We consider the problem of estimating the trajectory of a submerged source emitting acoustic signals without using any anchor nodes or receiving array. This approach is required for several applications, including the localization of acoustic sources such as marine mammals or underwater vehicles, for which the cost of covering a broad area with multiple receivers would be excessively high. Since multi-lateration is impossible in this scenario, we perform localization by incorporating bathymetry information. Specifically, we assume that the receiver retains knowledge of the environmental parameters that affect the signal propagation, and that the bathymetry of the area is sufficiently diverse to induce distinguishable channel impulse responses for different source locations. Our method compares the channel estimates obtained from the received acoustic signals against a database of channel responses, pre-computed through an acoustic ray tracing model. The set of possible node locations that result are then organized in trellis form to obtain a final estimate of the source's trajectory via a path tracking method similar to the Viterbi algorithm. Our results show that the proposed approach can estimate node locations and paths with very small error, provided that the receiver has sufficiently accurate and up-to-date environmental information.
|Title of host publication||2017 14th Workshop on Positioning, Navigation and Communications, WPNC 2017|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|State||Published - 8 Jan 2018|
|Event||14th Workshop on Positioning, Navigation and Communications, WPNC 2017 - Bremen, Germany|
Duration: 25 Oct 2017 → 26 Oct 2017
|Name||2017 14th Workshop on Positioning, Navigation and Communications, WPNC 2017|
|Conference||14th Workshop on Positioning, Navigation and Communications, WPNC 2017|
|Period||25/10/17 → 26/10/17|
Bibliographical noteFunding Information:
ACKNOWLEDGMENT This research was sponsored in part by the NATO Science for Peace and Security Programme under grant G5293.
This research was sponsored in part by the NATO Science for Peace and Security Programme under grant G5293.
© 2017 IEEE.
ASJC Scopus subject areas
- Control and Optimization
- Computer Networks and Communications