A Fast TFM Imaging Algorithm With Tradeoff Between Resolution And Contrast

In this paper, a fast TFM imaging algorithm using partial of full matrix data is proposed that reduces the amount of computation and makes a tradeoff between the width of main lobe and the level of sidelobes. Firstly, the monostatic image is obtained by the main diagonal data of the full matrix data captured. Secondly, the sub-diagonal data of the full matrix data corresponding to the condition of separate transmitter and receiver are gradually superimposed into the monostatic image. The interval distance between transmitter and receiver is recorded as $|\sigma_{n}|$, and n is the difference between the number of transmitting and receiving elements. The trading off the width of main lobe and the level of sidelobes is controlled by the maximum interval distance $|\sigma_{\max}|$. The Stolt mapping is used for fast algorithm implementation. Simulations and experiments are used to verify the performance of the algorithm. Results have shown that the amount of data is reduced while good resolution and contrast are obtained and the implementation of algorithm in frequency-wavenumber domain is more efficient in computation.