An underwater glider equipped with a hydrophone observed the acoustic sounds of an earthquake that occurred on 15 November 2017 05:29:32 (UTC) in the Pohang area. The underwater glider observed the earthquake sounds after 19 s (05:29:51) at approximately 140 km from the Pohang epicenter. In order to distinguish the earthquake sound from the glider’s operation noise, the noise sources and Sound Pressure Level (SPL) of the underwater glider were analyzed and measured at laboratory tank and sea. The earthquake acoustic signal was distinguished from glider’s self-noises of fin, pumped Conductivity-Temperature-Depth profiler (CTD) and altimeter which exist over 100 Hz. The dominant frequencies of the earthquake acoustic signals due to the earthquake were 10 Hz. Frequencies at which the spectra had dropped 60 dB were 50 Hz. By analysis of time correlation with seismic waves detected by five seismic land stations and the earthquake acoustic signal, it is clearly shown that the seismic waves converted to Tertiary waves and then detected by the underwater glider. The results allow constraining the acoustic sound level of the earthquake and suggest that the glider provides an effective platform for enhancing the earth seismic observation systems and monitoring natural and anthropogenic ocean sounds.

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(Cho, 2015), with the exception of a quantitative difference at resonant periods. The experimental results showed that the sloshing characteristics in a tank were closely dependent on both the porosity and submergence depth of the baffle, and the optimal porosity existed near P = 0.1275.

A navigation system is critical for the operation of autonomous vehicles. Various sensors must be used to build navigation systems. To fuse multiple sensors, a highly advanced filter algorithm is required. Navigation systems have difficulties in signal-degraded scenarios, where the navigation solution can be degraded by errors such as multipath and obscured signals. This paper proposes a navigation system using a technique to reject the outliers measured by sensors. The navigation system was designed to include sensor modeling, navigation filters, and outlier rejection. The sensors used in the navigation system are the accelerometer, gyroscope, magnetometer, and global positioning system. Before the experiment, a navigation simulation was performed to evaluate the results and validate the proposed navigation algorithm. The results of the experiment verified that the navigation system, including outlier rejection, had less positional error than that of the general navigation system.

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