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为解决传统脉冲雷达游标测距中解相位模糊和解速度模糊相互耦合的问题,将目标的运动约束与传统游标测距结合在一起,提出了一种新的基于运动约束的游标测距方法.利用运动约束积累一段时间的观测数据进行UKF滤波,得到精度较高的径向速度来解速度模糊,得到的无模糊速度可用于距离游标.利用得到的游标距离取代脉冲测距数据进行UKF预测,可准确估计下一时刻的速度并解速度模糊,这样建立了可同时解相位模糊和解速度模糊的耦合滤波器,成功实现脉冲雷达游标测距,并大大减小脉冲雷达测距随机误差.高速飞行器主动段仿真和脉冲雷达实测数据验证表明,该算法能大大减小径向距离随机误差,将距离随机误差减少一个数量级至分米级.
In order to solve the problem of the fuzzy coupling between the resolving phases of the resolving phase and the resolving speed in the traditional pulse radar ranging, the target motion constraint is combined with the traditional cursor distance measurement, and a new method of cursor distance measurement based on motion constraint is proposed. The kinematic constraints accumulate the observed data for a period of time and carry out the UKF filtering to obtain the high accuracy radial velocity to solve the velocity blurring and the obtained unambiguous velocity can be used for the distance cursors.The UKF prediction can be performed by using the obtained cursor distance instead of the pulse range finding data Accurately estimate the speed of the next moment and solve the speed ambiguity, so that a coupling filter that can solve the ambiguity of the phase ambiguity and the speed of ambiguity solution is established, the pulse radar ranging and the random error of the pulse radar ranging are reduced greatly. The experimental results of segment simulation and pulse radar show that this algorithm can greatly reduce the random error of radial distance and reduce the random error of distance by an order of magnitude to decimeter.