ArticleEcology and evolution2022
Optimizing trilateration estimates for tracking fine-scale movement of wildlife using automated radio telemetry networks.
Article in Ecology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Enabling high-resolution wildlife tracking: antenna beam-based approach including novel per-position error estimations for automated radiotelemetry systems.Movement ecology · 2026Article
- Windy weather drives social structure in wild zebra finches.Movement ecology · 2026Article
- Tracking large bees in open landscapes with active radio tags-Advantages and challenges using stationary receivers.The Journal of animal ecology · 2025Article
- Hidden space use behaviors of a nonbreeding migratory bird: the role of environment and social context.Movement ecology · 2024Article
- Constant companions: wild zebra finch pairs display extreme spatial cohesion.Biology letters · 2024Article
- Tracking Small Animals in Complex Landscapes: A Comparison of Localisation Workflows for Automated Radio Telemetry Systems.Ecology and evolution · 2024Article
- A multi-species evaluation of digital wildlife monitoring using the Sigfox IoT network.Animal biotelemetry · 2023Article
- Optimizing trilateration estimates for tracking fine-scale movement of wildlife using automated radio telemetry networks.Ecology and evolution · 2022Article
- High spatial pair cohesion during and after breeding in a socially monogamous territorial passerine.Behavioral ecology : official journal of the International Society for Behavioral EcologyArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A major advancement in the use of radio telemetry has been the development of automated radio tracking systems (ARTS), which allow animal movements to be tracked continuously. A new ARTS approach is the use of a network of simple radio receivers (nodes) that collect radio signal strength (RSS) values from animal-borne radio transmitters. However, the use of RSS-based localization methods in wildlife tracking research is new, and analytical approaches critical for determining high-quality location data have lagged behind technological developments. We present an analytical approach to optimize RSS-based localization estimates for a node network designed to track fine-scale animal movements in a localized area. Specifically, we test the application of analytical filters (signal strength, distance among nodes) to data from real and simulated node networks that differ in the density and configuration of nodes. We evaluate how different filters and network configurations (density and regularity of node spacing) may influence the accuracy of RSS-based localization estimates. Overall, the use of signal strength and distance-based filters resulted in a 3- to 9-fold increase in median accuracy of location estimates over unfiltered estimates, with the most stringent filters providing location estimates with a median accuracy ranging from 28 to 73 m depending on the configuration and spacing of the node network. We found that distance filters performed significantly better than RSS filters for networks with evenly spaced nodes, but the advantage diminished when nodes were less uniformly spaced within a network. Our results not only provide analytical approaches to greatly increase the accuracy of RSS-based localization estimates, as well as the computer code to do so, but also provide guidance on how to best configure node networks to maximize the accuracy and capabilities of such systems for wildlife tracking studies.
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