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This paper discusses the application of Lagrange interpolation and cubic spline interpolation to predict acceleration/velocity and to adapt better window lengths for any range of target acceleration. The estimated velocity/acceleration is then smoothed using Kalman and adaptive Kalman filters. Simulation results show that in a ‘high-level noise’ scenario, the interpolated adaptive filter gives a more accurate estimation than the existing method of using a rectangular window function. Track initialization error minimized with spline interpolation was comparable to that minimized with Lagrange interpolation.

Interpolated Adaptive Doppler Filter for Estimating Velocity