Leti and Orolia unveiled a sensor-data-fusion engine that ensures resilient positioning and navigation, even in cases of global navigation satellite system (GNSS) jamming or spoofing. Called FlexFusion, the algorithm technology processes data from GNSS, inertial management units (IMU) and odometers to provide precise positioning in all conditions.
FlexFusion’s design relies on a modelization of GNSS and IMU (triple-axis accelerometer, triple-axis gyrometer and triple-axis magnetometer) output for synthetic trajectory generation. The fusion approach exploits Bayesian estimators, e.g. Kalman filters. The first algorithm was setup on modeling signals and its optimization relies on an extensive real-life sample database acquired through field test. This process used CEA-Leti’s HYLOC reference platform, which provides a reference positioning of a few centimeters.
The new positioning technology supports edge AI because the data-fusion algorithm is performed locally to ensure that positioning and navigation information is available locally and is failsafe even in the case of jamming or spoofing of GNSS data. A version of FlexFusion that demands less of the CPU implements a loose coupling algorithm that uses GNSS receiver-output positions as entry of the algorithm. An advanced version implements a tight coupling fusion algorithm of GNSS and IMU data that significantly enhances the resilience of positioning and navigation under real-world conditions.
For more AI news, check out: