The transitional zone in the ocean is the channel connecting the shallow water and deep water and where the sloping bottom widely exists and affects the sound propagation significantly.

Source range estimation in the transitional zone has been an important issue. Previous studies about source range estimation are mainly concentrated on shallow water and the primary means are match-field process, waveguide invariant process and warping transform process.

Researchers from the Institute of Acoustics of the Chinese Academy of Sciences proposed an approach for source range estimation in an ocean environment with sloping bottom recently. The study was published in Chinese Physics Letters.

This approach is based on matching the depth structure of pulse waveform between the received and simulated signals. For the explosive sources in the experiment with two depths, the mean relative errors of range estimation are both less than 7%, which shows the effectiveness of this algorithm.

In a slope environment, the depth structures of pulse waveforms were utilized to estimate source range. Researchers delayed the pulse signals recorded by all the channels, then superposed all delayed signals and supposed that all signals are received by the first channel. This step transformed the two-dimensional pulse waveform (depth and temporal distribution) into one-dimensional (temporal distribution), which not only reserved the distribution structure of pulse waveform, but also provided more information for range estimation.

Comparing the experimental and numerical pulse waveforms, it was observed that the depth structures agree well. Besides, the depth structures of pulse waveform were different when the source ranges were changed. Accordingly, source range was able to be estimated through matching the depth structure of pulse waveform.

When the source depth is 200 m and range is 5.2 km, after correlated process of the experimental data and the numerical data, the cross-correlation coefficient versus source range can be obtained. Afterwards, the range corresponding to the maximum value of the correlation coefficient is 5.3 km, which is the estimated source range.

Applying the algorithm to all the experimental data in the propagation track, results showed the mean relative error is 5.21%, which revealed that this algorithm is effective for source range estimation. However, due to the errors of bottom parameters in the complicated environment with a slope bottom, range estimation would have bad performance in some special ranges.