Nonlinear correction of frequency-modulated continuous-wave lidar frequency modulation based on singular value decomposition-least square algorithm

Abstract. Frequency-modulated continuous-wave (FMCW) lidars combine the advantages of lasers and FMCW radars and have a wide range of applications in three-dimensional imaging and meteorological observation. However, its spatial resolution is directly limited by the nonlinearity of laser frequency sweep. A nonlinear correction method is proposed using a singular value decomposition (SVD)-least squares algorithm, which can calculate the nonlinear coefficient of each order accurately by minimizing the error between the actual phase and the fitted phase. In the simulation, the results demonstrate that the proposed method can achieve significantly better performance on nonlinearity and root-mean-square error (RMSE) than that of the conventional high-order ambiguity function (HAF) algorithm. Calculation results show that, for the SVD algorithm, the nonlinearity and RMSE are reduced by 50.37% and 52.55%, respectively, compared with those of the HAF algorithm under the signal-to-noise ratio of 25 dB, proving the performance improvement of the proposed algorithm.