Orthogonal waveform separation in multiple‐input and multiple‐output imaging sonar with fractional Fourier filtering
Abstract Multiple‐input and multiple‐output (MIMO) imaging sonar can achieve high spatial resolution with a minimum number of elements and improve imaging performance. However, the superposed echoes for the multiple transmitted orthogonal waveforms cannot be separated perfectly using conventional ma...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-05-01
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| Series: | IET Radar, Sonar & Navigation |
| Online Access: | https://doi.org/10.1049/rsn2.12051 |
| Summary: | Abstract Multiple‐input and multiple‐output (MIMO) imaging sonar can achieve high spatial resolution with a minimum number of elements and improve imaging performance. However, the superposed echoes for the multiple transmitted orthogonal waveforms cannot be separated perfectly using conventional matched filtering, which can severely reduce the quality of underwater acoustic images because of cross‐correlation noise. Herein, an orthogonal waveform separation method based on the fractional Fourier filtering to suppress the cross‐correlation noise between received orthogonal waveforms is proposed for the MIMO imaging sonar. First, the superposed echoes for transmitted linear frequency‐coded waveforms are processed using a fractional Fourier transform. Then, time‐varying fractional Fourier filters are used to separate echoes corresponding to different transmitted waveforms. Subsequently, images are obtained by joint transmit‐receive beamforming for the output of matched filtering with weighting. Finally, the results of numerical simulations and a lake experiment demonstrate that the cross‐correlation noise between the received orthogonal waveforms is effectively suppressed. Moreover, the image becomes sharp and its quality is improved with sidelobe levels lower than −40 dB. |
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| ISSN: | 1751-8784 1751-8792 |