Localization of an Acoustic Fish-Tag using the Time-of-Arrival Measurements: Preliminary results using eXogenous Kalman Filter

Abstract

This paper addresses the source localization problem of an acoustic fish-tag using the Time-of-Arrival measurement of an acoustic signal, transmitted by the fish-tag. The Time-of-Arrival measurements denote the pseudo-range information between the acoustic receiver and the fish-tag, except that the Time-of-Transmission of the acoustic signal is unknown. Starting with the pseudo-range measurement equation, a globally valid quasi-linear time-varying measurement model is presented that is independent of the Time-of-Transmission of the acoustic signal. Using this measurement model, an Uniformly Globally Asymptotically Stable (UGAS), three stage estimation strategy (eXogenous Kalman Filter) is designed to estimate the position of an acoustic fish-tag and evaluated against a benchmark Extended Kalman Filter based estimator. The efficacy of the developed estimation method is demonstrated experimentally, in presence of intermittent observations using an array of receivers mounted on three Unmanned Surface Vessels (USVs).

Design and validation of a system of autonomous fish tracking vehicles

“…Nevertheless, the high SNR readings where most of the tag detections were received definitively show that the vehicle system was able to collaboratively position a genuinely small acoustic transmitter tag in an uncontrolled environment. Compared with the results presented in [11] and [12], the power of the tracked transmitter was 21 dB lower (137 vs. 158 dB Re 1 µPa at 1 m [30]), and was transmitting with significantly longer update intervals (30 s -90 s pseudorandom interval vs. 7 s fixed interval).…”

“…Recursive filters that suppress noise are therefore crucial, along with adaptive sampling strategies that optimize receiver (vehicle) position with respect to geometry and detection probability. Preliminary results presented in [12] and [11] demonstrate the feasibility of this approach with acoustic receivers carried by autonomous surface vehicles. Our goal is to extend this approach and demonstrate its viability even for smaller and less frequently transmitting tags in an uncontrolled environment.…”

“…In contrast, autonomous surface vehicles (ASV) have the benefit of simultaneous access to both air and water, which enables them to take advantage of both efficient radio-based communications and positioning systems while maintaining a connection to the underwater environment through a submerged acoustic receiver. In [11], [12], three ASVs carrying acoustic telemetry receivers were collaborating to track an acoustic transmitter carried by a fourth ASV simulating a moving fish. The system employed multilateration in an exogenous Kalman filter to estimate the position of the acoustic tag in combination with a distance-based formation controller [13] that directed the tracking vehicles to positions where subsequent transmissions were likely to be detected in a favorable geometry.…”