Research on Meteor Radar Phase Calibration Using the JADE Algorithm with Collaborative Position Estimation
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摘要: 本文提出一种基于自适应差分进化协同位置估计的流星雷达多通道相位校准方法。该方法基于到达角估计“坏点”占比、流星高度分布等统计特性构建复合目标函数,采用可变步长的自适应差分进化搜索策略,并协同开展流星余迹到达角与高度信息的迭代估计,可高效获取精确的系统相位校准结果与流星余迹位置估计结果。利用流星雷达一天观测数据(包含18318颗流星余迹)开展的仿真结果表明,该方法平均可在150代以内实现稳定收敛,通道间相位偏差估计的方均根误差(RMSE)小于1°,可进一步提升流星雷达观测数据质量,并适用于雷达系统通道特性的长期持续监测。Abstract: A method for multi-channel phase internal calibration of meteor radar based on adaptive differential evolution and collaborative position estimation is presented. This approach constructs a composite objective function based on statistical properties, specifically the proportion of angle-of-arrival (AOA) estimation "outliers" and the characteristic altitude distribution of meteors. By employing the JADE search strategy with an adaptive mutation factor and optional external archive, the method synchronously conducts iterative estimation the AOA and altitude information of meteor trails. This framework efficiently facilitates the high-precision multi-channel phase offsets and meteor trail positions. Primarily simulation results, fulfilled with a 24-hour observational data set containing 18,318 meteor trails, demonstrate that the search algorithm typically achieves stable convergence within 150 generations. The root mean square error of the multi-channel phase offsets is less than 1°. The proposed method substantially enhances the data quality of meteor radar and is highly applicable for the routine on-line self phase calibration measurements.
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Key words:
- meteor /
- meteor radar /
- Phase calibration /
- Adaptive differential evolution
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