Title :
Aircraft bearing estimation using underwater acoustic sensors
Author :
Lo, Kam W. ; Ferguson, Brian G.
Author_Institution :
Maritime Div., Defence Sci. & Technol. Organ., Sydney, NSW, Australia
fDate :
June 29 2014-July 2 2014
Abstract :
The acoustic signal emitted by an aircraft (or other airborne source of broadband sound) arrives at a hydrophone located under water after propagation through the atmosphere, across the air-sea interface (where it is refracted), and then through the underwater medium. Under the far-field assumption, a mathematical model for the differential time of arrival (DTOA) of the acoustic signal at a pair of hydrophones is derived as a function of the angle of arrival (AOA) of the signal at the hydrophone pair. An inverse of this model provides an estimator for the AOA of the signal or the apparent bearing of the aircraft. Both the DTOA model and AOA estimator are found to be identical to those for an underwater source. The statistical performance of the apparent bearing estimator is evaluated using simulated data, and the results are compared with the predictions. The estimator is then applied to real data from a towed array for various transits of a propeller driven fixed-wing aircraft flying directly over and along the array axis, and from a bottom-mounted linear array for various transits of a rotary-wing aircraft (helicopter) with a flight path approximately perpendicular to the array axis. Experimental results showing the variation with time of the aircraft´s apparent bearing are presented.
Keywords :
acoustic measurement; aircraft instrumentation; direction-of-arrival estimation; hydrophones; underwater sound; aircraft bearing estimation; angle of arrival; bottom-mounted linear array; differential time of arrival; hydrophone; propeller driven fixed-wing aircraft; rotary-wing aircraft; underwater acoustic sensors; Acoustics; Helicopters; Sensor arrays; Sonar equipment; Bearing estimation; airborne source; angle of arrival; differential time of arrival; underwater acoustic sensors;
Conference_Titel :
Statistical Signal Processing (SSP), 2014 IEEE Workshop on
Conference_Location :
Gold Coast, VIC
DOI :
10.1109/SSP.2014.6884608