원문정보
초록
영어
Coastal surveillance and harbour defence are the most complex and challenging opera- tional issues for modern navy in the current turbulent global political climate. In most of the coastal surveillance and harbour defence systems, long sea-bed arrays consisting of hundreds of pressure sensors are deployed along the coastal belt to capture the low frequency compo- nents emanating from the sub-surface targets. Deployment of these sensor-arrays along with its associated signal conditioning hardware at the ocean-bed is a challenging task. The output of the sensor-array is to be conditioned and then digitized using multi-bit analog to digital converters (ADC). Further, the digitized channel data are required to be send to a base station through a radio frequency link. In this paper, we propose a compressively sampled (CS) architecture of acoustic vector sensor (AVS) array, to estimate the direction of arrival (DoA) of multiple acoustic sources, in a range independent shallow ocean using a one-dimensional search without prior knowledge of the ranges and the depths of the sources. We extend the high resolution angular spectral estimators MUSIC, MVDR and subspace in- tersection method (SIM) to suit the compressively sampled AVS array architecture operating in a shallow ocean environment. This architecture promises a signicant reduction in the number of sensors, analog signal conditioning hardware, data rate or bandwidth, the number of snapshots and the software complexity, leading to easy installation and maintenance.
목차
1 Introduction
2 AVS array data model for shallow ocean
3 Compressive sampling
3.1 Bene
ts of compressive sampling on AVS array processing
3.2 Applying compressive sampling to the AVS array data model for shallowocean.
4 DoA estimation
4.1 Modied Subspace Intersection Method applied to CS-AVS Array
4.2 Compressive beamforming
5 Results and discussions
6 Conclusions
Acknowledgements
References