【摘要】 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。更多还原

【Abstract】 The imaging of moving targets by synthetic aperture radar (SAR) needs to accurately estimate the parameters of chirp return signals of moving targets. This paper presents a new method to obtain the maximum likelihood estimate of mono-component chirp parameters. The method merges the Markov chain Monte Carlo (MCMC) technique and mean likelihood estimation (MELE) with discrete chirpogram as the initial value selection method. Simulations and analyses showed that the parameter estimation performance of this method can attain the Cramer Rao bound (CRB) at low signal-to-noise ratio (SNR). The method is simple and can be implemented with modest amount of computations. The method jointly estimates the parameters with no error propagation effect.更多还原