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为实现合成孔径雷达对运动目标有效地成像,需要对运动目标的线性调频(chirp)回波信号的参数进行准确地估计。该文将马尔可夫链蒙特卡洛(MarkovchainMonteCarlo,MCMC)方法和均值似然估计相结合,利用离散调频图(chirpogram)作为起始点的选择方法,提出了一种实现单分量chirp信号最大似然参数估计的新方法。仿真和分析表明这种方法的参数估计性能可以在较低信噪比时达到CramerRao界(CRB)。该方法结构简单,计算量适中,可以联合估计各参数,无误差传递效应,估计性能良好。
In order to achieve effective imaging of a moving target by a synthetic aperture radar, the parameters of a linear chirp echo signal of a moving target need to be accurately estimated. In this paper, the Markov chain Monte Carlo (MCMC) method is combined with the method of average likelihood estimation. By using the chirpogram as the starting point selection method, a method is proposed to realize the maximum likelihood of single component chirp signal New method of parameter estimation. Simulation and analysis show that the performance of this method can reach CramerRao boundary (CRB) at low SNR. The method has the advantages of simple structure, moderate amount of calculation, joint estimation of parameters, error-free transfer effect and good estimation performance.