SUBJECT: Ph.D. Dissertation Defense
BY: Brendan Nichols
TIME: Thursday, March 15, 2018, 3:00 p.m.
PLACE: Love Building, 210
TITLE: Exploiting Ambient Noise for Coherent Processing of Mobile Vector Sensor Arrays
COMMITTEE: Dr. Karim Sabra, Chair (ME)
David Trivett (ME)
Dr. Julien Meaud (ME)
Dr. Costas Arvanitis (ME)
Dr. Justin Romberg (ECE)


A network of mobile sensors, such as vector sensors mounted to drifting floats, can be used as an array for locating acoustic sources in an ocean environment. Accurate localization using coherent processing on such an array dictates the locations of sensor elements must be well-known. In many cases, a mobile, submerged array cannot meet this requirement, however the presence of ambient acoustic noise provides an opportunity to correct sensor location errors. It has been previously shown that ambient noise correlations across separated, fixed hydrophones can provide the separation distance between them [Sabra et al., IEEE J. Ocean Engineering, 2005, Vol. 30]. A time-domain framework for this method is presented for the case of vector sensors in isotropic ambient noise to quantify their gain relative to traditional hydrophone correlations. Furthermore, a novel method is presented for identifying hidden ambient noise correlation peaks when the separation distance is changing, and its accuracy is found to match that of GPS. Lastly, a novel weighted coherent processing algorithm is presented and its performance compared to traditional methods, finding increased localization precision even in the presence of severe noise. This method is applied to locating a source, and succeeds using both GPS and ambient-noise-corrected sensor locations. All experimental data used in these studies were collected from a novel vector sensor array, and details of its design and deployment are presented as well.