Particle Filtering

Particle filtering is a probabilistic localization technique that estimates a user's position by maintaining a cloud of weighted "particles," each representing a possible location. As new sensor data arrives—from GPS, inertial sensors, or other sources—particles are updated, reweighted, and resampled to converge on the most likely position. In accessible navigation systems for blind and low-vision users, particle filtering is valuable because it can fuse multiple imprecise data sources, incorporate environmental constraints like walls and no-go zones, and gracefully handle the transition between indoor and outdoor environments where GPS availability fluctuates.