High precision on-orbit geometric calibration technology is the key to obtaining high precision satellite laser altimeters. Different from the traditional full-waveform laser altimeter, the single-photon laser altimeter has the characteristics of high repetition frequency and small footprint. These characteristics put forward new requirements for on-orbit geometric calibration. Aiming at the characteristics of the single-photon laser altimeter, this paper proposes a pointing angle and range calibration algorithm based on a Corner Cube Retro-Reflectors (CCRs). The algorithm determines the position of the CCR closest to the center of the footprint based on the photon signal returned by the CCR deployed on the ground, and unifies the natural ground and the laser footprint and establishes an on-orbit geometric calibration model. Through 8 sets of control experiments, the system errors of 30 second,60 second and 90 second are added to the pointing angle, and the system errors of -3m,-4m,-6m and -9m are added to the range. After using this algorithm for calibration, The average elevation deviation is decreased from more than 86m to less than 1m. The results show that the CCR-based pointing angle and range calibration algorithm can better restore the added system error, and can effectively improve the data accuracy of the laser altimeter.
The satellite laser altimeter requires high-precision on-orbit geometric calibration to ensure the accuracy of the laser altimeter data. However, the calibration method based on undulating terrain may have multiple solutions under complex terrain, which means that the calibration parameters may converge to the local optimal solution. In order to solve the problem, a satellite laser altimeter pointing and ranging calibration algorithm based on simulated annealing is proposed, which can reduce the possibility of the calibration parameters to converge to the local optimal solution. In 10 sets of comparative experiments, there are 2 sets of result converging to the local optimal solution using algorithm based on Monte-Carlo simulation, while all sets of result converge to the global optimal solution using algorithm based on simulated annealing. After calibration with the proposed algorithm, the average of elevation error decreased from about 9.1m to within 3m, and standard error decreased from about 1m to about 0.5m. The results show that the calibration algorithm based on simulated annealing can effectively prevent the calibration parameters from converging to the local optimal solution, and can effectively improve the accuracy of laser altimeter data.
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