Browsing by Subject "Correlated-date fusion"

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    Correlated-Data Fusion and Cooperative Aiding in GNSS-Stressed or Denied Environments
    (2014-09) Mokhtarzadeh, Hamid;
    A growing number of applications require continuous and reliable estimates of position, velocity, and orientation. Price requirements alone disqualify most traditional navigation or tactical-grade sensors and thus navigation systems based on automotive or consumer-grade sensors aided by Global Navigation Satellite Systems (GNSS), like the Global Positioning System (GPS), have gained popularity. The heavy reliance on GPS in these navigation systems is a point of concern and has created interest in alternative or back-up navigation systems to enable robust navigation through GPS-denied or stressed environments. This work takes advantage of current trends for increased sensing capabilities coupled with multilayer connectivity to propose a cooperative navigation-based aiding system as a means to limit dead reckoning error growth in the absence of absolute measurements like GPS. Each vehicle carries a dead reckoning navigation system which is aided by relative measurements, like range, to neighboring vehicles together with information sharing. Detailed architectures and concepts of operation are described for three specific applications: commercial aviation, Unmanned Aerial Vehicles (UAVs), and automotive applications. Both centralized and decentralized implementations of cooperative navigation-based aiding systems are described. The centralized system is based on a single Extended Kalman Filter (EKF). A decentralized implementation suited for applications with very limited communication bandwidth is discussed in detail. The presence of unknown correlation between the a priori state and measurement errors makes the standard Kalman filter unsuitable. Two existing estimators for handling this unknown correlation are Covariance Intersection (CI) and Bounded Covariance Inflation (BCInf) filters. A CI-based decentralized estimator suitable for decentralized cooperative navigation implementation is proposed. A unified derivation is presented for the Kalman filter, CI filter, and BCInf filter measurement update equations. Furthermore, characteristics important to the proper implementation of CI and BCInf in practice are discussed. A new covariance normalization step is proposed as necessary to properly apply CI or BCInf. Lastly, both centralized and decentralized implementations of cooperative aiding are analyzed and evaluated using experimental data in the three applications. In the commercial aviation study aircraft are simulated to use their Automatic Dependent Surveillance - Broadcast (ADS-B) and Traffic Collision Avoidance System (TCAS) systems to cooperatively aid their on board INS during a 60 min GPS outage in the national airspace. An availability study of cooperative navigation as proposed in this work around representative United States airports is performed. Availabilities between 70-100% were common at major airports like LGA and MSP in a 30 nmi radius around the airport during morning to evening hours. A GPS-denied navigation system for small UAVs based on cooperative information sharing is described. Experimentally collected flight data from 7 small UAV flights are played-back to evaluate the performance of the navigation system. The results show that the most effective of the architectures can lead to 5+ minutes of navigation without GPS maintaining position errors less than 200 m (1-σ). The automotive case study considers 15 minutes of automotive traffic (2,000 + vehicles) driving through a half-mile stretch of highway without access to GPS. Automotive radar coupled with Dedicated Short Range Communication (DSRC) protocol are used to implement cooperative aiding to a low-cost 2-D INS on board each vehicle. The centralized system achieves an order of magnitude reduction in uncertainty by aggressively aiding the INS on board each vehicle. The proposed CI-based decentralized estimator is demonstrated to be conservative and maintain consistency. A quantitative analysis of bandwidth requirements shows that the proposed decentralized estimator falls comfortably within modern connectivity capabilities. A naive implementation of the high-performance centralized estimator is also achievable, but it was demonstrated to be burdensome, nearing the bandwidth limits.