双基地前向散射雷达机动目标跟踪

M aneuvering T argets T rack ing in the B istatic Forw ard Scattering R adar

为进行基于EKF(Extended Kalman Filter,EKF)的双基地前向散射雷达机动目标跟踪,基于双基地前向散射雷达(Bisktic forward scattering radars,BFSR)在其前向散射区探测隐身目标的能力明显优于单基地雷达的特点,建立常加速度和变加速度2种运动模型,使用扩展卡尔曼滤波进行目标跟踪保持,精确估计了运动目标参数(运动轨迹、速度、加速度),为该体制雷达成像、识别奠定了基础。并使用了高斯-牛顿迭代算法估计初值,提高了滤波的效率和准确性。通过对匀加速、变加速运动目标仿真,验证了提出模型和算法的有效性。

Based on the characteristic that the B istatic forward scattering radars are superior to the monostatic radars in effectively detecting and tracking the small radar cross section（RCS） targets,non-variable acceleration and variable acceleration motion models are constructed.The Extended Kalman Filter algorithm is applied to keeping targets in track,the parameters（trace of the target,velocity and acceleration of the targets） of the moving targets are accurately estimated which establish the foundation for radar imaging and identification.By applying Gauss-Newton iterative algorithm,the efficiency and accuracy of the filtering results are improved.The models proposed and the effectiveness of the algorithms are verified by simulating the non-variable and variable acceleration motion targets.