Abstract
In order to further improve the frequency estimation precision under high dynamic, the frequency estimation method based on Kalman filter is studied. Two methods of Kalman filter directly using for frequency estimation are studied, taking the phase of echo signal and the echo signal for measurements, which adopt nonlinear and linear Kalman filtering algorithm to estimate the Doppler frequency. Based on the study of performance of these two methods, the Doppler adaptability of the two methods is studied. The simulation results show that the speed precision is improved. But, the two methods of this research are limited by the fixed frequency conversion, and when Doppler changed a large range, the filtering is easy to diverge.
Highlights
LEO satellite flight dynamics complicated, speed and all derivative values are large, so it belongs to frequency estimation problem under high dynamic condition
Phaselocked loop is the most commonly used in satellite signal processing frequency estimation method[1,2,3,4], but under high dynamic conditions it requires using higher-order loop, which cause stability problems
In order to further improve the high frequency dynamic state estimation accuracy, this paper focus on the frequency estimation method based on Kalman Filter
Summary
LEO satellite flight dynamics complicated, speed and all derivative values are large, so it belongs to frequency estimation problem under high dynamic condition. Phaselocked loop is the most commonly used in satellite signal processing frequency estimation method[1,2,3,4], but under high dynamic conditions it requires using higher-order loop, which cause stability problems. Kalman filter is an optimal estimation method, with excellent performance and noise filtering characteristics predict [5, 6]. In order to further improve the high frequency dynamic state estimation accuracy, this paper focus on the frequency estimation method based on Kalman Filter
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