NovAtel's Annual Journal of GNSS Technology Solutions and Innovation

Issue link: http://velocitymagazine.epubxp.com/i/164724

little bird As one can see, the major complication of this project was simply coordinating and matching the myriad of required data between not only the two external systems but also the subsystems inherent to the SPAN-SE design itself. Romote SPAN SE ExtINSPVAOutMs ExtINSPVAInMsg RelINSPVA RTCARefExtINS Bi Directional HeadingExtlNS Radio Link ExtINSPVAOutMs In order to account for the usersupplied eccentric offset, the master SPAN-SE was set up to transmit the INS position at the antenna as well as the position, velocity, and attitude corrected to the eccentric offset The underlying algorithms are quite simple and are based on two well-known techniques. First, computation of the RTK vector using double-differenced carrier phase observations and least-squares ambiguity decorrelation adjustment (LAMBDA), the well-documented method for the integer estimation of ambiguities proposed by Professor Peter Teunissen of Delft University, and second, fusion of GNSS/INS using an extended Kalman ﬁlter to control the INS errors via GNSS observables. The RTK translation vector is applied to the ﬁltered master INS estimate and used as a noise-reduced position update to control the remote INS errors. Because the transfer system of the Kalman ﬁlter is governed by the input variance, was increased the covariance of the position update by a factor of three to help ensure that computed gains were properly distributed. So, a position update at the remote receiver's location, where For more Solutions visit http:/ /www.novatel.com ExtINSPVAInMsg Master SPAN SE FIGURE 1: SPAN SE Relative Architecture RP/MP is Remote Position and Master Position, respectively, has these elements: Update = MPins + RTK Vector Update Covariance = 3.0*MPins Covariance If the RTK vector is not available, the remote will continue to perform local position updates using the single point least-squares position update and associated covariance. Inertial errors at both remote and master vehicles typically vary slowly, which means the relative error between the two systems is also slowly varying. With the presence of a valid RTK vector, the relative INS position can be corrected by differencing the two post-update INS positions from the RTK vector. This in turn will provide information about the amount of drift that has been experienced between the two INS systems. The correction can then be applied directly back to the post-update remote INS position. It should be emphasized that the FIGURE 2: Relative Navigation Schematic corrections are applied to the output of the inertial system, and not to the inertial system parameters themselves, as it will cause all the other inertial system components to become unobservable. So, the steps in applying a remote relative position correction, are as follows: Correction = RTK – (RPins – MPins) RPcor = RPins + Correction Relative Position = RPcor – MPins The correction is used to remove the bulk of the relative error caused by the slowly varying wander noticed between the two INS systems. It will typically be updated at the requested rate, but will continue to be used for a period of up to ﬁve seconds. After ﬁve seconds the amount of potential error in the correction could be as much as the singlepoint relative error; so, it will no longer provide any additional beneﬁt and could actually begin corrupting the solution further. 2013 velocity 21

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