LOS-Rate Estimation of Highly Maneuvering Targets via LOS-Domain Modeling and Adaptive Strong Tracking Lattice Kalman Filtering

Accurate line-of-sight (LOS) rate estimation is essential for terminal guidance against highly maneuvering targets. To improve estimation accuracy under rapidly varying target dynamics, this paper proposes a framework that combines a 12-state LOS-domain jerk model with an adaptive strong tracking lattice Kalman filter (ASTLKF). By exploiting the exact linear measurement relation induced by the LOS-domain formulation, the proposed method preserves computational practicality while improving maneuver responsiveness. An adaptive strong tracking mechanism with a dynamically bounded upper limit is further introduced to enhance filter responsiveness under model mismatch caused by target maneuvers. Simulation results under both abrupt pull-up and smooth sinusoidal maneuvers show that the proposed 12-ASTLKF achieves more accurate LOS-rate estimation than the benchmark methods. In particular, it reduces transient lag under abrupt maneuvering conditions and maintains better tracking consistency under continuous maneuvering conditions. A parameter sensitivity analysis further verifies the practical robustness of the proposed adaptive mechanism. These results demonstrate that the proposed framework provides an accurate and robust solution for LOS-rate estimation of highly maneuvering targets.