Coupling GPS/INS and IMM Radar Tracking Algorithms for Precise Collaborative Ground Vehicle Navigation

This thesis describes a method of collaborative ground vehicle navigation utilizing shared radar data to provide observations during periods of GPS degradation. Navigational errors that typically arise from degraded GPS signals can be reduced by providing relative observations between vehicles from an Interacting Multiple Model (IMM) radar tracking filter. Loosely coupled GPS/INS Extended Kalman Filters provide navigation solutions for each vehicle. When a vehicle experiences GPS outages, other vehicles provide external observations from the IMM tracking filter to correct the INS solution and bound error growth during the outage. The IMM tracking filter uses constant velocity, constant acceleration, and constant turn models in combination to generate a tracking solution. An evaluation of the performance of the proposed method is presented using both simulated and experimental data. The IMM tracking algorithm is implemented using range, range-rate, and azimuth data from a Delphi electronically scanning radar. Results show improved navigation performance when utilizing the relative observations during GPS outages. Specifically, the drift of the INS solution is bounded by the external measurements provided by the IMM tracking filter when GPS is unavailable. Results from both simulated and experimental data sets show that the system provides drastic improvements over standalone INS navigation, with up to a 94% decrease in error on position. These results demonstrate that the proposed combination of GPS/INS and Radar IMM algorithms constitute a feasible method of maintaing navigational accuracy during GPS outages

Stomach cancer and occupational exposure to asbestos: a meta-analysis of occupational cohort studies

BACKGROUND: A recent Monographs Working Group of the International Agency for Research on Cancer concluded that there is limited evidence for a causal association between exposure to asbestos and stomach cancer. METHODS: We performed a meta-analysis to quantitatively evaluate this association. Random effects models were used to summarise the relative risks across studies. Sources of heterogeneity were explored through subgroup analyses and meta-regression. RESULTS: We identified 40 mortality cohort studies from 37 separate papers, and cancer incidence data were extracted for 15 separate cohorts from 14 papers. The overall meta-SMR for stomach cancer for total cohort was 1.15 (95% confidence interval 1.03–1.27), with heterogeneous results across studies. Statistically significant excesses were observed in North America and Australia but not in Europe, and for generic asbestos workers and insulators. Meta-SMRs were larger for cohorts reporting a SMR for lung cancer above 2 and cohort sizes below 1000. CONCLUSIONS: Our results support the conclusion by IARC that exposure to asbestos is associated with a moderate increased risk of stomach cancer