PT - JOURNAL ARTICLE AU - Sriramya Bhamidipati, AU - Grace Gao TI - Robust GPS-Vision Localization via Integrity-Driven Landmark Attention AID - 10.33012/navi.501 DP - 2022 Mar 20 TA - NAVIGATION: Journal of the Institute of Navigation PG - navi.501 VI - 69 IP - 1 4099 - https://navi.ion.org/content/69/1/navi.501.short 4100 - https://navi.ion.org/content/69/1/navi.501.full SO - NAVIGATION2022 Mar 20; 69 AB - For robust GPS-vision navigation in urban areas, we propose an integrity-driven landmark attention (ILA) technique via stochastic reachability. Inspired by cognitive attention in humans, we perform convex optimization to select a subset of landmarks from GPS and vision measurements that maximizes integrity-driven performance. Given known measurement error bounds in non-faulty conditions, our ILA technique follows a unified approach to address both GPS and vision faults and is compatible with any off-the-shelf estimator. We analyze measurement deviation to estimate the stochastic reachable set of positions associated with each landmark, which is parameterized via probabilistic zonotope (p-zonotope). We apply set union to formulate a p-zonotopic cost that represents the size of position bounds based on landmark inclusion/exclusion. We jointly minimize the p-zonotopic cost and maximize the number of landmarks via convex relaxation. For an urban data set, we demonstrate improved localization accuracy and robust predicted availability for a pre-defined risk and alert limit.