基于ADS-B数据的一次雷达系统误差配准方法

针对大误差一次雷达测量过程中雷达配准方法的精度提升问题,分析了一次雷达误差分布特性,以广播式自动相关监视系统的航迹数据为真值,提出了基于改进轨迹跟踪滤波的实时雷达配准方法。采用点云配准方法中随机抽样一致性的迭代最近点法,对基于期望增加模型的变结构交互式多模型算法中的偏置函数进行了改进,有效减少了随机误差在配准过程中的影响,并获得最优的偏置参数,以提升大误差一次雷达配准的精度。算例分析结果表明,该方法配准后可使所选一次雷达俯仰角平均绝对误差降低至0.04°,方位角平均绝对误差降低至0.07°,为雷达系统误差配准提供新方法支撑。

Research on Error Registration Method for Primary Radar System Based on ADS-B Data

In order to improve the accuracy of the radar registration method in the process of large error primary radar measurement, taking the track data of the broadcast automatic correlation monitoring system as the true value, the characteristics of the primary radar error distribution are analyzed, and a realtime radar registration method is proposed based on the improved track tracking filter. This method is intended to improve the bias function in the variable structure interactive multi-model algorithm (EMAIMM) based on the expected increase model by adopting the iterative nearest point method (RANSACICP) of random sampling consistency in point cloud registration method, effectively reducing the influence of random errors in the registration process, obtaining the optimal bias parameters, and improving the accuracy of large error primary radar registration. The results show that the average absolute error of pitch Angle and azimuth Angle can be reduced to 0.04° and 0.07° respectively, and this provides a new method for radar system error registration.