The Research On Technologies Of Identification And Parameter Estimation Of TT&C Signals

Aerospace communication system is an important unit of aerospace, its main task is to track the state of the aircraft flight, control the command transmission of the movement, transfer data of the working state. In order to complete the above tasks, the receiving equipment needs to detect and identify signal effectively, which has become an important research topic in comumunication field. Meanwhile, signal’s identification and parameter estimation techniques is very important to receiver’s intelligentialize, software based and digitize development trend. Due to the complicated electromagnetic environment and the diversity of signal modulation, the traditional detection methods are difficult to adapt to this situation. Under this background, this thesis make a deep research.This thesis mainly aims at two kinds of co-signal: Unified S-Band(USB) TT&C signal and spread spectrum TT&C signal’s identification and parameter estimation research. Firstly, this thesis proposed Fast Fourier Transform(FFT) to detect the USB signal according to the operating principle and signal characteristic of USB signal. There’s code rate characteristic in spread spectrum signal, so here using the improved time delay multiplication algorithm to detect the spread spectrum signal. To verified the improved time delay multiplication algorithm’s accuracy, this thesis maked simulation combine with time-frequency analysis--Wigner-Ville transform. The results showed that using this algorithm can accurately identify the two signals. As for parameter estimation, this thesis use Back-Propagation(BP) Neural Networks to recognize typical modulation types in USB TT&C system with 7 characteristic parameters,including 2FSK, 4FSK, BPSK,QPSK, MSK, PM, CW. The Simulation results indicated that the accuracy of BPSK, PM, CW have obvious improvement. At last, this thesis using the second calculation of power spread after computing the power spectrum of the received signals at the first step to estimate the periodic of PN Sequence in DS-SS signal. The simulation results showed that the proposed method can realize the periodic estimation of PN sequence under lower SNR accurately.The improved time delay multiplication algorithm proposed in this thesis can not only detect spectrum signal, it also can identify two kinds of commonly used spread spectrum signal types: direct sequence spread spectrum signal and direct sequence/frequency hopping spread spectrum signal by adjusting the different delay time. The simulation results showed that the accuracy can reach above 95%. Combine with the above studied algorithms, this thesis designed a detection and identification module in simulink. This module can accurately detect and identify USB TT&C signal and spread spectrum TT&C signal, besides the module has been applied to actual project. The signal identification and parameter estimation techniques studied in this thesis provided a feasible scheme for blind signal identification, it also has certain reference value for practical engineering application.