Research On Grey Correlation Method Of Multi-radar Tracks

In the face of increasingly complex diversified combat environments and international situations,coupled with the diversification of enemy interference methods,if only a single sensor is used to obtain battlefield information,it will inevitably reduce its survivability and put us at a disadvantage.Therefore,the use of a multi-sensor information fusion system to gain insight into the battlefield environment has become an inevitable trend.Compared with a single sensor,it enhances the reliability and credibility of the system,expands the detection range,reduces information ambiguity,and makes the survivability of the system is greatly improved,and the advantages are obvious.There are many functional modules in a multisensor system.Among them,the correlation between track and track is particularly important as the basis of multi-target tracking.Its task is to judge whether the tracks generated by different sensors come from the same target,so as to solve the repeated tracking problem.Based on the above discussion,this paper uses multi-radar as the research background and gray theory as the basis to study the gray track correlation problem.The main work is as follows:1.In order to facilitate the follow-up research,the preprocessing technology in radar data processing is introduced,mainly including time registration and space registration,as well as threshold filtering technology.Secondly,the principle and implementation process of Kalman filter are introduced.Through simulation analysis,it is verified that Kalman filter can reduce the influence of noise and smooth the track.2.Two types of traditional track correlation algorithms are studied,one is based on statistical theory,and the other is based on fuzzy theory.The disadvantages and advantages of the traditional methods are pointed out.Aiming at the problem of poor correlation effect and difficult selection of parameters in membership function under the situation of dense targets and crossing tracks in traditional methods,this paper simplifies the calculation of membership degree,and uses membership degree as input to calculate the gray correlation matrix to judge whether the track is correlated.So,a grey track correlation method based on fuzzy mathematics is proposed.The simulation results show that,compared with the traditional algorithm,this algorithm can maintain good correlation effect in sparse target environment,medium dense target environment and dense target environment,and the superiority of this algorithm is verified in the actual scene.3.In the case of dense targets,cross tracks and maneuvering,this paper applies empirical mode decomposition(EMD)technology in signal time-frequency processing to track correlation,and compares Deng’s general grey correlation degree with B-type grey correlation degree.Because B-type grey correlation degree takes into account the proximity between two track curves and the slope difference,it can improve the correlation effect.In summary,this paper proposes a track correlation method based on EMD and B-type gray correlation degree.The simulation results and the measured data show that the algorithm has better correlation performance in the case of dense target,cross track and maneuvering.