Passive ranging for dog-fight air-to-air IR missiles

摘要

In short-range air-to-air intercept scenarios, passive ranging for a maneuvering target is still the most challenging problem for dogfight IR missiles. ^It is important to estimate the relative range between the missile and the target as a dominate parameter for the imaging seeker to switch its tracking algorithms during the entire homing phase or for the gyro-stabilized IR seeker to lead the hottest spot of the target, such as a point on the engine exhaust plume, with a lead bias during the end game homing phase. ^In this study, a U-D extended Kalman filter in modified spherical coordinates (MSC), combined with an observability enhancing modified proportional navigation guidance (MPNG) law, is proposed to obtain convergent estimates of state variables involved particularly in range channel otherwise unavailable from IR trackers. ^Observability analysis via line-of-sight (LOS) only measurements is briefly discussed based on the differential geometric approach for the nonlinear tracking filter. ^Simulation results indicate that the proposed tracking filter in conjunction with the dual guidance law is able to provide the convergence of the range estimate in a few hundred meters. ^(Author)