Abstract
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.
Highlights
Maneuvering-target tracking using laser, radar, and/or sonar is essential for monitoring systems in robots, aircrafts, and intelligent vehicles
We investigate the performance of the linear frequency-modulated (LFM) α-β filter with the proposed gain design method using theoretical steady-state analyses and numerical simulations assuming radar tracking of a maneuvering target
This paper proposed a gain design method to achieve optimal steady-state range tracking for the LFM α-β filter
Summary
Maneuvering-target tracking using laser, radar, and/or sonar is essential for monitoring systems in robots, aircrafts, and intelligent vehicles. With respect to a general tracking filter (without LFM waveforms), our previous work [12,13] introduced an efficiency performance index called a root-mean-square (RMS)-index, which expresses the steady-state root-mean-square error in position (range) predictions. Using this index, we achieved accurate tracking compared with conventional gains determined based on the Kalman filter equations. It is believed that the application of the RMS-index to the LFM α-β filter resolves the above-mentioned problems In this communication, a gain design method used to compose an LFM α-β filter that minimizes the steady-state range prediction errors is proposed. An application of the proposed method to an LFM radar simulation is demonstrated to show its effectiveness
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