Heuristic-Based Nuisance Parameter Estimation of Low-Cost Accelerometers for Guided Spin-Stabilized Projectiles

Accelerometer measurement errors due to low-cost devices and minimal ground calibration significantly affect inertial navigation performance in a spin-stabilized projectile application. A method of compensating for these nuisance parameters is proposed that leverages the spin-stabilized projectile flight dynamics and sensor modeling in an extended Kalman filter. Nonlinear modeling and practical simplification of the in-flight measurements was undertaken. An estimator algorithm was designed and validated in simulation. Results illustrate the manner in which corrupted measurements are enhanced. Monte Carlo analysis suggests that the nuisance parameter estimation improves navigation accuracy by three orders of magnitude, and under certain conditions is sufficient to increase overall system precision over the ballistic performance for munitions in a global positioning system-denied environment.
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