Bearing estimation using foghorn sounds

Situational awareness is critical for safe navigation and autonomous ship operations. To improve safety and automate navigation, multi-sensor systems could involve sound-based direction-finding of foghorns. In this paper, we study the performance of a three-microphone array in bearing estimation when a distant foghorn is audible. We adopt an approach which utilizes Hilbert transforms to obtain phase delay from filtered sounds, and get bearing estimate by minimization of an energy function. We compare this approach with a cross correlation method and GPS-based ground-truth bearing. We present results from simulated tests, laboratory tests with synthetic foghorn sounds, and field tests done on a cruise vessel in the Gulf of Finland. The results suggest that vessel bearing estimation is possible through foghorn sounds received by the microphone array. Best accuracy of 7^∘ is achieved in bearing estimation using Hilbert transform approach with target-to-receiver distance of 3.2 km, and processing time of 19 ms for 1 second of sound information. We provide recommendations on how the sound could play an important role in multi-sensor systems. It can be concluded that sound sensory information is useful in autonomous navigation.