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Optimal Steady-State Range Prediction Filter for Tracking with LFM Waveforms

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This communication proposes a gain design method of an α - β filter with linear frequency-modulated (LFM) waveforms to achieve optimal range prediction (tracking) of maneuvering targets in steady-state. First, a steady-state root-mean-square (RMS) prediction error, called an RMS-index, is analytically derived for a constant-acceleration target. Next, a design method of the optimal gains that minimizes the derived RMS-index is proposed. Numerical analyses demonstrate the effectiveness of the proposed method, as well as producing a performance improvement over the conventional Kalman filter-based design method. Moreover, the theoretical relationship between range tracking performance and a coefficient for range-Doppler coupling of LFM waveforms is clarified. Numerical simulations using the proposed method demonstrate LFM radar tracking of maneuvering targets and prove the method’s effectiveness.
Title: Optimal Steady-State Range Prediction Filter for Tracking with LFM Waveforms
Description:
This communication proposes a gain design method of an α - β filter with linear frequency-modulated (LFM) waveforms to achieve optimal range prediction (tracking) of maneuvering targets in steady-state.
First, a steady-state root-mean-square (RMS) prediction error, called an RMS-index, is analytically derived for a constant-acceleration target.
Next, a design method of the optimal gains that minimizes the derived RMS-index is proposed.
Numerical analyses demonstrate the effectiveness of the proposed method, as well as producing a performance improvement over the conventional Kalman filter-based design method.
Moreover, the theoretical relationship between range tracking performance and a coefficient for range-Doppler coupling of LFM waveforms is clarified.
Numerical simulations using the proposed method demonstrate LFM radar tracking of maneuvering targets and prove the method’s effectiveness.

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