US-12618941-B2 - Method, system and storage medium for model predictive automatic gain control of satellite transponder under additive white gaussian noise jamming

Abstract

The present disclosure provides a method for model predictive automatic gain control under additive white Gaussian noise jamming. The method includes predicting a plurality of consecutive signal values by an autoregressive integrated moving average model; calculating a signal average value of the plurality of consecutive signal values; calculating a gain control value using the signal average value of the plurality of consecutive signal values; if the gain control value is greater than a maximum control capability of a AGC processor, using the gain control value as a desired gain control value; or if the gain control value is equal to or less than the maximum control capability, using a minimum difference between an estimated amplitude and each of reference amplitudes in the LUT as the desired gain control value; and calculating a new AGC gain for a current time step according to the desired gain control value.

Inventors

• Yajie BAO
• Peng Cheng
• Khanh Pham
• Erik Blasch
• Dan Shen
• Xin Tian
• Genshe Chen

Assignees

• Intelligent Fusion Technology, Inc.

Dates

Publication Date

20260505

Application Date

20230915

Claims (20)

1. 1 . A method for model predictive automatic gain control (AGC) of a satellite transponder under additive white Gaussian noise (AWGN) jamming, wherein the satellite transponder includes an AGC processor, the method comprising: predicting a plurality of consecutive signal values by an autoregressive integrated moving average (ARIMA) model using data collected by an antenna receiver in the satellite transponder; calculating a signal average value of the plurality of consecutive signal values; calculating a gain control value using the signal average value of the plurality of consecutive signal values through a model predictive controller; if the gain control value is greater than a maximum control capability of the AGC processor, using the gain control value as a desired gain control value, wherein the maximum control capability is predefined in a lookup table (LUT); or if the gain control value is equal to or less than the maximum control capability, using a minimum difference between an estimated amplitude and each of reference amplitudes in the LUT as the desired gain control value; and calculating a new AGC gain for a current time step according to the desired gain control value and a corresponding AGC gain for a previous time step.
2. 2 . The method according to claim 1 , before predicting the plurality of consecutive signal values by the ARIMA model using the data collected by the antenna receiver in the satellite transponder, further including: evaluating accuracy of the ARIMA model by computing mean squared differences between the plurality of consecutive signal values predicted by the ARIMA model and corresponding real signal values.
3. 3 . The method according to claim 2 , after evaluating the accuracy of the ARIMA model, further including: if the ARIMA model is accurate, predicting the plurality of consecutive signal values by the ARIMA model; and if the ARIMA model is not accurate, returning to collect new data by the antenna receiver in the satellite transponder.
4. 4 . The method according to claim 2 , before evaluating the accuracy of the ARIMA model, further including: fitting the ARIMA model using the data collected by the antenna receiver in the satellite transponder.
5. 5 . The method according to claim 1 , after calculating the new AGC gain for the current time step according to the desired gain control value and the corresponding AGC gain for the previous time step, further including: applying the new AGC gain for the current time step and evaluating performance of the model predictive AGC.
6. 6 . The method according to claim 5 , further including: if the performance of the model predictive AGC is acceptable, keeping using the model predictive AGC to maintain a signal amplitude at a specified level; and if the performance of the model predictive automatic gain control (AGC) is not acceptable, returning to collect new data by the antenna receiver in the satellite transponder.
7. 7 . The method according to claim 1 , wherein: after calculating the new AGC gain for the current time step, the new AGC gain is processed through a gain control amplifier (GCA).
8. 8 . A system, comprising: a memory, configured to store program instructions for performing a method for model predictive automatic gain control (AGC) of a satellite transponder under additive white Gaussian noise (AWGN) jamming, wherein the satellite transponder includes an AGC processor; and a processor, coupled with the memory and, when executing the program instructions, configured for: predicting a plurality of consecutive signal values by an autoregressive integrated moving average (ARIMA) model using data collected by an antenna receiver in the satellite transponder; calculating a signal average value of the plurality of consecutive signal values; calculating a gain control value using the signal average value of the plurality of consecutive signal values through a model predictive controller; if the gain control value is greater than a maximum control capability of the AGC, using the gain control value as a desired gain control value, wherein the maximum control capability is predefined in a lookup table (LUT); or if the gain control value is equal to or less than the maximum control capability, using a minimum difference between an estimated amplitude and each of reference amplitudes in the LUT as the desired gain control value; and calculating a new AGC gain for a current time step according to the desired gain control value and a corresponding AGC gain for a previous time step.
