The acoustic localization of wildlife can provide valuable ecological and conservation information. However, achieving an accurate acoustic source location within a defined area remains challenging due to the complexities of real-life (synchronized) landscape passive acoustic monitoring. This work presents a multilateration methodology to estimate bird call locations based on the Gillette and Silverman algorithm, a closed-form linear method whose implementation was simplified by the novel Python library OpenSoundscape. We tested it by localizing playback of a pre-recorded Grey Warbler (Gerygone igata) song at known locations using a grid of synchronized microphones uniformly placed in a flat open landscape. Our approach was able to locate 19 of the 20 replayed events within 1.24 ± 0.90 m of their real source position (in a \(80\times 80\) m grid). This is the first approach to tracking birds through synchronized audio recordings in the open field.