Paper
2 April 2010 A method of phase estimation for sinusoid signal based on correlation algorithm
Xiaoming Chang, Xiaolin Zhang, Qiang Zhang
Author Affiliations +
Proceedings Volume 7651, International Conference on Space Information Technology 2009; 76510O (2010) https://doi.org/10.1117/12.855277
Event: International Conference on Space Information Technology 2009, 2009, Beijing, China
Abstract
Phase difference change rate has been put forward recently, which attracts wide attention as a measuring parameter in the rapid passive positioning system. In the measurement of passive location, positioning accuracy is greatly influenced by the measurement accuracy of corresponding observed quantity and the follow-up effects of wave filtering. A method of phase estimation based on correlation algorithm for sinusoid signal is presented in this paper, which can be used in the design of digital phase interferometer. Using the correlation algorithm method, it is possible to effectively separate part of noise from the useful signal, and also to improve the resistibility to random disturbance and the accuracy of measuring system. The explicit formula explanation in this paper demonstrates that as the most important characteristic of the method, the frequency for received sinusoid signal is not required in advance. The Monte Carlo simulation demonstrates that the phase estimation by this method can be achieved within 1°, which is more accurate than that with the traditional analog phase interferometer; Compared with the other method by FFT in the digital interferometer, the accuracy of this method is better in the low SNR situation.
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Xiaoming Chang, Xiaolin Zhang, and Qiang Zhang "A method of phase estimation for sinusoid signal based on correlation algorithm", Proc. SPIE 7651, International Conference on Space Information Technology 2009, 76510O (2 April 2010); https://doi.org/10.1117/12.855277
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KEYWORDS
Interferometers

Phase interferometry

Analog electronics

Interference (communication)

Signal to noise ratio

Error analysis

Monte Carlo methods

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