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

Area of Science:

• Animal aeroecology
• Electromagnetic scattering theory
• Radar ornithology

Background:

• Radar technology is vital for studying bird migration and aeroecology.
• Accurate radar cross-section (RCS) estimation is crucial for quantifying bird density.
• Large bird species, particularly soaring and flocking ones, lack sufficient RCS data due to complex morphology and measurement challenges.

Purpose of the Study:

• To introduce a practical modelling framework for estimating species-specific RCS in large birds.
• To address the critical lack of empirical RCS data for large avian species.
• To enhance the understanding of migration patterns and mitigate bird-aircraft collisions.

Main Methods:

• Utilized the T-matrix electromagnetic scattering method with geometrically simplified bird morphology.
• Computed spherical RCS values for 11 large bird species at C- and S-band radar wavelengths.
• Compared T-matrix results with WIPL-D software estimates (spherical and prolate spheroidal models).

Main Results:

• Spherical RCS simplification systematically overestimated RCS compared to more anatomically representative models.
• The overestimation bias was consistent and correctable using regression-derived scaling factors.
• The developed framework provides an accessible alternative for RCS estimation in large birds.

Conclusions:

• The T-matrix modelling framework offers a practical solution for estimating large bird RCS.
• This approach can be implemented in open-source platforms and integrated with automated detection tools.
• Improved RCS data will enhance aeroecological studies and aid in bird-aircraft collision mitigation efforts.