Improving the spatial accuracy of wildlife tracking data with automated radio telemetry systems

Automated radio telemetry systems (ARTS) consisting of animal-borne radio transmitters and networks of fixed radio receivers are frequently used to continuously track wildlife movements over time. The low weight of available radio transmitters and the ability of these systems to collect data with high temporal resolution make ARTS an attractive alternative to other wildlife tracking technologies. However, the research questions that can be addressed with ARTS are often limited by the spatial accuracy of location data produced by the system. One of the primary methods used to produce location estimates with ARTS involves comparing the received signal strength (RSS) of radio transmissions detected by multiple receivers in a network. The accuracy of the resulting locations is highly dependent on the algorithm used to process the raw RSS data generated by the ARTS into location estimates. In this work, we have developed a grid search algorithm for producing location estimates from RSS data generated by networks of receivers. In an experiment conducted with a radio transmitter and receiver network, we demonstrate that the grid search method produces location estimates that are greater than 2 times more accurate than the commonly used method of multilateration. A simulation was developed to compare the accuracy of the two methods over a large range of receiver spacings and with varying levels of measurement noise in the system. The simulation showed that the grid search method and multilateration perform similarly for receiver networks with relatively close receivers; however, as the distance between receivers in the array increases, the mean error of location estimates increases much more rapidly for multilateration than for grid search. The improvement in spatial accuracy realized through the use of grid search enables the design of wildlife tracking studies utilizing ARTS to address research questions that were previously inaccessible.

Authors

Institutions

Publication Details

Journal
Animal Biotelemetry
Published
2025-11-11
DOI
https://doi.org/10.1186/s40317-025-00431-3
Primary Topic
Wildlife Ecology and Conservation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improving the spatial accuracy of wildlife tracking data with automated radio telemetry systems

Jessica Gorzo, Sheldon Blackshire, David Mizrahi, Michael Lanzone et al.
Animal Biotelemetry
Wildlife Ecology and Conservation
article

Improving the spatial accuracy of wildlife tracking data with automated radio telemetry systems

Jessica Gorzo, Sheldon Blackshire, David Mizrahi, Michael Lanzone, Sean Burcher, David La Puma
article en

Abstract

Automated radio telemetry systems (ARTS) consisting of animal-borne radio transmitters and networks of fixed radio receivers are frequently used to continuously track wildlife movements over time. The low weight of available radio transmitters and the ability of these systems to collect data with high temporal resolution make ARTS an attractive alternative to other wildlife tracking technologies. However, the research questions that can be addressed with ARTS are often limited by the spatial accuracy of location data produced by the system. One of the primary methods used to produce location estimates with ARTS involves comparing the received signal strength (RSS) of radio transmissions detected by multiple receivers in a network. The accuracy of the resulting locations is highly dependent on the algorithm used to process the raw RSS data generated by the ARTS into location estimates. In this work, we have developed a grid search algorithm for producing location estimates from RSS data generated by networks of receivers. In an experiment conducted with a radio transmitter and receiver network, we demonstrate that the grid search method produces location estimates that are greater than 2 times more accurate than the commonly used method of multilateration. A simulation was developed to compare the accuracy of the two methods over a large range of receiver spacings and with varying levels of measurement noise in the system. The simulation showed that the grid search method and multilateration perform similarly for receiver networks with relatively close receivers; however, as the distance between receivers in the array increases, the mean error of location estimates increases much more rapidly for multilateration than for grid search. The improvement in spatial accuracy realized through the use of grid search enables the design of wildlife tracking studies utilizing ARTS to address research questions that were previously inaccessible.

Animal BiotelemetryVol. 13(1)
National Audubon Society (US), RNET Technologies (United States) (US), May Institute (US)
Openalex Percentile: Top 67%
Wildlife Ecology and Conservation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.