Research On Temporal And Spatial Alignments Of A Radar Network

Temporal and spatial alignments are the most important part of the data process in the radar network. The result of temporal and spatial alignments directly influences the precision of data fusion, and the performance of the radar network. Therefore, it is necessary to do research on the temporal and spatial alignments for the radar network building.This dissertation systematically reviews the development history and research status of the radar network, deeply analyzes the model and structure of data processing system of the radar network. Combining H∞filtering theory and homogeneous coordinate, it studies on temporal and spatial alignments. The main results of this dissertation are:1. This dissertation analyzes the main factors which affect the spatial alignment error in ECEF(Earth-Centered Earth-Fixed coordinate), and then an error model is established with homogeneous coordinate. Through analysis of the model, the conclusions are reached. The spatial alignment error caused by the error of platform positions is approximately equal to the error of platform positions. And the same deck deformation,fixing error,attitude error have the same effect on the spatial alignment error. Numeric examples validate the above-mentioned conclusions.2. This dissertation introduces the main concepts and methods of the temporal alignment and analyzes their advantages and disadvantages. Then this paper introduces arithmetic model for the temporal alignment, proposes the algorithm of the temporal alignment based on H∞filtering theory. Compared to the Kalman filter, the H∞filter is independent to the state noise and observation noise,that means it is only necessary to assume that the energy of the noise is limitary instead of the statistical characteristics, it is more rational. In addition, the structure of the H∞filter is dependent to the state combination while the Kalman filter estimates the linear combination of the states through the linear combination of state estimates. The difference between the two concepts implies that the H∞filter has more advantages. This dissertation designs 7 numeric examples which testify the validity and advantages of the proposed algorithm.