Study On Data Fusion With Applications From Aircraft Multi-information Measurement And Control

Data fusion technology is a new integrated technology, and has a wide applications perspective in both military and civilian. As to spacecraft measurement and control data, Multi-source data fusion is influenced and constrained by many factors. It is significant for the improvements of Chinese spacecraft testing and launching technology. In order to deepen the understanding and practice on data fusion, it is the principle to combine the theoretical analysis and simulation together.In the paper, multi-source data fusion to measurement and control of spacecraft and decision-making technology is explored to solve the problems on the application of data fusion technology. Through simulations and experiments the scheme, theory and technologies are analyzed and validated. This paper introduces some kernel methods on three-level data fusion, which is foundational data fusion technology, target identification technology, feature vector extraction technology and evidence reasoning decision-making technology respectively.To illuminate the main framework, the paper expounds the basic concepts, basic principles and the main features of data fusion, analyzes the principle of function model and structure model, structural features and main algorithms of data fusion. On the background of multi-resource from spacecraft measurement and control, the paper analyzes the structure of data fusion and decision-making system, establishes the research framework of system and expounds the main research contents of every level in the fusion model.With respect to the data from multi-source spacecraft measurement and control, the theory and process algorithm of data association is analyzed and improved. The formation methods of tracking gate and measurement data association algorithms is proposed, which includes the calculation of tracking gate based on number theory method, the process of data association and modified joint probability data association method and so on. The representative of sampling is improved by using the method based on uniform probability sampling, which is used to calculate the size and form of tracking gate. The method is suitable for three-dimensional tracking gate set because of a small amount of calculation and simple process. Modified joint probability data association method divide the intersection region of the tracked target into several independent tracking regions, and then carries on probability calculation of public measurement objects in common space and the probability density of multi-data measured in each correlated gate. The probability density values of multi-measurement data in tracking gate related to every target are weighted by probability. So it gets high precision.Buffer operator and gray association are used to preprocess measurement and control data. It reduces the random error of measurement data primarily. Measurement sequence is fused by using spline filtering and strong tracking filter technology according to variation characteristics of measurement sequence. Fourth-order spline function is used to establish system state equation for spline filtering. It compensates the estimation error and observation error of the system state combining the observation equation, restrains the random observation error of measurement data, smoothes the measurement data. STF is strongly robust to the parameter mismatch of model. It may restrain noise and low initial statistical characteristic, which is of fast convergence. In particular, it has strong track ability to state mutation and is stable in presence of large disturbance.The paper analyses the calculation theory and method of feature layer of data fusion aiming at the measured velocity and position, mutual position range of multi-source spacecraft measurement process, derives a new methods for real-time calculation of spacecraft velocity on the condition of different results in data layer and combines spline filter and number theory method to provide pseudo-random number for the position distribution of the escape and chase when relative distance is closest in order to reflect real-time state distribution precisely.Using the simulation data of the chase and escape, the paper combines spline filter and kalman filter to evaluate the position and velocity of the chase and escape and analyses the estimated result of relative distance vector.Evidence weighting data fusion and adjudgement method are proposed to solve the combination problem of conflict evidence, and validate it by simulation. The evidence decision-making problem in the type identification of spacecraft, the selection of measurement and the assessment of target miss distance is solved. According to the process of D-S evidence reasoning, the paper combines the conception of confidence function and likelihood function, uses evidence weighted fusion restrain evidence conflict. Different weight calculation methods are used in the type identification of spacecraft and the assessment of target miss distance in order to reduce the overall influence due to minor sensors, and to make use of known information furthest and enhance the system's fault tolerance in bad condition.