Parameter Estimation of Polyphase Code Signals Based on Periodic FRFT

DOI

10.2991/aiea-16.2016.72How to use a DOI?

Keywords

Radar reconnaissance; polyphase code; continuous wave; signal detection; Periodic FRFT.

Abstract

In order to improve the ability to intercepting polyphase code continuous wave signals for the radar reconnaissance receiver, a polyphase code continuous wave signals detection algorithm based on Periodic Fractional Fourier transform (Periodic FRFT, PFRFT) is proposed. In this paper, the PFRFT and its properties of linear frequency modulated continuous wave signals are studied. And the characteristics of linear frequency modulated continuous wave (LFMCW) signals of polyphase code continuous wave signals is analyzed. According to the similarity between the polyphase code continuous wave signals and the linear frequency modulated continuous wave signals, a polyphase code continuous wave signals detection algorithm based on PFRFT is proposed, also the realization process is given, and then the detection performance and parameter estimation performance are analyzed. Simulation results show that, compared with other existing algorithms, the proposed algorithm has better ability to detecting weak signal, and the minimum detectable signal to noise ratio (SNR) can be reduced by at least 6 dB, which is further reduced with the observation time extended.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jiandong Zhu
AU  - Tengfei Jia
AU  - Yanfei Wei
AU  - Zhiqiang Ji
AU  - Youyi Fan
AU  - Junkui Xu
PY  - 2016/11
DA  - 2016/11
TI  - Parameter Estimation of Polyphase Code Signals Based on Periodic FRFT
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
PB  - Atlantis Press
SP  - 405
EP  - 412
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.72
DO  - 10.2991/aiea-16.2016.72
ID  - Zhu2016/11
ER  -