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调频步进逆合成孔径雷达(ISAR)在低信噪比(SNR)下采用距离-多普勒(R-D)成像算法时,必须有效进行包络对齐和相位聚焦,但是在目标运动未知的情况下,采用普通方法很难解决这个问题。利用调频步进雷达的粗距离像信号为慢时间域的线性调频(LFM)信号这一特点,通过对若干个连续子脉冲串的分数阶傅里叶变换(FRFT)谱图进行等距滑动叠加的方法,解决了单个子脉冲串的FRFT谱图在低信噪比下被噪声淹没的问题。通过搜索叠加后的FRFT谱图,可以估计出目标运动参数,然后利用目标运动参数估计值构造出补偿函数,从而实现了包络对齐和相位聚焦。由于FRFT有快速算法,计算速度与快速傅里叶变换(FFT)相仿,所以算法的参数估计步骤运算效率较高,易于工程实现。仿真结果显示该算法可以获得较为理想的成像结果,验证了算法的有效性。
Frequency-Stepping Inverse Synthetic Aperture Radar (ISAR) When using distance-Doppler (RD) imaging algorithms at low signal-to-noise ratios (SNRs), envelope alignment and phase focusing must be performed efficiently but when the target motion is unknown , Using common methods is difficult to solve this problem. Based on the characteristic that the coarse distance image signal of the FM stepping radar is a LFM signal in a slow time domain, the FRFT spectrum of several consecutive sub-bursts is equidistantly slidingly superposed The method solves the problem that the FRFT spectrum of a single sub-burst is submerged by noise at a low signal-to-noise ratio. By searching the superimposed FRFT spectrum, the target motion parameters can be estimated and then the compensation function can be constructed by using the estimated target motion parameters to achieve envelope alignment and phase focusing. Because of the fast algorithm of FRFT, the computational speed is similar to that of Fast Fourier Transform (FFT), so the parameter estimation of the algorithm has higher computational efficiency and is easy to implement. The simulation results show that the algorithm can obtain the ideal imaging results and verify the effectiveness of the algorithm.