Speaker: Binghui Wang

Title: Error-weighted fitting estimation of ion drift velocity using incoherent scatter radar

Abstract: Time domain signal processing techniques are commonly employed to obtain bulk measurements of the ion drift velocity in F-region. The measurements are obtained by fitting estimates of the mean autocorrelation function (ACF) of the radar target. To accurately and consistently extract target parameters from the ACF, it is necessary to utilize an error-weighted fitting algorithm with a weight given by the variance of the ACF. 

In this presentation, I will start with the first principle of statistics — Gaussian random variable to derive the variance in ACF, then show how the variance propagates in phase angle measurements and thus adding uncertainty in estimating the ion drift velocity. Lastly, a recent velocity estimation result using the error-weighted fitting from my research will be presented. 

Bio: Mr. Wang studies the theory of Incoherent Scatter Radar, and employs ISR data to detect and estimate plasma properties of the ionosphere. His research focus is on the development of data processing techniques that can accommodate unprecedented resolution and high efficiency.  Through his academic career, Binghui has been a dedicated Teaching Assistant since 2016. In recognition of his outstanding teaching record, he has received the “Excellence in Undergraduate Teaching” award in 2019, and has been selected as one of the Mavis Future Faculty Fellows in 2020.  Recently, Mr. Wang has developed a new laboratory manual for the Analog Signal Processing course at UIUC (ECE 210) to further aid student’s remote learning during the COVID pandemic, which further demonstrates his dedication to teaching. In his spare time, Binghui enjoys traveling, learning new languages, and figure skating.