Aerospace Systems (2019) 2:15–20 https://doi.org/10.1007/s42401-018-0012-1 REVIEW Atmospheric turbulence detection by PCA approach Qiang Zhang 1 · Gang Xiao 1 · Yi-qun Lan 2 · Rui-Rui Li 2 Received: 22 September 2018 / Revised: 9 November 2018 / Accepted: 13 November 2018 / Published online: 21 November 2018 © Shanghai Jiao Tong University 2018 Abstract By detecting the severe meteorological situations on flight route, airborne weather radar (WXR) can ensure the safety of the aircraft and on-board personnel. Among these critical weather conditions, atmospheric turbulence is one of the main factors that affect flight safety. Atmospheric turbulence detection method that the current WXR adopts mainly is the pulse pair processing (PPP) method, which estimates Doppler spectrum width of weather target echo and compares it with a threshold to determine whether this weather target is turbulence or not. PPP method is simple and easy to implement, but the performance of this method under the condition of low signal-to-noise ratio (SNR) is poor. In this paper, we propose a new turbulence detection method based on the principal component analysis (PCA) approach. This new method uses PCA approach to preprocess the weather target echo and divides it into two parts: the principal component part as signal and the rest part as noise, so as to realize the de-noising function of PCA approach, and it is then combined with PPP method to estimate the spectrum width. Due to the good de-noising performance of PCA approach, this new method improves the detection performance of traditional PPP method especially under the condition of low SNR. Keywords Airborne weather radar · Atmospheric turbulence detection · Pulse pair processing · Principal component analysis · De-noising 1 Introduction Airborne weather radar (WXR), as a subsystem of the air- craft environment surveillance system (AESS), can help to ensure the safety of aircraft and on-board personnel under severe weather conditions by detecting the weather condi- tions within a certain fan-shaped area in front of the aircraft. Among these severe weather conditions, atmospheric turbu- lence is one of the important factors affecting aircraft flight safety. Because of its random fluctuations within a certain period of time and space, severe turbulence will not only make the aircraft jolt but also affect the safety of the on- board personnel. B Qiang Zhang 18392066956@163.com Gang Xiao xiaogang@sjtu.edu.cn Yi-qun Lan jinyexin@126.com 1 School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China 2 Department of Aviation Maintenance, Shanghai Civil Aviation College, Shanghai, China The detection of meteorological targets by WXR is accomplished through a series of processing of radar echoes reflected from meteorological targets. The three spectrum moments of meteorological target echoes are closely related to the types of meteorological targets [1–3]: the magnitude of echo power or the zero moment of the Doppler spectrum can be used to determine the intensity of rainfall on the flight path; by calculating the rate of change of the average wind speed with distance, we can determine the degree of dan- ger of wind shear; by comparing the spectrum width of the echo and the spectrum width threshold of turbulence, we can determine whether the front of the aircraft has turbulent area causing bumps. Therefore, the detection of atmospheric tur- bulence targets is essentially an estimation of the spectrum width of radar echoes. At present, the methods of estimating spectrum width used in actual airborne weather radars are mainly the pulse pair processing (PPP) method and the fast Fourier transform (FFT) method [4–6]. The PPP method estimates the Doppler spectrum width by calculating the correlation function of the adjacent pulse echoes; the FFT method calculates the power spectrum of the echoes by the fast Fourier transform, and estimates Doppler spectrum width according to the sec- ond order moment of power spectrum. These two methods 123