Markov Channel Modeling for Time-Varying Loran Singal with Joint Amplitude and Phase
- Resource Type
- Conference
- Authors
- Ma, Hongyu; Du, Yongxing; Zhao, Zhenzhu; Xi, Xiaoli
- Source
- 2023 International Applied Computational Electromagnetics Society Symposium (ACES-China) Applied Computational Electromagnetics Society Symposium (ACES-China), 2023 International. :1-2 Aug, 2023
- Subject
- Engineering Profession
Fields, Waves and Electromagnetics
Wireless communication
Fading channels
Computational modeling
Radio navigation
Markov processes
Probability
Computational electromagnetics
Loran
Finite-state Markov Chain
Channel Modeling
Statistical Model
- Language
Channel modeling helps developers understand the wireless channel environment and can reduce expenses when developing new technologies. We propose a joint amplitude and phase modeling method for loran signals. We establish a realtime monitoring system to obtain real signal delay and fading data. The statistical properties of the a priori data are reproduced by dividing the data states and using the Markov chain method. The results with the first-order statistical properties show that the algorithm has a good probability density distribution fit and integral probability density distribution.