Systems and methods for GNSS SNR probabilistic localization and 3-D mapping

US10495464B2 · kind B2 · utility

Assignee

• The Regents of the University of California · US

Inventors

• Andrew Irish · Mountain View, US
• Jason T. Isaacs · Lompoc, US
• Francois Quitin · Brussels, BE
• Joao P. Hespanha · Lompoc, US
• Upamanyu Madhow · Lompoc, US

Key dates

• Filing date: Dec 2, 2014
• Grant date: Dec 3, 2019
• Expiry date: May 14, 2035

Classification

• Technology area (CPC G): Physics
• CPC primary: G01S19/22
• WIPO field: Measurement
• WIPO sector: Instruments

Abstract

Various embodiments each include at least one of systems, methods, devices, and software for GNSS simultaneous localization and mapping (SLAM). The disclosed techniques demonstrate that simultaneous localization and mapping (SLAM) can be performed using only GNSS SNR and geo-location data, collectively termed GNSS data henceforth. A principled Bayesian approach for doing so is disclosed. A 3-D environment map is decomposed into a grid of binary-state cells (occupancy grid) and the receiver locations are approximated by sets of particles. Using a large number of sparsely sampled GNSS SNR measurements and receiver/satellite coordinates (all available from off-the-shelf GNSS receivers), likelihoods of blockage are associated with every receiver-to-satellite beam. Loopy Belief Propagation is used to estimate the probabilities of each cell being occupied or empty, along with the probability of the particles for each receiver location.