Due to the mismatch between the tracking model and the real motion state of the target， the estimation accuracy of the high order motion feature of the target is poor in single-station radar.In this paper， the estimation accuracy of high order motion feature of the target is improved from the perspective of radar networking and radial velocity augmentation measurement. The sequential unscented Kalman filter algorithm is used to centrally fuse the asynchronous measurement information of multiple radars. The estimation effect of the high order motion feature of the target under different ranging， angular accuracy and radial velocity augmentation measurement is analyzed， and the influence of the radar station layout on the estimation effect of the high order motion feature of the target is analyzed by using the geometric accuracy factor of double sensors to optimize the radar station layout. Through simulation experiment， it is found that the radar ranging accuracy in this radar networking mode has a greater impact on the estimation effect of high order motion feature than the angle measurement accuracy. Radar station layout optimization combined with radial velocity augmentation measurement can effectively obtain high precision estimation of high order motion feature of target.