9. 9 . The system according to claim 8 , before predicting the plurality of consecutive signal values by the ARIMA model using the data collected by the antenna receiver in the satellite transponder, the processor is further configured to: evaluate accuracy of the ARIMA model by computing mean squared differences between the plurality of consecutive signal values predicted by the ARIMA model and corresponding real signal values.
10. 10 . The system according to claim 9 , after evaluating the accuracy of the ARIMA model, the processor is further configured to: if the ARIMA model is accurate, predict the plurality of consecutive signal values by the ARIMA model; and if the ARIMA model is not accurate, return to collect new data by the antenna receiver in the satellite transponder.
11. 11 . The system according to claim 9 , before evaluating the accuracy of the ARIMA model, the processor is further configured to: fit the ARIMA model using the data collected by the antenna receiver in the satellite transponder.
12. 12 . The system according to claim 8 , after calculating the new AGC gain for the current time step according to the desired gain control value and the corresponding AGC gain for the previous time step, the processor is further configured to: apply the new AGC gain for the current time step and evaluate performance of the model predictive AGC.
13. 13 . The system according to claim 12 , the processor is further configured to: if the performance of the model predictive AGC is acceptable, keep using the model predictive AGC to maintain a signal amplitude at a specified level; and if the performance of the model predictive automatic gain control (AGC) is not acceptable, return to collect new data by the antenna receiver in the satellite transponder.
14. 14 . The system according to claim 8 , wherein: after calculating the new AGC gain for the current time step, the new AGC gain is processed through a gain control amplifier (GCA).
15. 15 . A non-transitory computer-readable storage medium, containing program instructions for, when being executed by a processor, performing a method for model predictive automatic gain control (AGC) of a satellite transponder under additive white Gaussian noise (AWGN) jamming, wherein the satellite transponder includes an AGC processor, the method comprising: predicting a plurality of consecutive signal values by an autoregressive integrated moving average (ARIMA) model using data collected by an antenna receiver in the satellite transponder; calculating a signal average value of the plurality of consecutive signal values; calculating a gain control value using the signal average value of the plurality of consecutive signal values through a model predictive controller; if the gain control value is greater than a maximum control capability of the AGC, using the gain control value as a desired gain control value, wherein the maximum control capability is predefined in a lookup table (LUT); or if the gain control value is equal to or less than the maximum control capability, using a minimum difference between an estimated amplitude and each of reference amplitudes in the LUT as the desired gain control value; and calculating a new AGC gain for a current time step according to the desired gain control value and a corresponding AGC gain for a previous time step.
16. 16 . The storage medium according to claim 15 , before predicting the plurality of consecutive signal values by the ARIMA model using the data collected by the antenna receiver in the satellite transponder, the processor is further configured to: evaluate accuracy of the ARIMA model by computing mean squared differences between the plurality of consecutive signal values predicted by the ARIMA model and corresponding real signal values.
17. 17 . The storage medium according to claim 16 , after evaluating the accuracy of the ARIMA model, the processor is further configured to: if the ARIMA model is accurate, predict the plurality of consecutive signal values by the ARIMA model; and if the ARIMA model is not accurate, return to collect new data by the antenna receiver in the satellite transponder.
18. 18 . The storage medium according to claim 16 , before evaluating the accuracy of the ARIMA model, the processor is further configured to: fit the ARIMA model using the data collected by the antenna receiver in the satellite transponder.
19. 19 . The storage medium according to claim 15 , after calculating the new AGC gain for the current time step according to the desired gain control value and the corresponding AGC gain for the previous time step, the processor is further configured to: apply the new AGC gain for the current time step and evaluate performance of the model predictive AGC.
20. 20 . The storage medium according to claim 19 , the processor is further configured to: if the performance of the model predictive AGC is acceptable, keep using the model predictive AGC to maintain a signal amplitude at a specified level; and if the performance of the model predictive automatic gain control (AGC) is not acceptable, return to collect new data by the antenna receiver in the satellite transponder.

