In practical application, the time when the maneuvering targets enter and leave the radar coverage observation is usually unknown, which will seriously deteriorate the performance of coherent integration and target detection. To solve this problem, we propose a method based on the symmetric autocorrelation function and the proposed window Lv's transform (SAF-WLVT) for coherent integration and motion parameters estimation of maneuvering target, involving the range migration (RM) and Doppler frequency migration (DFM). Firstly, the SAF is utilized to correct the linear RM induced by target's radial velocity and range curvature caused by target's radial acceleration simultaneously. Then, the proposed WLVT is applied to eliminate the residual DFM caused by the target's radial acceleration, accumulate the target energy without introducing excess noise energy, and obtain the baseband velocity and acceleration estimations. Finally, the Doppler ambiguity number is estimated by matched filtering and 1-D parameter searching, and then the target's radial velocity is obtained. The proposed method has low computational complexity, and possesses favorable performance of target detection and parameter estimation in the high signal to noise (SNR) environment. The mathematical analysis and simulation results demonstrate the effectiveness of the proposed method.

在实际应用中，机动目标进入和离开雷达覆盖范围的时间通常是未知的，这将严重降低相干积分和目标检测的性能。为解决这一问题，我们提出了一种基于对称自相关函数和拟议窗口Lv变换（SAF-WLVT）的机动目标的相干积分和运动参数估计方法，涉及距离偏移（RM）和多普勒频率偏移（DFM） ）。首先，利用SAF校正目标径向速度引起的线性RM和目标径向加速度引起的距离曲率。然后，将拟议的WLVT应用于消除目标径向加速度引起的残余DFM，在不引入过多噪声能量的情况下累积目标能量，并获得基带速度和加速度估计。最后，通过匹配滤波和一维参数搜索来估计多普勒模糊度数，然后获得目标的径向速度。该方法计算复杂度低，在高信噪比环境下具有良好的目标检测和参数估计性能。数学分析和仿真结果证明了该方法的有效性。该方法计算复杂度低，在高信噪比环境下具有良好的目标检测和参数估计性能。数学分析和仿真结果证明了该方法的有效性。该方法计算复杂度低，在高信噪比环境下具有良好的目标检测和参数估计性能。数学分析和仿真结果证明了该方法的有效性。