Sparse Nested Arrays With Spatially Spread Square Acoustic Vector Sensors for High-Accuracy Underdetermined Direction Finding

Abstract

In acoustic sensing systems, acoustic vector sensor (also known as vector hydrophone for underwater applications) arrays are widely used. Most of the acoustic vector sensor array signal processing methods presume the minimum spacing between two adjacent sensors or sensor components to be within a half-wavelength in order to avoid azimuth-elevation angle estimation aliasing. This would limit the effective array aperture, thereby reducing the potential estimation accuracy. Furthermore, they are unapplicable to the underdetermined scenarios, where the number of sources exceeds that of sensor components. Exploiting the recently proposed nested array concept, we present a new type of nested array, termed as Sparse Nested spatially spread Square Acoustic Vector sensor Array (SNSAVA) to realize underdetermined 2-D direction finding with increased estimation accuracy. In SNSAVA, interspacing of two sensors and two components of a sensor can be spread to be much higher than a half-wavelength so that the effective array aperture will be significantly extended. An unambiguous angle estimation method is further derived to make this fully sparse array configuration practically feasible. Performance studies focused on underdetermined high-accuracy azimuth-elevation angle estimation are provided via numerical examples. The estimation performance for the SNSAVA is also compared with that of the nested acoustic vector sensor arrays, proposed in [33], and with the Cramér-Rao bound.