ReNiL: Event-Driven Pedestrian Bayesian Localization Using IMU for Real-World Applications

Kaixuan Wu, Yuanzhuo Xu, Zejun Zhang +4

Pedestrian inertial localization is key for mobile and IoT services because it provides infrastructure-free positioning. Yet most learning-based methods depend on fixed sliding-win…