Description

GOVERNMENT RIGHTS The present disclosure was made with Government support under Contract No. FA9453-21-C-0556, awarded by the United States Air Force Research Laboratory. The U.S. Government has certain rights in the present disclosure. FIELD OF THE DISCLOSURE The present disclosure generally relates to the field of satellite communication technology and, more particularly, relates to a method, a system and a storage medium for model predictive automatic gain control of a satellite transponder under additive white Gaussian noise (AWGN) jamming. BACKGROUND Automatic gain control (AGC) is a closed-loop-feedback regulating circuit used in the satellite transponder to maintain a suitable signal amplitude at output, despite signal amplitude variations at input. The control performance of AGC affects the efficiency of satellite communications (SATCOM) by playing a part in both the quantization error of the analog-to-digital converter (ADC) and the signal distortion of the high-power amplifier (HPA). Satellite jamming has been considered a growing threat; and different approaches for satellite communication jamming mitigation such as game theory, frequency hopping, wave selection, power allocation, systems-level analysis and the like have been developed. The anti-jamming approaches may increase the variations of the signal amplitude. For frequency hopping, the signal carrier frequency rapidly hops among various distinct frequencies occupying a wide spectral band, which may add uncertainty of amplitude fluctuations caused by jamming signals to channel noise. However, existing AGC schemes determine the gain control values based on current signal amplitude tracking errors, which may not respond fast enough to rapid signal amplitude variations. Therefore, there is a need to provide a transponder's front-end AGC that is capable of fast response to rapid amplitude variations. BRIEF SUMMARY OF THE DISCLOSURE One aspect of the present disclosure provides a method for model predictive automatic gain control of a satellite transponder under additive white Gaussian noise jamming. The method includes predicting a plurality of consecutive signal values by an autoregressive integrated moving average (ARIMA) model using data collected by an antenna receiver in the satellite transponder; calculating a signal average value of the plurality of consecutive signal values; calculating a gain control value using the signal average value of the plurality of consecutive signal values through a model predictive controller; if the gain control value is greater than a maximum control capability of the AGC, using the gain control value as a desired gain control value, where the maximum control capability is predefined in a lookup table (LUT); or if the gain control value is equal to or less than the maximum control capability, using a minimum difference between an estimated amplitude and each of reference amplitudes in the LUT as the desired gain control value; and calculating a new AGC gain for a current time step according to the desired gain control value and a corresponding AGC gain for a previous time step. Another aspect of the present disclosure provides a system. The system includes a memory, configured to store program instructions for performing a method for model predictive automatic gain control of a satellite transponder under additive white Gaussian noise jamming; and a processor, coupled with the memory and, when executing the program instructions, configured for: predicting a plurality of consecutive signal values by an autoregressive integrated moving average (ARIMA) model using data collected by an antenna receiver in the satellite transponder; calculating a signal average value of the plurality of consecutive signal values; calculating a gain control value using the signal average value of the plurality of consecutive signal values through a model predictive controller; if the gain control value is greater than a maximum control capability of the AGC, using the gain control value as a desired gain control value, where the maximum control capability is predefined in a lookup table (LUT); or if the gain control value is equal to or less than the maximum control capability, using a minimum difference between an estimated amplitude and each of reference amplitudes in the LUT as the desired gain control value; and calculating a new AGC gain for a current time step according to the desired gain control value and a corresponding AGC gain for a previous time step. Another aspect of the present disclosure provides a non-transitory computer-readable storage medium, containing program instructions for, when being executed by a processor, performing a method for model predictive automatic gain control of a satellite transponder under additive white Gaussian noise jamming. The method includes predicting a plurality of consecutive signal values by an autoregressive integrated moving average (ARIMA) model using data collected by an anten