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Corresponding Author

Kraza, A.

Subject Area

Electrical Engineering

Article Type

Original Study

Abstract

Inertial navigation systems (INS) can provide high-accuracy position, velocity, and attitude information over short time periods. However, their accuracy rapidly degrades with time due to inertial sensor errors. To damp down the error growth, the INS sensor errors should be properly estimate and compensated before the inertial data are involved in the navigation computation. Therefore, appropriate modeling of the INS sensor errors is a necessity. Allan Variance (AV) is a simple and efficient method for modeling and verifying these errors by representing the root mean square (RMS) random drift error as a function of averaging time. Allan variance can provide information on the types and magnitude of the various error terms. This paper uses the AV technique to analyze and model different types of random errors residing in the measurements of Micro Electro Mechanical System (MEMS) based inertial sensors. The derived stochastic error model will be further included in the INS error model for intergrade navigation system, once the correctness of the model is verified. Finally , the paper presents the test results and model validation.

Keywords

Stochastic modeling; Allan variance (AV); Inertial sensor errors; INS; MEMS

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