基于HT-MDCFT的高速机动目标运动参数估计

针对低信噪比条件下高速机动目标运动参数估计问题，将Hough变换(HT)和修正离散线性调频傅里叶变换(MDCFT)相结合，提出一种新的雷达信号处理算法(HMDCFT)。该算法首先采用Hough变换，从距离像图像中提取目标运动轨迹特征，校正距离走动并解速度模糊；然后利用MDCFT校正多普勒频率徙动，估计目标运动参数；最后沿估计的目标运动轨迹对回波能量进行相参积累。数值实验表明，该方法具有优越的抗噪声能力和运动参数估计性能。相比于利用距离像间相关性的包络互相关法，其抗噪声能力提升了约17.6 dB；即使雷达回波输入信噪比低至-35 dB，该方法仍可精确估计目标运动参数，充分聚焦目标回波能量。

High-speed maneuvering target motion parameter estimation based on HT-MDCFT

To deal with the problem of motion parameter estimation for a high-speed maneuvering target under low Signal-to-Noise Ratio(SNR) environment, based on Hough Transform(HT) and Modified Discrete Chirp-Fourier Transform(MDCFT), a novel algorithm, i.e., HMDCFT, is proposed in this paper. It first employs the trajectory feature extracted from the image of range profiles by HT to correct the first-order Range Migration(RM) and resolve the Doppler ambiguity. Then, it adopts MDCFT to compensate the Doppler Frequency Migration(DFM) and estimate the target''s motion parameters. After that, it coherently integrates the energy of radar returns along the estimated target moving trajectory. The numerical experiments show that the proposed method has superior anti-noise ability and motion parameter estimation performance. Compared with the envelope cross-correlation function method based on the correlation between range profiles, its anti-noise ability is improved by about 17.6 dB. Even the input SNR of radar echoes is as low as -35 dB, this method can accurately estimate the target''s motion parameters and fully focus the energy of the target''s echoes.