• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.665-671
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• 1994

Some extended results in the study of two-position alignment for strapdown inertial navigation system are presented. In [1], an observability analysis for two-position alignment was done by analytic rank test of the stripped observability matrix and numerical calculation of the error covariance propagation using ten-state error model. In this paper, it is done by an analytic approach which utilizes the nonsingular condition of the determinant of simplified stripped observability matrix and by numerical calculation of the error covariance propagation accomplished in more cases than [1], and the twelve-state error model including vertical channel is used instead of ten-state error model. In addition, it is confirmed that this approach more clearly produces the same result as shown in the original work in terms of complete observability and there exist some better two-position configurations than [1] using the twelve-state error model.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.276-284
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• 2013

This paper considers the transfer alignment in the inertial navigation system and the observability analysis is performed for velocity matching. The state variable of the Kalman filter is modeled including the lever arm error and the measurement equation is obtained. The SOM(Stripped Observability Matrix) method is used for the observability analysis for various maneuvering conditions of the vehicle, which gives the full state observability condition as a specific maneuver sequence of the vehicle. While the observability analysis of a lever arm effect in the existing papers is mainly performed by simulations, we performed it analytically by the observability analysis method. The analysis result is verified using the computer simulations.

• Journal of Advanced Navigation Technology
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• v.22 no.3
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• pp.220-227
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• 2018

The most widely used method for constructing an inertial navigation system (INS)/global navigation satellite system (GNSS) coupling system is to construct an integrated navigation system using a Kalman filter. However, depending on the trajectory, non-observable state variables may be generated. In this case, the state variables are not estimated. To solve this problem, a integrated navigation system is constructed and then an observability analysis is performed. In this paper, a 24th order position-matched Kalman filter is defined to design an INS/GNSS integrated navigation system for vehicles moving with a large pitch angle change. To verify the appropriateness of the error state variables applied to the Kalman filter, an observability analysis was performed. The trajectory was divided into five segments, and the piece-wise constant system (PWCS) was assumed for each segment, and the results were analytically analyzed. The analytical results and the simulation results confirm that the error state parameters of the Kalman filter are well-designed to the estimation side.