• 한국측량학회지
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• 제32권3호
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• pp.271-279
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• 2014

As an alternative way to overcome the weakness of the global navigation satellite system (GNSS) in hostile situation, a gravity gradient referenced navigation (GGRN) has been developed. This paper analyzed the performance of GGRN with respect to the initial errors, DB resolution as well as update rates. On the basis of simulations, it was found that the performance of GGRN is getting worse when initial errors exist but the navigation results are rapidly converged. Also, GGRN generates better results when DB resolution is higher and update rates are shorter than 20 seconds. However, it is difficult to deduce the optimal parameters for the navigation because some trajectories show better performance in case low-resolution DB is applied or long update rate is supposed. Therefore, further analysis to derive specific update conditions to improve the performance has been performed. Those update conditions would not be generalized for all cases although maximum improvement rate is over 200% in certain case. In the future, some more developments and tests on the combination of various geophysical data and/or algorithms are necessary to construct more stable and reliable navigation system.

• 한국측량학회지
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• 제32권1호
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• pp.63-73
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• 2014

최근 의도적인 간섭 또는 전파교란으로 인한 위성기반항법시스템(GNSS)의 정확도 저하 문제가 대두되면서 GNSS를 사용할 수 없는 환경에 대응할 수 있는 항법 기술 중 하나로 데이터베이스(DB)를 기반으로 한 항법 연구가 진행되고 있다. 본 연구에서는 지구물리 DB 중 중력구배를 선정하여 우리나라 중력구배 DB를 구축하고, 확장형칼만필터(EKF)를 적용하여 중력구배기반 항법을 구현하였다. 항법 성능은 시뮬레이션을 통해 분석하였으며, 우리나라 전역에 14개의 비행궤적을 생성한 후 다양한 DB와 센서 오차, 그리고 고도에 따른 영향을 고려하였다. 비행성능을 분석한 결과 DB와 센서 오차가 작을수록, 고도가 낮을수록 정밀한 항법이 가능함을 확인하였다. 또한, DB 기반의 항법시스템 중 가장 널리 알려진 지형참조 항법과 상대적인 성능 분석을 수행한 결과, 고도가 낮은 경우는 DB 및 센서 오차와 무관하게 대체로 중력구배기반 항법이 우수한 성능을 나타내었다. 그러나 고도가 높아지면 높은 정밀도의 중력구배계와 중력구배 DB를 탑재한 경우에만 지형참조 항법의 결과와 유사한 수준의 항법이 가능하였다. 본 연구에서 고려한 DB와 센서 오차, 고도 외에도 DB 해상도, 비행속도 및 갱신 주기 등 중력구배기반 항법에 영향을 미치는 다양한 요인이 있으므로 이를 고려한 분석이 추가로 수행되어야 할 것이다.

• 한국측량학회지
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• 제33권6호
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• pp.569-577
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• 2015

The navigation algorithm developed based on the extended Kalman filter (EKF) sometimes diverges when the linearity between the measurements and the states is not preserved. In this study, new update conditions together with two conditions from previous study for gravity gradient referenced navigation (GGRN) were deduced for the filter performance. Also, the effect of each update conditions was evaluated imposing the various magnitudes of the database (DB) and the sensor errors. In case the DB and the sensor errors were supposed to 0.1 Eo and 0.01 Eo, the navigation performance was improved in the eight trajectories by using part of gravity gradient components that independently estimate states located within trust boundary. When applying only the components showing larger variation, around 200% of improvement was found. Even the DB and sensor error were supposed to 3 Eo, six update conditions improved performance in at least seven trajectories. More than five trajectories generated better results with 5 Eo error of the DB and the sensor. Especially, two update conditions successfully control divergence, and bounded the navigation error to the 1/10 level. However, these update conditions could not be generalized for all trajectories so that it is recommended to apply update conditions at the stage of planning, or as an index of precision of GGRN when combine with various types of geophysical data and algorithm.