Research On The Overlapped Signals Separation Method Of Space-based ADS-B

Automatic Dependent Surveillance-Broadcast(ADS-B)is an important technology for air traffic management.In recent years,as aviation activities have become more frequent and intensive,ground-based ADS-B has gradually exposed the problem of insufficient coverage,especially in areas such as oceans,polar regions,and deserts.For this reason,the ADS-B payload was chosen to be carried on the satellite,and the high-distance characteristics of the satellite were used to make up for the defects of the ground-based ADS-B.However,because ADS-B signals are broadcast randomly,a large number of aircraft may transmit ADS-B signals to satellites in the same frequency band at the same time,which may cause aliasing between signals,which seriously affects the monitoring capabilities of the system.In response to the above problems,this thesis focuses on the separation of ADS-B overlapping signals.The main work of the full thesis is as follows:(1)A method for measuring total ionospheric electron content based on space-based ADS-B is proposed.The traditional method for measuring the total electron content of the ionosphere requires the deployment of related base stations on the ground,which will consume a lot of manpower and material resources,and the base stations are difficult to deploy in areas such as oceans and deserts.To this end,a method for measuring the total ionospheric electron content based on satellite ADS-B data information and satellite ephemeris information is proposed.This method only needs to use the existing ADS-B system,which can greatly increase the data update rate.According to the total ionospheric electron content,the transmission delay and phase shift of the ADS-B signal in the ionospheric transmission process can be calculated,and the time and phase parameters in the ADS-B overlapping signals model can be subsequently corrected for error.(2)Established an evaluation model for the ADS-B system.In order to analyze the impact of co-frequency interference of ADS-B signals on the performance of the ADS-B system under current airspace traffic,based on the poisson distribution model,a satellite monitoring capacity evaluation model of the ADS-B system is derived.The simulation experiment proves that the successful separation of ADS-B signals under current airspace traffic greatly improves the performance of ADS-B system.(3)A method for detecting overlapping positions of ADS-B signals based on multi-stage Wiener filters is proposed.Due to the low signal-to-noise ratio on the satellite,there is no obvious distinction between the singular value and the noise value in the traditional singular value decomposition method,and it is difficult to correctly estimate the overlapping position of the ADS-B signals.To solve this problem,an orthogonal projection method based on multi-stage Wiener filters is proposed to detect the overlapping position of ADS-B signals.The method first uses the cross-correlation between the received signals of different array elements to construct a spatial matched filter,and then uses a multi-stage Wiener filter to filter the received signals to obtain the desired signals,and finally to each item in the desired signals carry out the autocorrelation operation to obtain the vector used for the estimation of the number of information sources.Compared with the traditional singular value decomposition method,this method reduces the computational complexity and improves the detection accuracy under the condition of low signal-to-noise ratio.(4)An ADS-B overlapping signals separation algorithm based on compressed sensing is proposed.Aiming at the problem of under-determined blind source separation in the single-channel separation of ADS-B overlapping signals,based on the internal relationship between the ADS-B overlapping signals single-channel separation model and the compressed sensing model,a single-channel separation model of ADS-B overlapping signals based on compressed sensing is established.Using the signal reconstruction idea in the compressed sensing theory to successfully realize the signals separation.Compared with the traditional algorithm,the separation performance of this algorithm is further improved,and the requirement for the sampling rate is not high,which has potential value for on-board applications.