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Research on the Identification of Radar Signal Modulation in Earth Observation System

Author: YuanYuHan
Tutor: QuanTaiFan
School: Harbin Institute of Technology
Course: Information and Communication Engineering
Keywords: modulation recognition extraction of characters instantaneous self-correlation Wigner-Ville distribution wavelet ridge BP ANN classifier
CLC: TN957.51
Type: Master's thesis
Year: 2009
Downloads: 42
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Abstract


The identification of signal modulation is a crucial technique in electronic reconnaissance which directly determines the results of electronic reconnaissance. In this paper, the way of extracting characters of instantaneous frequency is investigated, and the emulation experiment is made to extract the character of time-frequency curve and identify the style of signal modulation used by BP artificial neural net classifier.In the first, the signal environment include the rule of choosing the density of information flow and the instantaneous areas covered by satellites which the electronic reconnaissance receiver works in is investigated and the time-frequency characters of common radar signals are studied. In this dissertation, four kinds of common radar signals are choused. They are simple pulse signal, linear frequency modulation, binary phase-coded pulse and binary frequency-coded pulse.In the second, the ways of extraction of time-frequency curve in the time-frequency field are investigated specifically. These ways are include instantaneous self-correlation algorithm, Winger-Ville distribution and the extraction algorithm of time-frequency curve based on wavelet ridge. The instantaneous self-correlation algorithm has simple principle and a small quantity of calculative times, so it is easy to use in engineering. A mutative time-frequency resolving rate is owned by Wigner-Ville distribution, and cross components are produced in the process of Winger-Ville distribution and they will effect the identification of the way of signal modulation. In this paper, several methods to reduce the effect of cross components are introduced. The effect of noise is restrained in the extraction algorithm of time-frequency curve based on wavelet ridge, but the calculative time is long.In the third, a statistic method is used to extract the characters of time-frequency curve and the classification performance of these characters is discussed. By this method, the style of modulation is classified clearly, and in a certain extent, the effect of noise is restrained.In the end, the principle of designing BP artificial neural net is discussed. In addition, the classification emulation experiment for the four kinds of common radar signals is made to elicit classification rate.

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Radar > Radar equipment,radar > Radar receiving equipment > Radar signal detection and processing
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