Inside GNSS Media & Research

MAR-APR 2018

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www.insidegnss.com M A R C H / A P R I L 2 0 1 8 Inside GNSS 59 way stations to rides through cuttings and tunnels. To be able to create new satellite navi- gation technologies that provide PVT information with integrity and solu- tions for high-precision positioning even under difficult conditions, a well-suited end-to-end simulation tool is required. End-to-end means that realistic signals from complete satellite constellations can be generated which take, for exam- ple, transmitter and receiver antenna characteristics, atmospheric and local wave propagation mechanisms, receiver dynamics, and other distorting effects into account. Oen such end-to-end simulations are performed using a radio frequency constellation simulator (R FCS) and hardware GNSS receivers. A number of commercial off-the-shelf solutions are available for each of these items. However, for the development of said algorithms, it is more efficient to be able to use pure software or hybrid hard- ware/software solutions. This allows for a much higher frequency for the development-integration-test cycles of a project. To respond to INLU's requirements and to meet today's needs of GNSS end- to-end simulations, Airbus Defense and Space has been developing the Position- ing and Integrity Performance Evalua- tor (PIPE) as a research activity since 2012. Beyond INLU, PIPE found appli- cations for the development of novel tracking (F. M. Schubert et alia (2014a); F. M. Schubert et alia (2015)) and chan- nel model research (I. Gulie et alia; F. M Schubert et alia (2016)), to name a few examples. e article's organization follows the high-level procedure of getting results from an end-to-end simulation run using PIPE. We first describe the sce- nario definition in terms of user trajec- tory, satellite constellation, and propa- gation channel conditions. Next, the configuration of the simulated receiver is reported with methods for acquisi- tion and tracking of GNSS signals and computation of the PVT solutions. An example is then given that reports a filter bank approach developed during the INLU project. It is used for mitigat- ing the influence a spoofer has on the receiver's performance. Scenario Generation Figure 1 reports the general structure of end-to-end GNSS simulations that can be performed using PIPE. PIPE consists of three groups of programs: tools for digital signal processing (DSP), a GNSS scenario and constellation simulator, and a GNSS receiver. PIPE's DSP pro- vides classical signal chain simulations consisting of a signal source, one or mul- tiple signal processors, and a signal sink. Among other programs, PIPE includes GNSS signal generators, filters, up- and down-converters, and interference sig- nal generators. PIPE's scenario and constellation simulator programs are able to gener- ate user trajectories, satellite positions for given times and orbits, and the propagation channel response based on multipath components. As this group of scenario-related programs differs from the DPS programs, they are called SNIPE tools — short for Scenarios for Navigation and Integrity Performance Evaluation. INLU also requires the pos- sibility to process real-world signals. Sig- nal sources for the PIPE receiver can be sampled signals as sensed by antennas, FIGURE 1 The high-level structure of the PIPE simulator that is used for the INLU activity. A scenario is defined by receiver trajectory, sensor data, GNSS observables, and a channel response. Additionally, real-world data like recordings from inertial measurement units can be processed. From this scenario definition data, the PIPE GNSS Signal Generator can start to generate samples as if they were sensed by the simulated receiver. Moreover, the scenario definition data can also be used to control hardware constellation simulators. Such a setup allows for the processing of data with the PIPE GNSS receiver, third-party software receivers, or hardware receivers via a replay device.

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