Analysis And Recogniton Of Signal Parameters In Satellite USB Tt&c Systems

Satellites are key hubs in modern information networks, and they are important means to promote global information realization. A Satellite monitoring and control communication system is the link through which information exchange between a satellite and the earth station or between a satellite and other satellites can be done, it is the technical and functional support for the information acquisition, information transmission and information control functions of a satellite. Unified S-band (USB) satellite measurement and control system is widely use in military and civilian applications. Based on this background, satellite single parameter automatic identification technique is researched, which can be applied to adaptive signal detection and signal reconnaissance receiving for information offense and defense. For this reason, it has important academic, national defense and social significance either from a theoretical point of view or from the application point of view.Combining with Software Radio technique is a new tendency of development of Signal Recognition technique. A satellite signal detection and recognition system that is based on software radio uses open hardware as a universal platform, implementing automatic signal recognition by software that can be updated and reset. Based on this, to ensure the real-time performance, stability and reliability with little priori knowledge has become the focus of attentions of domestic and foreign researchers.Firstly, satellite signal noise reduction techniques are studied in this paper. Signal noise reduction is a preprocessing for parameter identification, its goal is to reduce the impacts of the satellite link noise, to improve the accuracy and reliability of parameter identification. In this paper, the source of the noise in satellite measuring and control link is analyzed, development status of noise control technique is introduced; on this basis, weights of influence of different types of noise are evaluated, the satellite channel is simplified to a channel with Additive White Gaussian Noise(AWGN). In order to reduce the algorithm's dependence on priori knowledge of signal, wavelet coefficients threshold method is adopted as the basic method of signal noise reduction. After a brief introduction of the basic principle and structure of threshold method, several key issues that affect the performance of the algorithm are studied: first, according to the characteristic parameters of wavelet bases, choosing appropriate optimal wavelet base, and by using reconstruction factors the reconstruction ability of the chosen wavelet base is evaluated; second, mean value approximation method is used to reduce the variance of noise, in order to weaken the impact of noise on the selection of threshold value, this can generally reduce the difference between the reconstructed signal and the original signal; in the end, unbiased maximum-likelihood threshold criterion is used for adaptive threshold selection, and a new threshold value function is introduced to do iterative processing on the wavelet coefficients.Secondly, in this paper, some principles and knowledge of particle filters which are related to sub-carrier separation and parameter estimation are introduced, this forms the base of separation and parameter recognition algorithms studied in the following chapters, which includes Bayesian Filter principle, Monte-Carlo Method and basic idea of Particle Filters, in the end, the degeneration problem in particle filters is introduced and the structure of basic particle filter algorithm is summarized.Thirdly, blind recognition of USB satellite measuring and control sub-carrier is studied. The Blind Recognition of satellite sub-carrier consists of two parts, namely Separation and Parameter Estimation. In this paper, the idea of particle filters is introduced, and a sub-carrier signal blind recognition algorithm based on particle filters is developed. The blind recognition problem can be transformed into a joint-estimation problem of unknown parameters and information symbols, the single channel underdetermined blind source separation and parameter estimation can be done at the same time. In the application of particle filters, in order to overcome the degeneration problem, taken into consideration of the characteristics of the satellite signal state space, the particle filter blind recognition algorithm can be improved in two ways, using auxiliary variable particle filter algorithm to introduce new observation values into the importance function, at the same time, during the re-sampling process, a particle global optimization algorithm based on particle group optimization is presented, which will improve the utilization efficiency of particles. At the end of this chapter, measuring and control sub-carrier code rate identification algorithms are studied. Wavelets transform algorithms, which are not sensitive to SNR and don't require priori knowledge, are used for code rate blind estimation. In order to improve the performance of wavelets transform, a rough-and-precise-integrated two-step estimation algorithm is designed, it first uses fast algorithms to give a rough estimation of code rate, choosing wavelet scale according to the result of rough estimation, and then it can do precise estimation on the code rate. Simulation result shows: the performance of the algorithm shown in this paper is better than the performance of single-scale algorithms.Lastly, a TT&C sub-carrier signals recognition test system is emplyed and a simplified TT&C sub-carrier signals recognition algorithm is transferred to the hardware board. The performance on the hardware board is deeply investigated using the signal source generator CORTEX. Furthermore, the recognition results of an in-orbit model satellite are given using TT&C sub-carrier signals recognition test system and remote sensing and controlling earth station in Harbin Institute of Technology, which proves the engineering validity of the algorithm.