Online time-resolved reconstruction method for acoustic tomography system

Yong Bao, Jiabin Jia

Research output: Contribution to journalArticlepeer-review


Acoustic tomography can deliver accurate quantitative reconstruction of the covered temperature distribution with low equipment cost. For the application of real-time temperature field monitoring, both the temporal resolution and reconstruction speed are of great significance. In this paper, we developed a novel online time-resolved reconstruction (OTRR) methods, which can improve temporal resolution to capture dynamic changes and accelerate the tomographic reconstruction process for online real-time monitoring. Firstly, by exploiting the redundancy of the temporal information, a temporal regularisation is designed based on adaptive auto aggressive (AR) model to reduce the required amount of TOF data per frame. A sliding overlapping window is applied to further improve the reconstruction accuracy. Secondly, recursive reconstruction process performs a sliding iteration over each data segment. For the reconstruction of each frame, the online computation is non-iterative. Numerical simulation and lab-scale experiment are performed to validate the proposed OTRR method. The reconstruction images are compared with the online time-resolved reconstruction methods based on Kalman filter. Results show that our method can improve the temporal resolution the computational time and produce acceptable results.
Original languageEnglish
JournalIEEE Transactions on Instrumentation and Measurement
Early online date17 Oct 2019
Publication statusE-pub ahead of print - 17 Oct 2019


  • time-resolved tomography
  • online reconstruction
  • acoustic tomography
  • Image Reconstruction
  • Tomography
  • Temperature measurement
  • acoustic measurement
  • Acoustics
  • Spatial resolution


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