Trilateration Method

Trilateration, and its generalization multilateration, are geometric methods for determining a location using distance measurements from multiple known points. Current research focuses on improving accuracy and robustness by incorporating additional sensor data (e.g., angle, Doppler shift), employing advanced algorithms like maximum likelihood estimation and optimal transport, and integrating machine learning techniques (e.g., graph neural networks) to handle noisy measurements. These advancements are significantly impacting diverse fields, from satellite tracking and navigation (improving initial orbit determination) to robotics and indoor positioning systems, enabling more precise and reliable localization in challenging environments.