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Performance Evaluation of a Two-Stage Guided Bomb Control System under Line-of-Sight Measurement Noise: A Jacobian-Based LQR and Lead-Prediction Approach
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Kielce University of Technology
 
These authors had equal contribution to this work
 
 
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Marta Grzyb   

Kielce University of Technology
 
 
 
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ABSTRACT
The main objective of this paper is to evaluate the dynamic robustness and tracking performance of a guidance and control architecture for a six-degree-of-freedom (6-DOF) guided bomb engaging a moving ground target with at constant velocity under severe line-of-sight (LOS) measurement noise. The proposed framework integrates a Jacobian-based Linear Quadratic Regulator (LQR), adaptive time-to-go lead prediction, backward numerical differentiation with first-order digital IIR low-pass filter with scenario-tuned parameters, and a constrained two-stage guidance scheme (midcourse and terminal phases). By recalculating the instantaneous Jacobian matrix at every integration step, the feedback gains adapt continuously to non-linear aerodynamic changes without relying on offline lookup tables. Extensive 6-DOF Matlab/Simulink simulations conducted across low, medium, and high LOS noise levels demonstrate that the integrated guidance system maintains a remarkably stable terminal miss distance of approximately 2.41-2.50 m despite a tenfold increase in measurement uncertainty. Furthermore, the tuned digital filter attenuates LOS tracking error RMSE by nearly 73% (from 0.312˚ down to 0.083˚ in high-noise conditions), effectively mitigating control chatter while preventing actuator saturation (maximum surface deflection reached 44.8˚ within physical ±45˚ limits). These quantitative findings confirm that the proposed Jacobian-based LQR and lead-prediction architecture provides an effective, structurally lightweight, and reliable baseline for precision-guided munitions under realistic sensor disturbances.
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