A comparison on the positioning accuracy from different filtering strategies in IMU/ranging system

Jay Hyoun Kwon, Jong Ki Lee

Research output: Contribution to journalArticlepeer-review


The precision of sensors' position is particularly important in the application of road extraction or digital map generation. In general, the various ranging solution systems such as GPS, Total Station, and Laser Ranger have been employed for the position of the sensor. Basically, the ranging solution system has problems that the signal may be blocked or degraded by various environmental circumstances and has low temporal resolution. To overcome those limitations a IMU/range integrated system could be introduced. In this paper, after pointing out the limitation of extended Kalman filter which has been used for workhorse in navigation and geodetic community, the two sampling based nonlinear filters which are sigma point Kalman filter using nonlinear transformation and carefully chosen sigma points and particle filter using the non-gaussian assumption are implemented and compared with extended Kalman filter in a simulation test. For the ranging solution system, the GPS and Total station was selected and the three levels of IMUs(IMU400C, HG1700, LN100) are chosen for the simulation. For all ranging solution system and IMUs the sampling based nonlinear filter yield improved position result and it is more noticeable that the superiority of nonlinear filter in low temporal resolution such as 5 sec. Therefore, it is recommended to apply non-linear filter to determine the sensor's position with low degree position sensors.

Original languageEnglish
Pages (from-to)263-273
Number of pages11
JournalJournal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
Issue number3
StatePublished - 30 Jun 2008


  • Extended Kalman filter
  • Nonlinear filter
  • Particle filter
  • Sigma point Kalman filter


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