Research On TDOA/FDOA Parameters Estimation For Satellite Interference Localization

With the extensive use of satellite communications, satellite incidents of interference have been increasing. Satellite interference localization has become a new and important content of the current anti-jamming satellite communications system, while the key to the satellite interference localization accuracy is the parameter estimation of Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA) of the wireless signal. At present, the most commonly used satellite interference localization method is the cross-ambiguity function (CAF) based on the correlation principle. Due to the computing intensity and time consuming searching process of the CAF algorithms, it can not meet the need of quick and accurate satellite interference localization. Thus, the searching of faster and more accurate localization parameter estimation algorithm has become the core of the interference positioning problem.Based on the background of the double satellite localization system, the thesis studied a number of issues of satellite interference localization parameter estimation from TDOA parameter estimation, FDOA parameter estimation and TDOA/FDOA joint parameter estimation respectively.In TDOA parameter estimation, Generalized cross correlation method and Bispectrum methods are classical estimation methods. But with the increase of noise correlation and the SNR difference of the two received signals becoming larger, the estimation accuracy of the two methods will be greatly reduced, or even come to wrong results. In order to avoid the above problems, the paper proposes a new TDOA parameter estimation method based on wavelet and wavelet packet. The new method is able to achieve better estimation performance, with the help of wavelet de-noising under the environment of low SNR under certain satellite ephemeris, the estimation accuracy is also improved.In FDOA parameter estimation, in view of classical FDOA parameter estimation method-non-parametric FDOA estimation is extremely vulnerable to noise impact, in order to suppress noise and improve the estimation accuracy, the paper analyzes FDOA parameter estimation method based on high-order cumulant.In TDOA/FDOA joint parameter estimation, due to the computing intensity and time consuming searching process of the classical TDOA/FDOA joint parameter estimation, including the cross-ambiguity function based on SOS and the cross-ambiguity function based on HOS, the thesis analyzes two-dimensional separation algorithm based on SOS and two-dimensional separation algorithm based on HOS, which transforms CAF from two-dimensional search algorithm into two one-dimensional parameter estimation problem.The thesis simulates the above algorithms. Finally, a brief summary of the dissertation is given. The suggestion for future research related to the location parameter estimation is put forward.