Earticle

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

Abstract
 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 Modied Subspace Intersection Method applied to CS-AVS Array
  4.2 Compressive beamforming
 5 Results and discussions
 6 Conclusions
 Acknowledgements
 References

키워드

저자

• N Suresh Kumar [ Naval Physical and Oceanographic Laboratory ]
• Dibu John Philip [ Rajagiri School of Engineering and Technology ]
• A. Unnikrishnan [ Naval Physical and Oceanographic Laboratory ]
• C. Bhattacharya [ Defense Institute of Advanced Technology ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605