Estimating large birds' radar cross-section for aeroecology studies using T-matrix modelling.

Abstract

Radar technology has become a powerful tool for studying animal aeroecology in the lower atmosphere, particularly bird migration across large spatio-temporal scales. Quantifying bird density from radar data requires radar cross-section (RCS) estimates. Although RCS data exist for small bird species, large birds, especially soaring and flocking species, remain poorly characterized, partly due to technical challenges in measuring and modelling their complex morphology. This study introduces a practical and accessible modelling framework for estimating species-specific RCS in large birds, using the T-matrix electromagnetic scattering method, based on geometrically simplified representations of bird morphology. We computed spherical RCS values for 11 large bird species across C- and S-band radar wavelengths and compared them with both spherical and prolate spheroidal RCS estimates obtained using the WIPL-D software, a method previously validated for biological targets. As expected, the spherical simplification led to a systematic overestimation of RCS relative to a more anatomically representative model. However, the bias was consistent and can be corrected using regression-derived scaling factors. This approach addresses the critical lack of empirical RCS data for large birds, offering an alternative that can be implemented in open-source platforms. It can be integrated with automated detection tools to enhance our understanding of migration patterns in understudied bird groups and to support efforts to mitigate bird-aircraft collisions.