Acoustic Tag State Estimation With Unsynchronized Hydrophones On Auvs
2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)(2018)
Abstract
This paper presents an underwater robotic sensor system for localizing acoustic transmitters when the robot's hydrophones cannot be time-synchronized. The development of the system is motivated by applications where tracking of marine animals that are tagged with an underwater acoustic transmitter is required. The system uses two novel real-time calibration algorithms that improve the accuracy of time of flight (TOF) and time difference of arrival (TDOA) measurements. The first algorithm corrects non-linear clock skews in TOF measurements based on temperature variation. The second algorithm compensates the localized relative clock skew between clocks using a mixed integer linear program. To validate the system's performance, an Autonomous Underwater Vehicle (AUV) was deployed to track a moving tag where GPS data was used as ground truth. Compared to traditional TOF and TDOA filtering methods, the results show that the proposed system can achieve reduction of mean localization errors by 59%, and a reduction of the standard deviation of measurements by 44%.
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Key words
underwater acoustic transmitter,real-time calibration algorithms,TOF measurements,temperature variation,mixed integer linear program,AUV,TDOA filtering methods,mean localization errors,acoustic tag state estimation,unsynchronized hydrophones,underwater robotic sensor system,marine animals,time difference of arrival,autonomous underwater vehicle,nonlinear clock skews,time of flight,GPS data,TOF filtering methods,standard deviation
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