An Improved Meteor Echo Recognition Algorithm for SuperDARN HF Radar

Abstract

The SuperDARN HF radars can be used for meteor observation and inversion of mid-upper atmosphere neutral wind using observed meteor echo Doppler velocities. Aiming at the problem that the extraction of meteor echo based on echo power, Doppler velocity and spectral width is rough and contains ionospheric echo, this paper optimizes the extraction algorithm of meteor echo. Based on the AgileDARN HF radar’s digital characteristics, the observation method of meteor echo was improved, and we designed a meteor observation mode without changing the hardware system: using a meteor observation with a 7.5 km range resolution and a 2 s integration time, we extracted the Doppler characteristics of different echo types at meteor echo ranges; according to these features, the extraction algorithm of meteor echo was optimized. By analyzing the measured data, the characteristics of diurnal variation, power distribution, Doppler velocity distribution and spectral width distribution of meteor echo extracted by the optimization algorithm were obtained. The meteor echo characteristics obtained by the improved algorithm are more consistent with the theoretical analysis; thus, the improved algorithm is better than the SuperDARN high frequency radar meteor echo extraction algorithm and has good performance. The meteor echo extraction algorithm presented in this paper can extract the meteor echo more accurately, so that the atmospheric neutral wind can be retrieved more accurately. At the same time, the proposed algorithm is not only applicable to AgileDARN HF radar meteor observation mode data, but also to AgileDARN and SuperDARN normal mode data, which is beneficial to expand the data application of SuperDARN radars.