基于FRT-MLVD的无源雷达机动目标徙动补偿算法

Migration compensation algorithm for maneuvering target in passive radar based on FRT-MLVD

无源雷达机动目标长时间相参积累过程中,目标的运动参数会引起距离徙动和多普勒徙动,导致回波信号能量分散和检测性能恶化。为实现含有第二加速度的变加速运动目标相参积累,提出了一种基于频域序列反转变换(FRT)和改进吕分布(MLVD)的相参积累算法。首先,利用 FRT 去除信号的距离徙动,将回波能量积累至同一距离单元;然后,利用 MLVD 对该距离单元内的回波进行处理,估计出目标加速度和第二加速度;在补偿目标的加速度和第二加速度引起的多普勒徙动后,利用 Keystone 变换(KT)校正目标速度引起的线性徙动,实现距离和速度的估计。仿真结果表明,所提算法可有效补偿无源雷达中机动目标的距离徙动和多普勒徙动,对变加速目标的积累效果和检测概率显著优于现有算法。

During the long coherent integration time in passive radar, the motion parameters (such as high speed, ac- celeration and jerk motion, etc.) will bring about range migration (RM) and Doppler frequency migration (DFM), fur- ther deteriorate the integration performance. To realize the coherent integration of maneuvering targets with jerk mo- tion, a method based on frequency reversing transform (FRT) and modified Lv’s distribution (MLVD) called FRT-MLVD was proposed to achieve the coherent integration and motion parameters estimation. More specifically, the FRT was firstly proposed to remove RM. Then the MLVD was employed to estimate the acceleration and jerk param- eters. After compensating the DFM induced by the acceleration and jerk motion, the residual RM was corrected and the velocity and range was achieved via the KT operation. Simulation results demonstrate that the proposed method can effectively compensate the RM and DFM induced by the target motion parameters in passive radar, and for ma- neuvering targets with jerk motion, the proposed method achieves a better integration and detection performance over existing methods.