Parameters Design Method of Kalman Filter-Based Tracking Loop in GNSS/INS Deep Integration
This paper proposes a parameter design method of a second-order KF tracking loop in the deep integration architecture according to inertial sensor errors and receiver oscillator errors. Firstly, the effects of INS aiding on the state-driven and measuremen
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Abstract This paper proposes a parameter design method of a second-order KF tracking loop in the deep integration architecture according to inertial sensor errors and receiver oscillator errors. Firstly, the effects of INS aiding on the state-driven and measurement noises of KF tracking loop are analyzed. Secondly, through coordinate frame transformation and LOS projection, the variances of the two accelerometer noises in the Earth-centered Earth-fixed (ECEF) frame and LOS direction are obtained. Lastly, the performance of KF-based tracking loop in the deep integration architecture is tested through the data collected from the GNSS/INS hardware simulator, and is compared with the conventional tracking loop in the deep integration architecture. The test results show that the proposed parameter design method makes the channel KF in the deep integration share the comparable performance to the conventional tracking loop in the deep integration. The test results illustrate the correctness and effectiveness of the parameter design method proposed in the paper. Since each parameter is set according to its physical meaning in the paper, the empirical and tentative trials in the parameter optimization process are avoided. Keywords Kalman filter noise
Parameter design State driven noise Accelerometer
B. Li (&) W. Guo X. Niu J. Liu GNSS Reasearch Center, Wuhan University, Wuhan, China e-mail: [email protected] N.I. Ziedan Computer and Systems Engineering Department, Zagazig University, Zagazig, Egypt e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2017 J. Sun et al. (eds.), China Satellite Navigation Conference (CSNC) 2017 Proceedings: Volume I, Lecture Notes in Electrical Engineering 437, DOI 10.1007/978-981-10-4588-2_79
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1 Introduction In the GNSS/INS deep integration architecture, the inertial navigation system (INS) provides Doppler aiding information for GNSS receiver tracking loops, which substantially improve receiver’s tracking and navigation performance. Therefore, GNSS/INS deep integration technology has been widely used under various challenging environments, such as high dynamics, weak signals and anti-interference. For conventional carrier phase tracking loops, parameters including loop order, bandwidth and coherent integration time need to be designed. In conventional receivers without INS aiding, the effects of noise performance and dynamic response should be taken into consideration in the tracking loop design [1]. While in the deep integration architecture, the INS aiding guarantees the dynamic response of the tracking loop, but brings about the INS aiding error which influences the loop tracking performance and should be considered consequently [2]. For a KF-based tracking loop, measurement noise covariance matrix R, state-driven noise covariance matrix Q and state estimation error covariance matrix P should be designed. The parameter design method of KF-based tracking loop without INS aiding has been widely investigated. In Won [3], the measurement noi
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