KR101317887B1 - Radar modulation identification method using gini's coefficient - Google Patents

Abstract

PURPOSE: A radar modulation type identifying method using Gini's coefficient is provided to use a maximum likelihood (ML) classifier, thereby automatically identifying a radar modulation type. CONSTITUTION: A radar signal (S[k]) stored in a digital receiver is read (S200). A degree of unbalance in a frequency domain of the radar signal is quantified by a quantifying unit using Gini's coefficient (S210). A modulation type of the radar signal is identified by quantifying the degree of unbalance and using an ML classifier (S220). [Reference numerals] (S200) Read a radar signal (S[k]) stored in a digital receiver; (S210) Quantify a degree of unbalance in a frequency domain of the radar signal (s[k]) detected using Gini's coefficient which is a feature factor; (S220) Identify a modulation type of the radar signal (s[k]) detected by quantifying the degree of unbalance and using an ML classifier

Description

Radar modulation identification method using Gini's coefficient

The present invention relates to an electronic warfare support system, and more particularly, to quantify the degree of imbalance in the frequency domain of a detected radar signal using Gini's Coefficient and based on the maximum likelihood classifier (ML). A method for automatically recognizing a radar modulation type using a classifier.

An electronic warfare support system is a system for detecting and / or identifying radar signals in a high density electromagnetic wave signal environment. For the detection / identification, the electronic warfare support system receives the radar signals received from all directions and measures the pulse unit variable specifications in real time, so that each radar has continuity, regularity and correlation of the signals in the mixed pulse train data mixed with multiple signals. Disconnect the signal source.

In addition, the pulse strings of the radar signal sources are analyzed for inter-pulse and intra-pulse modulation characteristics, and the radar signals are identified by comparison with the finally embedded identification library.

Recently, due to the gradual development of radar technology and the rapid increase of electronic equipment using electromagnetic signals, it is increasingly difficult to accurately identify each signal source.

Therefore, the intra-pulse modulation of the radar signal is an important identification variable that can contribute to signal detection and identification in electronic warfare support systems. Recently, a method of analyzing / identifying a signal using a digital receiver has been proposed to receive and analyze a radar signal operating in a wide band.

Therefore, there is a need for a technique for analyzing the intra-pulse modulation of radar signals detected through digital receivers.

1. Korean Published Patent No. 10-2009-0096913 2. Korean Patent No. 10-1075516 3. Korean Patent No. 10-1235059 4. Korean Patent No. 10-1241101

The present invention is proposed to solve the problem according to the above background technology, UM (Un-modulated, Unmodulated), LFM (Linear Frequency Modulation), NLFM (Non-LFM), FSK (Frequency Shift Keying) It is an object of the present invention to provide a radar modulation type recognition method capable of automatically recognizing a modulation type of a radar signal having intra-pulse modulation such as frequency shift modulation.

The present invention provides a radar modulation mode recognition method capable of automatically recognizing the modulation mode of the radar signal having intra-pulse modulation in order to achieve the problem posed above.

The radar modulation type recognition method,

A signal reading step of reading a radar signal;

An unbalance degree quantification step of quantifying an unbalance degree in a frequency domain of the radar signal using a Genie coefficient; And

And a modulation shape recognition step of recognizing a modulation shape of the radar signal using an imbalance degree quantification and a ML (Maximum Likelihood) classifier.

In this case, the step of quantifying the degree of imbalance, the step of calculating the power spectrum information using the read radar signal; Calculating a frequency power vector by sorting in order of a large value according to a frequency change using the power spectrum information; Calculating all frequency power sums using the power spectrum information; And calculating the degree of imbalance degree using the frequency power vector and the sum of the frequency powers as inputs of the Gini's coefficients.

(여기서, φ는 초기 위상이고, f_c는 중심 주파수이며, t는 시간이고, k는 자연수를 나타낸다)에 의해 산출되고, 상기 파워 스펙트럼 정보는, 수학식

(여기서, s[k]는 레이더 신호이고, f는 주파수, k는 자연수를 나타낸다)인 것을 특징으로 할 수 있다.In addition, the radar signal is a radar signal detected through a digital receiver,

(Where φ is an initial phase, f _c is a center frequency, t is time, and k represents a natural number), and the power spectrum information is expressed by the following equation.

(Where s [k] is a radar signal, f is a frequency, and k is a natural number).

In addition, the ML classifier may be modeled using the Gini's coefficient as a feature factor and using a mean and a variance of feature factor values and a Gaussian distribution.

(여기서, L(g)=

이고, z는 자연수이고,

는 지니계수의 평균이고,

는 지니계수의 분산을 나타낸다)인 것을 특징으로 할 수 있다.In addition, the ML classifier

Where L (g) =

, Z is a natural number,

Is the mean of the Gini coefficient,

Represents the variance of the Gini's coefficient).

