New computing method of weighted coefficients for tracking a maneuvering target using PDAF in the pr

来源 :Journal of Systems Engineering and Electronics | 被引量 : 0次 | 上传用户:nayitian1046906153
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To avoid or reduce the influence of unpredictable motion mode on data association,a new computing method of weighted coefficients of measurements for PDAF is presented in which it is assumed that the current turn rate of a maneuvering target changes within a limited range and its turn may be in arbitrary direction during data association.Thus,the predicted center for computing the weighted coefficients is a curved surface in 3-D space,which differs from the predicted center for setting up a validation gate,namely,a point in 3-D space.The distance between a measurement and the curved surface is used to compute its weighted coefficient.To reduce the computational complexity of weighted coefficients,the formulas for computing the maneuvering direction angle and turn rate corresponding to a measurement are presented.Simulation results show the proposed method reduces the percentage of lost tracks and improves the state estimation accuracy in tracking a maneuvering target using PDAF in the presence of clutter. To avoid or reduce the influence of unpredictable motion mode on data association, a new computing method of weighted coefficients of measurements for PDAF is presented in which it is assumed that the current turn rate of a maneuvering target changes within a limited range and its turn may be in arbitrary direction during data association.Thus, the predicted center for computing the weighted coefficient is a curved surface in 3-D space, which differs from the predicted center for setting up a validation gate, namely, a point in 3-D space The distance between a measurement and the curved surface is used to compute its weighted coefficient. To reduce the computational complexity of weighted coefficients, the formulas for computing the maneuvering direction angle and turn rate corresponding to a measurement are presented. Simulation results show the proposed method reduces the percentage of lost tracks and improves the state estimation accuracy in tracking a maneuvering target using PDAF in the presence of clutter.
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