RFI modeling and prediction approach for SATOP applications: RFI prediction models

Tien M. Nguyen; Hien T. Tran; Zhonghai Wang; Amanda Coons; Charles C. Nguyen; Steven A. Lane; Khanh D. Pham; Genshe Chen; Gang Wang

doi:10.1117/12.2223518

13 May 2016 RFI modeling and prediction approach for SATOP applications: RFI prediction models

Tien M. Nguyen, Hien T. Tran, Zhonghai Wang, Amanda Coons, Charles C. Nguyen, Steven A. Lane, Khanh D. Pham, Genshe Chen, Gang Wang

Author Affiliations +

Proceedings Volume 9838, Sensors and Systems for Space Applications IX; 98380I (2016) https://doi.org/10.1117/12.2223518
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

Abstract

This paper describes a technical approach for the development of RFI prediction models using carrier synchronization loop when calculating Bit or Carrier SNR degradation due to interferences for (i) detecting narrow-band and wideband RFI signals, and (ii) estimating and predicting the behavior of the RFI signals. The paper presents analytical and simulation models and provides both analytical and simulation results on the performance of USB (Unified S-Band) waveforms in the presence of narrow-band and wideband RFI signals. The models presented in this paper will allow the future USB command systems to detect the RFI presence, estimate the RFI characteristics and predict the RFI behavior in real-time for accurate assessment of the impacts of RFI on the command Bit Error Rate (BER) performance. The command BER degradation model presented in this paper also allows the ground system operator to estimate the optimum transmitted SNR to maintain a required command BER level in the presence of both friendly and un-friendly RFI sources.

Citation Download Citation

Tien M. Nguyen, Hien T. Tran, Zhonghai Wang, Amanda Coons, Charles C. Nguyen, Steven A. Lane, Khanh D. Pham, Genshe Chen, and Gang Wang "RFI modeling and prediction approach for SATOP applications: RFI prediction models", Proc. SPIE 9838, Sensors and Systems for Space Applications IX, 98380I (13 May 2016); https://doi.org/10.1117/12.2223518

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