基于运动约束的脉冲雷达游标测距方法

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.

Vernier ranging method for pulse radar based on motion constraints

Traditional pulse radar Vernier ranging method has the problem of coupled ambiguity in resolving the ambiguity of Doppler phase and velocity. To solve this problem, the motion constraint of target was applied into Vernier ranging and a new motion constraint Vernier ranging method was proposed. Accumulating a period of measurement data, an unscented Kalman filter was used to estimate radial velocities with higher accuracy. The high accuracy velocities were used to resolve the velocity ambiguity to startup the Vernier ranging. The radial velocity of next time period was accurately estimated through UKF forecast on the Vernier range, and the velocity ambiguity of next period was resolved. The coupling filter that could resolve phase ambiguity and velocity ambiguity was built, and the random errors of pulse radar radial range data were greatly eliminated using this new Vernier ranging method. Simulations of high-speed aircraft in boost phase and measured data of pulse radar prove that, this motion constraint Vernier ranging method greatly reduces the random error of radial range from meters to decimeters.