2020IEEE AccessOpen access

A Framework of Multipath Mitigation With Joint Multipath-Doppler Diversity for RF Relative Measurement

Weiqing Mu, Zijie Wang, Lantu Guo, Yanan Liu

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Abstract

Radio frequency (RF) relative measurement provides an effective means of communication and autonomous navigation for the spacecraft formation flying. Multipath and Doppler are two main factors that affect the accuracy of RF relative measurement. In this study, a framework that exploits joint multipath-Doppler diversity is proposed to reduce multipath errors and improve the measurement accuracy. The proposed framework first utilizes an Extended Kalman Filter (EKF) estimator to estimate the parameters of Doppler and multipath. Different from existing research, the proposed framework reconstructs the received signal according to the estimated parameters, so as to mitigate multipath signals and enhance the direct signal. Numerical results demonstrate that the framework is suitable for both multipath and multipath-Doppler scenarios, and has a significant performance improvement over existing multipath mitigation methods.

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What this paper is about

Radio frequency (RF) relative measurement provides an effective means of communication and autonomous navigation for the spacecraft formation flying. Multipath and Doppler are two main factors that affect the accuracy of RF relative measurement. In this study, a framework that exploits joint multipath-Doppler diversity is proposed to reduce multipath errors and improve the measurement accuracy. The proposed framework first utilizes an Extended Kalman Filter (EKF) estimator to estimate the parameters of Doppler and multipath. Different from existing research, the proposed framework reconstructs the received signal according to the estimated parameters, so as to mitigate multipath signals and enhance the direct signal. Numerical results demonstrate that the framework is suitable for both multipath and multipath-Doppler scenarios, and has a significant performance improvement over existing multipath mitigation methods.

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Available abstract

Radio frequency (RF) relative measurement provides an effective means of communication and autonomous navigation for the spacecraft formation flying. Multipath and Doppler are two main factors that affect the accuracy of RF relative measurement. In this study, a framework that exploits joint multipath-Doppler diversity is proposed to reduce multipath errors and improve the measurement accuracy. The proposed framework first utilizes an Extended Kalman Filter (EKF) estimator to estimate the parameters of Doppler and multipath. Different from existing research, the proposed framework reconstructs the received signal according to the estimated parameters, so as to mitigate multipath signals and enhance the direct signal. Numerical results demonstrate that the framework is suitable for both multipath and multipath-Doppler scenarios, and has a significant performance improvement over existing multipath mitigation methods.

Key concepts: Multipath propagation, Doppler effect, Computer science, Delay spread, Multipath mitigation, Estimator, Diversity scheme, Electronic engineering

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