低信噪比条件下天基预警雷达目标运动参数估计方法

天基预警雷达目标回波包络峰值的距离徙动会导致FFT相参积累增益降低，为了对回波信号进行运动补偿，需要对目标运动参数进行估计。由于天基雷达对目标的观察距离较远，因此回波信噪比较低，直接影响了运动参数的估计精度。针对这一问题，本文提出了一种低信噪比条件下天基预警雷达目标运动参数估计方法。首先建立了目标回波模型，并对雷达观测距离范围内的回波信噪比进行了计算分析；然后利用Keystone变换对回波包络距离徙动进行校正，并对校正后的回波信号作离散短时傅里叶变换，得到回波信号方位向上的时频分布；最后利用Hough变换将时频域变换到参数域，得到运动参数的估计值。仿真结果表明，本文方法在低信噪比条件下能有效地估计目标运动参数，并且估计精度对信噪比的变化不敏感，具有良好的鲁棒性。 

Estimation of target motion parameters for space-based early warning radar in low SNR

After the clutter suppression, the space target echo of the space-based early warning radar still has inter-pulse envelope migration and Doppler diffusion, which causes the echo energy to defocus in the distance unit and Doppler domain after coherent accumulation. In order to increase the gain of coherent accumulation, the relative motion parameters between the satellite platform and the air target must be estimated to compensate the echo signal. Due to the limited power aperture product of the spaceborne radar and the long distance between the radar and the target, the signal-to-noise ratio of the echo signal is generally low, which affects the estimation accuracy of the motion parameters. Aiming at this problem, this paper proposes a method for estimating the motion parameters under low SNR. Firstly, the echo model of the air target is established, and the echo signal-to-noise ratio range in the radar line-of-sight range is calculated. Then, the Keystone transform is used to correct the distance migration of the echo envelope to obtain the azimuth time domain signal; finally, the time frequency distribution of the azimuth time-domain signal is obtained by Gabor transform, and then the time-frequency domain is transformed from the time-frequency domain to the parameter domain by standard Hough transform, and finally the estimated value of the motion parameter is obtained. The simulation results show that the proposed method can effectively estimate the target motion parameters under low SNR, and the estimation accuracy is not sensitive to the change of SNR, and it has good robustness.