INS/GPS integration and adaptive filtering methods for guided munitions

Date

2023-9-11

Author

Eroğlu, Nur Sıla

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INS/GPS integration is a widely used application in aerospace to obtain navigation solutions. Both sensors have complementing properties, and navigation solution improves significantly when INS and GPS are utilized together. This study applies INS/GPS integration on a guided munition by loosely and tightly coupled integration techniques. Error-state Kalman filters are used in INS/GPS integration. Even though GPS provides measurements with high precision, GPS can be prone to outside effects, and the measurements from GPS can become unreliable. For these situations, adaptive Kalman filter is implemented. This adaptive method calculates scale factors for the measurement noise covariance matrix. If a faulty measurement is detected, these scale factors are multiplied with the measurement noise covariance matrix. Scale factors can be singular (SSF) or multiple (MSF), meaning it can be a scalar or a diagonal matrix. It is illustrated that MSF helps to obtain better navigation solutions in all cases compared to the faulty measurement and SSF. On the other SSF provides better navigation solutions in several cases than the faulty measurement. It is concluded that if GPS measurements are faulty, using MSF adaptive Kalman filter helps to obtain better navigation solutions for a guided munition.

Subject Keywords

INS/GPS integration, Loosely coupled, Tightly coupled, Adaptive kalman filters, Guided munitions

URI

https://hdl.handle.net/11511/105630

Collections

Graduate School of Natural and Applied Sciences, Thesis