基于频率轴反转的机动目标距离徙动补偿方法

机动目标在长时间积累时间内发生严重的距离徙动与多普勒徙动，影响雷达对目标的检测性能.针对该问题，该文提出一种基于频率轴反转变换与广义自相关变换的机动目标检测与高阶运动参数估计快速算法.首先在距离频域利用频率轴反转变换校正距离徙动，信号变为立方相位信号；然后利用广义自相关变换与广义变尺度傅里叶变换实现信号降阶与参数非搜索估计；最后利用估计参数对原始信号解调频，并完成目标能量的积累.与现有的Keystone，广义Radon-Fourier变换，Radon-吕分布和Radon-分数阶傅里叶变换相比，本文方法可以快速校正距离徙动，实现非搜索的目标参数估计，达到低计算复杂度与检测性能的折中.仿真实验表明，该方法可有效完成机动目标的检测与参数估计.

Range Migration Compensation Method for Maneuvering Target Based on Frequency Axis Reversal

The integration and detection performance for the maneuvering targets may slide down due to the defocusing effects of the range migration and the Doppler frequency migration in the long integration time.To address these issues,we propose a fast non-searching method based on frequency axis reversal and generalized autocorrelation function.In this algorithm,the frequency axis reversal transform is applied to correct the range migration in the range frequency domain.Then the received signal becomes cubic phase signal and both generalized autocorrelation function and generalized scaled Fourier transform (GSCFT) are applied to finish the signal reduction and the estimation of the moving target.Finally,estimated parameters are employed to dechirp the echo and the target is well focused in the range-Doppler domain.Compared with the existing methods such as Keystone,GRFT (Generalized Radon Fourier Transform),RLVD (Radon-Lv's Distribution) and RFRFT (Radon Fractional Fourier Transform),the presented algorithm can fast eliminate the range migration and obtain the motion parameters without any searching procedure and can achieve a good balance between the computational cost and the detection ability.Several simulation experiments are provided to demonstrate the effectiveness of the proposed algorithm.