Reconstruction Method for Narrow-band Radar Returns withMissing Samples Based on Complex Gaussian Model

This paper proposes a new signal reconstruction method for the signals with missing samples obtained by narrow-band radar. For the narrow-band radar system, the target echoes can be assumed to follow the complex Gaussian distribution. Based on this precondition, first the probabilistic model between the observed signal with missing samples and the unknown complete signal is formulated. Then the posterior distribution of the complete signal is obtained via the Bayes' theorem. Finally, the maximum likelihood estimation of the model parameters is obtained with the Expectation Maximization (EM) algorithm and the reconstruction of the complete signal can be obtained. The advantage of the method is that the reconstruction of the complete signal only using the observed signal with missing samples based on the complex Gaussian distribution assumption, while no other signal and prior information are needed in the parameter learning process. Experiments based on the measured data and the comparation results with other state-of-the-art approaches show that the proposed method can achieve good reconstruction performance.