Inside Unmanned Systems

APR-MAY 2016

Inside Unmanned Systems provides actionable business intelligence to decision-makers and influencers operating within the global UAS community. Features include analysis of key technologies, policy/regulatory developments and new product design.

Issue link: https://insideunmanned.epubxp.com/i/668560

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Navigation

Page 57 of 75

58 unmanned systems inside April/May 2016 GROUND AUTOMOTIVE F or this example, the UAV is deployed in an open field; next, the vehicle enters an urban canyon to perform tasks such as surveying and inspection; and, finally, it re- turns to the deployment point. To enable opera- tion of the UAV at any point on the flight path, a precision navigation, attitude, and time capabil- ity on-board the vehicle is required. Currently, the majority of navigation prod- ucts rely on Global Navigation Satellite Systems (GNSS) as a primary navigation aid. Yet, GNSS signal availability and navigation data qual- ity decrease rapidly once operational environ- ments shift from open sky to degraded signal scenarios. Multi-sensor augmentations of GPS can maintain the required localization capabili- ties. However, as illustrated in Figure 2, cur- rent multi-sensor implementations are rather ad hoc and sensors-specific. Short-term gains in implementation efficiency are soon offset by non-recurring engineering costs of initial devel- opment and long-term higher integration costs whenever changes or upgrades are required. To address limitations of sensor fusion tech- nologies in GNSS-degraded applications, we have been developing plug-and-play (PnP) sen- sor fusion mechanizations. As shown in Figure 3, the PnP navigation solution automatically re- configures itself as sensors are connected to (dis- connected from) the system, without the need to redesign the system architecture or its specific components. PnP sensor fusion is supported by Andrey Soloviev, Michael Veth, Chun Yang, QuNav Mikel Miller, SoloNavigation PLUG AND PLAY SENSOR FUSION FOR NAVIGATION IN GNSS-CHALLENGED ENVIRONMENTS Introduction Many existing and perspective applications of navigation systems would benefit notably from the ability to navigate accurately and reliably in difficult environments. Examples of difficult navigation scenarios include urban canyons, indoor applications, radio-frequency (RF) interference and jamming environments. In addition, different segments of a mission path can impose significantly different requirements on the navigation sensing technology and data processing algorithms. To exemplify, Figure 1 shows a mission scenario of an autonomous aerial vehicle (UAV).

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