Key Technology Study Of Subsurface Buoy Detection System Based On Very Low Frequency Vector Sensor

Vector sensor is combined by sound pressure hydrophone and particle velocity sensor with dipole directivity, the directivity of vector channel is independent of frequency. Vector sensor has broad application prospects in acoustic field parameters acquisition and long range target detection at low and very low frequency. Compared with sound pressure hydrophone, vector sensor can synchronously measure sound pressure and three orthogonal components of particle velocity at the same location in acoustic field. It can provide more information and more choice for signal processing. The design of installation platform is one of the basic premise for vector sensor application, especially in low and very low frequency band. With a detailed study, vector sensor technology will be more widely used in underwater acoustic domain.In the thesis, vector sensor calibration technology, sea buoy technology and inactive target bearing tracking technology are reviewed. Based on subsurface buoy detection system with very low frequency vector sensor, the theoretical and experimental research is presented about vector sensor calibration technology in low and very low frequency band, vector acquisition system of acoustic field in low and very low frequency band and target bearing tracking algorithm with single vector sensor.Firstly, for the problem that moving-coil vector sensor calibration in low and very low frequency band is difficult, the vector sensor calibration method in tank is studied in low and very low frequency band. The relevant principles of air-acoustic are used for reference and acoustic field in rectangular tank is analyzed when low frequency sound source produces continuous harmonic wave. The direct sound of sound field is dominant near sound source and propagates by spherical expansion. Based on the character of sound field in tank, vector sensor calibration method in low and very low frequency band in tank is presented. When vector sensor is calibrated in spherical wave sound field in tank, for equivalent result of plane wave sound field, the raw measurement is spherically corrected and correction method is provided for calibration. In the thesis, the process of moving-coil vector sensor calibration in tank is introduced, results reveal that the calibration method is feasible.Secondly, vector acquisition system of acoustic field is studied in the thesis. For the character that there are some demands of vector sensor to installation platform, the installation platform is designed. The posture of subsurface buoy in sea water is proved stably by stress analysis of subsurface buoy and the results of sea trial and the installation platform is suitable for vector sensor. Low-noise data acquisition unit is designed for correct information acquisition of sound field. The self-contained storage unit and wireless communication net are designed and acquisition data can be self-stored in subsurface buoy or transmitted to main station in real time. Several sea trials show that the posture of vector acquisition system of acoustic field is stable and the system can correctly record information of acoustic field. The system can record vector information of acoustic field and is an important means of acoustic field vector analysis and long range detection in low and very low frequency band.Thirdly, for the problem of inactive target bearing tracking by single vector sensor, base on pre-estimation of target bearing by cross-spectral sound intensity method, the algorithm that the target bearings in validation gate are associated by probabilistic data association is presented and the estimation is more accurate. Target bearing tracking is non-linear problem and azimuth angle change with time is non-linear, so input estimation algorithm is used to enhance the performance of probabilistic data association for target bearing tracking. When there is bearing cross by multi-targets, joint probabilistic data association algorithm is used to track recognition. The computation quantity of optimal joint probabilistic data association algorithm is large, for reducing computation quantity, a new approximate decoupling joint probabilistic data association algorithm is presented and computation quantity is reduced.A summary of full thesis and the future prospects of research are in the final.