporal models with the input parameter of sampling time. Then, the compensation parameter of attitude low frequency error is calculated using the Fourier series model with the input parameter of latitude position.

Employing the experimental data of visual and infrared multispectral sensors, we analyze the calibration accuracy of attitude low frequency error, compensation accuracy of attitude low frequency error, and geometric positioning accuracy of visual and infrared images. For the calibration accuracy of attitude low frequency error, the model errors along yaw angle, roll angle, and pitch angle calibrated by the proposed method are 0.178″, 0.095″, and 0.131″ respectively (Table 3). Meanwhile, the model errors along yaw angle, roll angle, and pitch angle calibrated by the global Fourier series model are 4.155″, 2.200″, and 6.173″ respectively (Table 4). The proposed attitude low frequency error model can achieve high-precision modeling with sub angular second level and is better than the global Fourier series model. Furthermore, the geometric positioning accuracy of images of visual and infrared sensors is optimized from 4.274 pixel to 1.867 pixel (Tables 6 and 7). Before attitude low frequency error compensation, the cross-track errors fluctuate between 1 pixel and 4 pixel, and the along-track errors fluctuate between 2 pixel and 10 pixel, which makes the geometric positioning accuracy change between 40 m and 200 m (Fig. 7). After attitude low frequency error compensation, the geometric positioning accuracy of each image is significantly improved, with the cross-track error and along-track error less than 2 pixel (Figs. 7 and 8). Additionally, the proposed method can achieve high-precision geometric positioning accuracy for the images at different time and areas.

To improve the geometric positioning accuracy of the visual and infrared multispectral sensor of the GF-5B satellite, we put forward an attitude low frequency error compensation method based on the spatiotemporal characteristics. The spatiotemporal characteristics of attitude low frequency error within 181 d are comprehensively analyzed, and then a compensation strategy with time sequence and multi-spatial models is proposed. Additionally, we execute slowequential calibration with certain time intervals to eliminate the drift problem of low frequency error over time and build a compensation model with the input parameter of latitude position to compensate for the spatial differences of low frequency error. The low frequency error characteristics between conventional and unconventional attitude determination modes are unified by the proposed method. This method improves the geometric positioning accuracy of visual and infrared multispectral sensors of the GF-5B satellite with different imaging time and imaging areas.