Radar Target Recognition Based on Semiparametric Density Estimation
基于半参数化概率密度估计的雷达目标识别

Due to the density model selection problem of amplitudes in each range cells for radar target recognition using High-Resolution Range Profile (HRRP), a radar target recognition approach based on the semiparametric density estimation is proposed in this paper. Starting with the parametric density estimation, semiparametric method has the ability to make use of empirical knowledge which is known as the approximate Gamma distribution of amplitudes in each HRRP range cells, and the Gamma density estimate is then corrected by multiplying with a nonparametric estimation of a correction factor. Obviously, both advantages of parametric method and nonparametric method are merged in the semiparametric density estimation. Simulation results based on the HRRP dataset of five aircraft models demonstrate the effectiveness of the proposed approach.