A Study Of Netted Radar Information Fusion And Deception Jamming Technology Research

With the application of the new technology and novel methods in weapons, modern radar’s survival space is becoming more and more limited in complex environment, and radar system is facing more new threat. By building up a network consisting of radars with different parameters, not only the performance of the radar system is improved, but also the living space of radar system is expanded. Compared with the traditional mono-radar system, netted radar system has a better performance in early warning, target detection, target tracking and anti-interference, etc. Therefore, netted radar information fusion and confrontation technologies are hotspot in both radar signal processing and electronic warfare fields. This thesis focuses on the moving target model classification of the netted radar, data preprocessing, tracking filter algorithm, associated wave gate selection and data fusion algorithm to improve the detection efficiency of the netted radar.Due to the increasingly widespread use of netted radar system, the study on interference technology of network is the key research direction in the field of electronic warfare nowadays. Based on the research on the processing of radar network data and analysis of the disadvantages of the netted radar data processing algorithm, the concepts of deception jamming and the mathematical model are built up. Meanwhile, an effective method of false target deception and the corresponding algorithm procedures are studied. The problem of generating stable deception false track in netted radar system under complex electronic countermeasure environment is solved. Then the real target can be protected by tempting the netted radar system to make false judgments and wrong decisions. The specific content of this thesis is organized as follows:(1) A target tracking filter algorithm is studied, and the performances of different tracking filter algorithms are comparatively analyzed. Firstly, a mathematical model of different motion conditions is built. Secondly, methods for netted radar data preprocessing are discussed. Based on the analysis, the algorithms, including linear Kalman filtering algorithm, extended Kalman filtering algorithm and unscented Kalman filtering algorithm, are detailed in theory. And then the simulation results are given. Finally, the performances of different algorithms are compared to service for thefollowing netted radar observation data preprocessing, wave gate selection and data fusion.(2) By concentrating on the netted radar data fusion technology, the performances of different data fusion algorithms and the effect of the size of associated wave gate on data fusion are analyzed. A detailed discussion on the effects of the type and size of the associated wave gate on data fusion are firstly given, and the importance of the selection of the gate size is verified by simulation. Then, different data fusion algorithms are analyzed in detail, and the corresponding application condition is given for each of them. The improvement of the performance of the netted radar by applying data fusion algorithm is verified in the final of this section. The performances of different fusion algorithms are also discussed.(3) Based on the analysis of deception jamming of false track against netted radar, two methods, including deception jamming on range and deception jamming on both range and angle, are discussed. Multiple jammers are utilized to realize the range deception jamming based on the mathematical model and homologous hypothesis theory. Single jammer is used to generate a stable false track to realize the deception jamming on range and angle. The effectiveness of both the two methods are verified by simulation results.