3 research outputs found
Acoustic tomography imaging for atmospheric temperature and wind velocity field reconstruction
Owing to its non-invasive nature, fast imaging speed, low equipment cost,
scalability for a variety of measurement ranges, and ability to simultaneously
monitor both temperature and wind velocity fields, acoustic tomography has
attracted considerable interest in the field of atmospheric imaging. This thesis
aims to improve the reconstruction quality of the acoustic tomography system
for temperature and wind velocity field imaging. Focusing on this goal, the
contribution of the thesis can be summarised from the perspectives of data
collection system development, robust and accurate TOF estimation method,
and high-quality scalar and vector tomographic image reconstruction methods
for temperature and wind velocity fields respectively. Details are given below.
Firstly, in order to facilitate the experimental study of acoustic tomography
imaging, the design and evaluation of the data collection system and TOF
estimation method was presented. The evaluation results indicate that the
presented data acquisition system and TOF estimation method has good
quantitative accuracy in the lab-scale experiments.
The temporal resolution is of great significance for the real-time monitoring of
the fast-changing temperature field. To improve the temporal resolution, a
novel online time-resolved reconstruction (OTRR) method is presented, which
can reconstruct high quality time-resolved images by using fewer TOFs per
frame. Compared to state-of-the-art dynamic reconstruction algorithms such
as the Kalman filter reconstruction, the proposed algorithm demonstrated
superior spatial resolution and preferable quantitative accuracy in the
reconstructed images. These features are necessary for the real-time
monitoring of the fast-changing temperature field.
The forward modelling of most acoustic tomography problems is based on a
straight ray model, which may result in large modelling errors due to the
refraction effect under a large gradient temperature field. In order to reduce
the inaccuracy of using the straight ray model, a bent ray model and nonlinear
reconstruction algorithm is applied, which allows the sound propagation ray
paths and temperature distribution to be reconstructed iteratively from the
TOFs.
Using acoustic tomography to reconstruct large-scale temperature and wind
velocity fields, a fully parallel TOF measurement scheme is necessary. To
achieve this goal, a set of orthogonal acoustic waveforms based on the filtered
and modulated Kasami sequence is designed and a cross-correlation based
TOF estimation method is used for data collection. Besides, to overcome the
invisible field problem and improve the image quality of the wind velocity
reconstruction, a divergence-free regularised vector tomographic
reconstruction algorithm is studied. The proposed method is able to provide
accurate tomographic reconstruction of the 2D horizontal wind velocity field
from the TOF measurements.
In summary, this thesis focuses on the improvement of acoustic tomography
techniques for temperature and wind velocity fields, including the phase
corrected Akaike information criterion (AIC) TOF estimation for accurate and
robust TOF estimation, the online time-resolved reconstruction method for
real-time monitoring of the fast changing temperature field, the nonlinear
reconstruction based on the bent ray model to reconstruct the temperature
field with a large gradient, and the divergence-free regularised reconstruction
method to visualise the 2D horizontal wind velocity field