Abstract
Multiple-input-multiple-output (MIMO) sonar systems offer new perspectives for target detection and area surveillance. This paper introduces a unified formulation for sonar MIMO systems and focuses on the target detection and recognition capability of these systems. The multiplication of the number of transmitters and receivers not only provides a greater variety in terms of target view angles but also provides meaningful statistics on the target itself. Assuming that views are independent and the MIMO system is large enough, we demonstrate that target recognition is possible with only one MIMO snapshot. By studying the detection performance of MIMO sonars we also demonstrate that such systems solve the speckle noise and decorrelate individual scatterers inside one cell resolution, leading to super-resolution imaging. We also show that, if carefully designed, MIMO systems can surpass the resolution of a synthetic aperture sonar (SAS) system using the same bandwidth. All the discussed properties are derived from the independent view assumption. Fulfilling this assumption drives the design and efficiency of such systems.
Original language | English |
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Article number | 7559821 |
Pages (from-to) | 738-751 |
Number of pages | 14 |
Journal | IEEE Journal of Oceanic Engineering |
Volume | 42 |
Issue number | 3 |
Early online date | 2 Sept 2016 |
DOIs | |
Publication status | Published - Jul 2017 |
Keywords
- MIMO sonar systems
- multistatic sonars
- super-resolution sonar images
- target recognition
ASJC Scopus subject areas
- Ocean Engineering
- Mechanical Engineering
- Electrical and Electronic Engineering
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Dive into the research topics of 'Spatially distributed MIMO sonar systems: Principles and capabilities'. Together they form a unique fingerprint.Profiles
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Keith Edgar Brown
- School of Engineering & Physical Sciences - Associate Professor
- School of Engineering & Physical Sciences, Institute of Sensors, Signals & Systems - Associate Professor
Person: Academic (Research & Teaching)
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Yvan Petillot
- School of Engineering & Physical Sciences, Institute of Sensors, Signals & Systems - Professor
- School of Engineering & Physical Sciences - Professor
Person: Academic (Research & Teaching)