Signal Processing Technology In The Radio Monitoring Study

Radio monitoring is to monitor, measure, identify and locate the signals. One of its most important functions is to identify and locate the interfere signals. Modulation identification is required to identify the modulation format and modulation parameters in the complicated signal environment with noise, and to provide reference for further analysis and processing. With the development of communication technology, the spatial signals are more and more complicated and dense. It makes the modulation identification more difficult. As a result, there are more demands for the research of modulation identification. Time difference of arrival (TDOA) location system, namely dual-curve location system, is an important passive location method. Using the time difference of signals arrived to three or more different stations, we can determine the position of the target wanted to be located. Because of its high precision and fast location advantages, it is widely used in practice. But its precision depends on time delay estimation, so researching fast and exact time delay estimation method become a hot topic in TDOA location system. The main works are as follows:First, modulation identification and demodulation methods are studied. The pattern recogniser based on instantaneous characteristic paraments is analysed. Then a method to identify the modulation pattern was obtained. Simulation showed that it is feasible. Moreover, five familiar kinds of different modulation signals are demodulated using corresponding algorithms.Secondly, time delay estimation method using correlation function is studied. The cyclostationarity of signal is analysed and a model for TDOA is introduced. ZZLB of this method is analysed and a simulation of three paraments that affect the precision is completed. Furthermore, several major time delay estimation algorithms, namely standard cross-correlation, general corss-correlation (GCC) and cyclic cross-corelation (CCC), are analyzed in detail, and their characters is obtained by simulations.Thirdly, none line of sight (NLOS) recognition and error mitigation in TDOA are studied. Several major recongnition algorithms are analyzed in detail, including Wylie identification method, range identification method and remanet identification method. The total-deflection method using Kalman filtering was imported to mitigate the NLOS error in TDOA. Improvements were made to avoid the non-convergence problem in Kalman filtering, and then obtained a new method. Simulations showed that this new method could significantly mitigate NLOS error in TDOA.Finally, an initial outfield tri-station TDOA location experiment is done, the experiment scheme and method of data processing are introduced, and then the results of data processing are analyzed.