An Improved HAF-Based Nonlinear Correction Method of FMCW Radar With CEEMD

The frequency modulation continuous-wave (FMCW) radar has been widely concerned for its compact system structure, low hardware cost, and excellent imaging resolution. However, an FMCW radar suffers from the nonlinearity commonly, which leads to the deterioration of the imaging quality. A challenging problem is that the nonlinear reference beat signal contains multiple components with closely spaced and approximately equal amplitude, which has not been researched in the existing literature to the best of our knowledge. To deal with this trouble, a software-based correction method is proposed by utilizing the complementary ensemble empirical mode decomposition (CEEMD). First, several intrinsic model functions (IMFs) are generated by decomposing the beat signal obtained from a reference target by the CEEMD method. Then, an identification method is proposed to find the reference IMF from the IMFs by the average period method, and a reference delay estimation method based on windowed fast Fourier transform is proposed. Finally, the high-order ambiguity function (HAF) is employed to estimate the polynomial coefficients of the reference IMF, which are utilized to compensate the nonlinear beat signal by a time resampling method. The effectiveness and superiority are verified by numerical simulation and real data. Compared with the state-of-the-art nonlinear correction algorithms, we obtain more outstanding radar imaging quality by adopting the proposed method.