Remote Air-to-air Missile Combined Guidance Information Fusion Technology Research

In the21st century, the remote air-to-air missiles employed the traditional singlesensor-guided mode seeker has been very difficult to meet the requirements foraccurate target detection and tracking in high-tech information and modern war.Combined guidance technology can take full advantage of multi-sensor to improvetarget identification, capture, and tracking ability and attack target precisely.Information fusion technology is one of the key technologies of radar and infraredseeker combined guidance. In this paper, data pre-processing, data fusion and dataassociation techniques are researched.In data preprocessing, the time and space registration of two different sensors inradar and infrared measurement system and method for excluding outliers areresearched. The time and space alignment arithmetic are adopted to keep pace with thetime series of the two sensors. The Wright guidelines and template convolution methodcan effectively discriminate and eliminate outlier among the measurements from radarand infrared sensors. The method can improve the tracking accuracy of radar andinfrared measurement system.In data fusion, when the combined guidance seeker information fusion, extendedKalman filter method is adopted to deal with the linearization of nonlinear system tosimplifies the system. But EKF method easily leads to tracking filter divergence whenthe radar and IR seeker meet strongly nonlinear. In order to solve the problem ofnonlinear estimation in radar and infrared measurement system, the fusion algorithmbased on UKF radar/IR composite guidance is proposed, the nonlinear filteringunscented Kalman filter is introduced based on weighted track fusion algorithm. Thesimulation results show that the algorithm can effectively avoid filter divergence indealing with the non-linear observing system and owns better convergence andintegration of precision.The complexity of the maneuvering target tracking environment is considered and the IMM algorithm is introduced based on UKF radar/IR combined guidance fusionalgorithm. The simulation results show that the algorithm can enhance theperformance of complex guidance system for maneuvering target tracking.In data association, the weighted track association and the amendment toweighted track association are analyzed. Existent problem about the probabilistic dataassociation algorithm and the joint probability data association algorithm is presentedthat the target filter estimates serious deviate from the true target value due tointerference in a cluttered environment. Based on the combination of new interest ratefrom tracking filter in data association algorithm, an online adaptive weightedcorrection is proposed. The simulation results show that the correction algorithm canmake the filtering estimate approximate the true target value.