Research On Array Processing Of Vector Sensor Array

A vector sensor is an acoustic transducer composed of homocentric acoustic pressure sensors and particle velocity sensors that measure simultaneously scalar quantity (pressure) and vector quantity (pressure gradient, particle velocity, acceleration, displacement, etc) at the same location. Compared with traditional pressure sensors, vector sensors can measure acoustic information more comprehensively. More information brings wider processing space and injects more life to acoustic signal processing and sonar technology.Based on the development and actuality of vector sensor and vector signal processing, the thesis emphasizes on some basic and pivotal problems of vector array processing, including combined directivity, array gain, constant beam-width design, wide-band signal processing and so on. The comprehensive analysis of theory and simulation is given and further validated by Lake Trail data.Based on the vector correlation radius, which is the foundation of vector array processing in isotropic noise field, the combined directivities of some vector combinations are compared through theoretical analysis and simulation. Furthermore, the lake trial results of MOGAN Hill and FUXIAN Lake are presented. All these indicate the advantage of vector array in combined directivity. The ability to distinguish the target's left and right is one of the essential advantages of vector sensor array as several methods presented in this thesis can resist left and right ambiguity. The performance of these methods is evaluated by simulation.In isotropic noise field, referencing the energy detector's gain of pressure array, the combined gains of some vector combinations are analyzed theoretically, which is consistent with our simulation. The expressions of the combined gains are also presented. Considering the complexity of the actual noise, the simulations in color noise background and explanations are given. In this thesis, the gainanalysis using the Lake Trail data is also discussed. Under the desired noise field, compared with traditional acoustic pressure array energy detector, the given vector combinations have maximum spatial gains of 2.5 dB to 4.5 dB respectively.A new approach to narrow-band beamforming based on adaptive Notch filter is presented in the thesis. In terms of a uniform vector array, distilling and transforming the phase difference between the neighboring sensors can realize constant beam-width beamforming. Using this method, the frequency of the transmitted signal can be reduced to below the half-wavelength frequency. Meanwhile, the desired combined directivity of vector array according to the one-wavelength frequency is also achieved. Besides, the adoption of two-level coherent accumulation algorithm can effectively enhance the performance, the added imagined-sensor improve the directivity. Through the validation of simulation and lake experiments, the approach is proved efficient. All of the work will be very instructive for the design of vector array.Broad-band signals have features as more information, smaller correlation in reverberation background and so on which are propitious to signal detection, parameter estimation and object's feature extraction. For broad-band linear frequency modulation (LFM) signal, a broad-band beamformer based on adaptive Notch filter is presented. It divides the broad frequency band to several sub-bands, then uses different Notch filters to process them, and synthesizes the outputs of all filters as the multi-beam output in the end. In addition, a wide-band signal processing frame is established using Fractional Fourier Transform (FRFT). In underwater signal processing, the detection performance of sonar is greatly influenced by Doppler, the LFM signal's energy can be collected highly by adjusting the fractional order. The method can get high anti-Doppler performance and have many meanings to improve detection performance.