Path integration (PI) method for the parameter-retrieval of aircraft wake vortex by Lidar

Abstract

Aircraft wake is a pair of strong counter-rotating vortices generated behind a flying aircraft. It might be very hazardous to a following aircraft and the real-time detection of it is of great interest in aviation safety field. Vortex-core positions and velocity circulations, which respectively represent the location and strength of a wake, are two characteristic parameters that have attracted the main attention in wake vortex detection. This paper introduces a new algorithm, the Path Integration (PI) method, to retrieve the characteristic parameters of wake vortex. The method uses Doppler velocity distribution to locate the vortex-core positions, and the integration of Doppler velocity along a LOS (line-of-sight) is derived as a linear expression about the circulations. From this expression, the circulations can be solved with the least square method. Moreover, an vortex-core position adjusting method is proposed to compensate the compressing and expanding effects of wake vortex caused by the scanning of Lidar beam. Basically, the use of Doppler velocity integration can improve the method’s adaptability in turbulence environment and mitigate the impact of noise. Numerical examples and field detection data from Hong Kong international airport and Tsingtao Liuting airport have well verified the good performance of the method, in terms of both accuracy and efficiency.

Two‐step locating method for aircraft wake vortices based on Gabor filter and velocity range distribution

“…If the maximum range of interest is , the range and elevation step for interpolation can be set as 1 m and , respectively. In this paper, the triangulation‐based cubic interpolation method is used [8] and the locating of vortex cores will be processed on the interpolated Doppler velocity.…”

“…The Doppler spectrum is calculated from consecutive echo samples with fast Fourier transform (FFT) and spectra accumulation is made between pulse repetition time. Based on the accumulated spectrum, the Doppler velocity can be obtained from the weighted average around the spectral peak [8].…”

“…Under clear air condition (sunny day), the echo signals are mainly caused by the particles involved in the wake vortex, and the effective sensor is lidar. Thobois [6] and Hon and Chan [7] successfully detected the wake vortex with lidar, Li et al [8] and Shen et al [9] proposed a strength retrieval algorithm and constructed a parameter‐retrieval system for wake vortex based on lidar detection. However, under wet weather conditions (rainy/foggy/snowy day), lidar does not work well due to the heavy attenuation and the proposed sensor is radar.…”

A Spatio-Temporal Neural Network for Fine-Scale Wind Field Nowcasting Based on Lidar Observation

“…At present, lidar has been widely applied for wind field measurement because of its high accuracy and resolution in dry air condition [8], [9], [10], [11], [12], [13], [14], [15]. However, a single lidar can only measure the Doppler velocities, say, the velocity components along the line of sight (LOS), which are insufficient to describe the 2-D or 3-D wind Hang Gao, Chun Shen, Xuesong Wang and Jianbing Li are with the State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System and the College of Electronic Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China (e-mail: gaohang108@163.com, chunshen@nudt.edu.cn, wxs1019@vip.sina.com, jianbingli@nudt.edu.cn).…”

Cloud Seeding Evidenced by Coherent Doppler Wind Lidar

“…The Doppler wind lidar as an active optical remote sensing instrument measures the radial velocity accurately; these are primarily applied in detecting windshear [32], turbulence [33][34][35][36], aircraft vortex [37], fog [38,39], the atmosphere boundary layer [40], and gravity waves [41] under clear air conditions [42][43][44][45]. Recently, lidars have been extended to precipitation detection for their ability to detect the aerosol and precipitation signals simultaneously under rain conditions [46][47][48][49][50].…”