Detection-Guided Beamforming for Efficient Bat Localisation

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

Abstract Passive acoustic monitoring is widely used to study wildlife, but current approaches provide limited insight into the spatial behaviour of animals. In bat ecology, reconstructing flight trajectories is essential for studying habitat use, movement patterns, and interactions, yet it remains difficult to achieve under field conditions. Acoustic cameras offer a potential solution by enabling sound source localisation, but their practical application is limited by the computational cost of beamforming and by the non-stationary, broadband, and transient nature of echolocation calls. In particular, exhaustive beamforming over wide ultrasonic bandwidths and dense spatial grids becomes infeasible for continuous monitoring. In this work, we propose a detection-guided beamforming framework for efficient localisation of free-flying bats. The method exploits the sparsity of echolocation signals by restricting beamforming to detector-identified time-frequency regions and combines this with physically consistent short-time analysis parameters and dense spatial sampling. The framework is evaluated on field recordings acquired with a Sorama CAM iV64s acoustic camera. Results show that detection-guided processing reduces the number of beamformer evaluations by approximately 77×, corresponding to a reduction of about 98.7 % in computational effort, while preserving spatial resolution. At the same time, the proposed parameter configuration improves the stability and sharpness of reconstructed trajectories by avoiding artefacts associated with temporal averaging. These findings demonstrate that high-resolution acoustic localisation can be achieved under realistic computational constraints, supporting the integration of acoustic cameras into ecological monitoring workflows. The proposed framework enables the extraction of spatial trajectories from passive acoustic monitoring data, facilitating spatially resolved analyses of bat behaviour in field conditions. Highlights Acoustic beamforming enables spatial analysis of bat behaviour but is computationally expensive. We propose a detection-guided beamforming framework using the BatDetect2 bat-call detector to exploit time–frequency sparsity. The method reduces beamforming cost by over an order of magnitude while improving trajectory stability. This enables near-real-time spatial localisation of free-flying bats in field conditions.

Authors 5

1. Roberto Alessandri corresponding

   Tilburg University · Bat Conservation Trust

   Affiliation as printed

   Bat Conservation Trust, 8 Battersea Park Road, London, SW8 4BG, United Kingdom

   Sorama B.V., Achtseweg Zuid 153H, Eindhoven, 5651 GW, The Netherlands

   Tilburg School of Humanities and Digital Sciences, Tilburg University, Warandelaan 2, Tilburg, 5037 AB, The Netherlands

2. Lia R. V. Gilmour

   Bat Conservation Trust

   Affiliation as printed

   Bat Conservation Trust, 8 Battersea Park Road, London, SW8 4BG, United Kingdom

3. Jin Jack Tan
   Affiliation as printed

   Sorama B.V., Achtseweg Zuid 153H, Eindhoven, 5651 GW, The Netherlands

4. Alejandro Osses
   Affiliation as printed

   Sorama B.V., Achtseweg Zuid 153H, Eindhoven, 5651 GW, The Netherlands

5. Dan Stowell Aachen Naturalis Biodiversity Center

   Naturalis Biodiversity Center · Tilburg University

   Affiliation as printed

   Naturalis Biodiversity Center, Darwinweg 2, Leiden, 2333 CR, The Netherlands

   Tilburg School of Humanities and Digital Sciences, Tilburg University, Warandelaan 2, Tilburg, 5037 AB, The Netherlands