Identification and removal of aircraft clutter to improve wind velocity measurement made with Chung-Li VHF Radar

Abstract

Abstract In this study, a data processing based on the empirical mode decomposition (EMD) of Hilbert-Huang Transform (HHT) is developed at Chung-Li VHF radar to identify and remove the aircraft clutter for improving the atmospheric wind measurement. The EMD decomposes the echo signals into the so-called intrinsic mode functions (IMFs) in the time domain, and then the aircraft clutter that is represented by a number of specific IMFs can be identified in the radar returns and separated from the clear air echoes that are observed concurrently by the VHF radar. The identified clutter is validated by using the aircraft information collected by the Automatic Dependent Surveillance-Broadcast (ADS-B) receiver. It shows that the proposed algorithm can detect the aircraft echoes that are mixed with the clear air echoes. After implementing the algorithm on the experimental data, the atmospheric horizontal wind velocities are estimated after the aircraft clutter is removed. In order to evaluate the degree of the improvement of the horizontal wind measurement, a comparison in the horizontal wind velocities between Chung-Li VHF radar and a co-located UHF wind profiler radar is made. The results show that the use of EMD and the proposed data processing can effectively reduce the uncertainty and substantially improve the precision and reliability of the horizontal wind measurement.