Abstract
A self-contained MEMS vector hydrophone with a scalar–vector integrated design is proposed in this paper. Compared with traditional MEMS vector hydrophones, this design solves the problem of ambiguity in the port and starboard during orientation, and also realizes the self-contained storage of acoustic signals. First, the sensor principle and structural design of the self-contained MEMS hydrophone are introduced, and then the principle of the combined beamforming algorithm is given. In addition to this, the amplitude and phase calibration method based on the self-contained MEMS vector hydrophone is proposed. Then, the sensitivity and phase calibrations of the sensor are carried out in the standing wave tube. The sensitivity of the vector channel is −182.7 dB (0 dB@1 V/Pa) and the sensitivity of the scalar channel is −181.8 dB (0 dB@1 V/Pa). Finally, an outdoor water experiment was carried out. The experimental results show that the self-contained MEMS vector hydrophone can accurately pick up and record underwater acoustics information. It realizes the precise orientation of the target by combining beamforming algorithms. The direction of arrival (DOA) error is within 5° under the outdoor experimental conditions with an SNR of 13.67 dB.
Highlights
The vector hydrophone has the advantage of being able to estimate the azimuth of the target by a single one, so it has been widely used in underwater passive detection in recent years
The transmitting system is composed of a signal generator, a power amplifier and a fish lip transducer, and the receiving system is composed of a self-contained MEMS vector hydrophone and a computer
The experimental results show that after attitude calibration and with the combined calculation analysis and processing, it is possible to obtain accurate direction of arrival (DOA) information from the noise radiated by the ship which was collected by the self-contained MEMS vector hydrophone
Summary
The vector hydrophone has the advantage of being able to estimate the azimuth of the target by a single one, so it has been widely used in underwater passive detection in recent years. Shang et al studied the orientation algorithm of the MEMS vector hydrophone and gave experimental results [23]. A mixed near-field and far-field source localization algorithm based on a MEMS vector hydrophone array was studied by Shang et al they only gave the simulation analysis of the algorithm, and did not carry out an experimental verification [24]. The fidelity of the data is improved, and it is convenient for carrying with the underwater platform This is more in line with the needs of MEMS vector hydrophone engineering applications. A target orientation experiment was carried out in a standing wave tube and outdoor water, and the performance of the self-contained MEMS vector hydrophone was verified by the combined beamforming algorithm
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