(S_n은 주파수 파워 벡터이고, D는 주파수 파워 합을 나타낸다)에 의해 산출되는 것을 특징으로 할 수 있다.In addition, the Gini coefficient is,

(S _n is the frequency power vector, and D represents the sum of the frequency power).

In addition, the modulation type may be any one of UM (Un-modulated), Linear Frequency Modulation (LFM), Non-LFM (LFM), and Frequency Shift Keying (FSK).

According to the present invention, it is possible to quantify the degree of imbalance in the frequency domain of the detected radar signal using Gini's Coefficient and to automatically recognize the radar modulation type by using the maximum likelihood classifier. It is possible.

의 주파수 영역에서의 불균형 정도를 정량화하는 과정을 보여주는 흐름도이다.
도 4는 본 발명의 일실시예에 따라 레이더 변조 형태에 따른 파워스펙트럼과 지니계수의 연산 값에 대한 예를 보여주는 도면이다.1 is a block diagram of a radar modulation type recognition apparatus 100 according to an embodiment of the present invention.
2 is a flowchart illustrating a process of recognizing a radar modulation form using a Gini coefficient according to an embodiment of the present invention.
FIG. 3 is a radar signal detected using a Gini coefficient, which is a feature factor of the process shown in FIG.

Is a flow chart showing the process of quantifying the degree of imbalance in the frequency domain.
FIG. 4 is a diagram illustrating an example of an operation value of a power spectrum and a Gini coefficient according to a radar modulation type according to an embodiment of the present invention.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It is to be understood, however, that the invention is not to be limited to the specific embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

Like reference numerals are used for similar elements in describing each drawing.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another.

For example, without departing from the scope of the present invention, the first component may be referred to as the second component, and similarly, the second component may also be referred to as the first component. The term "and / or" includes any combination of a plurality of related listed items or any of a plurality of related listed items.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Should not.

Hereinafter, a radar modulation type recognition method using Genie coefficients according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a block diagram of a radar modulation type recognition apparatus 100 according to an embodiment of the present invention. Referring to FIG. 1, the radar modulation type recognition apparatus 100 may include a digital receiver 110 that receives a radar signal and processes the digital signal and stores the radar signal, an extractor 130 that extracts the stored radar signal, Modulation type recognition for recognizing the modulation form of the radar signal using the quantization unit 140 for quantifying the degree of imbalance in the frequency domain of the extracted radar signal using the Gini coefficients and the quantification of the degree of imbalance and the ML (Maximum Likelihood) classifier. The unit 150 is configured to be included.

Here, the radar signal receiving unit 111 and the radar signal storage unit 112 is a configuration of the digital receiver 110.

The quantization unit 140 performs a function of quantifying the degree of imbalance in the frequency domain of the extracted radar signal using the Genie coefficient. In other words, the power spectrum information is calculated using the read radar signal, the frequency power vector is calculated using the power spectrum information in order of large value according to the frequency change, and all the frequencies are used using the power spectrum information. The sum of powers is calculated and the degree of imbalance degree quantification is calculated using the frequency power vector and the sum of the frequency powers as inputs of the Gini coefficients.

The modulation type recognizer 150 uses UM (Un-modulated, Unmodulated), LFM (Linear Frequency Modulation), NLFM (Non-LFM), and the like, using a degree of imbalance quantification and a maximum likelihood (ML) classifier. And / or automatically recognizes the modulation form of the radar signal with intra-pulse modulation, such as frequency shift keying (FSK).

In general, a radar signal refers to a radio wave signal sensed by a radar antenna when high-frequency and high-power pulse waves radiated to the air from the radar transmitter are scattered back to a weather target.

Accordingly, the received radar signal may also include information about weather targets and interference signals from other radio sources.

In addition, elements of the radar signal include frequency, amplitude, phase, and the like.

라 할 때, 다음식과 같다.2 is a flowchart illustrating a process of recognizing a radar modulation form using a Gini coefficient according to an embodiment of the present invention. 2, the radar signal is read (step S200). In other words, the radar signal detected through the digital receiver 110

When we say,

Where? Is the initial phase, f _c is the center frequency, t is the time, and k is the natural number.

을 저장하고 있는 디지털 수신기(110)의 메모리(미도시)로부터 연산장치인 신호 추출부(130)로 읽어 들이게 된다. Thus, the detected signal to recognize the modulation type of s [k]

It is read from the memory (not shown) of the digital receiver 110, which stores the signal, into the signal extraction unit 130, which is an arithmetic device.

The memory may include a hard disk drive, a flash memory, an electrically erasable programmable read-only memory (EEPROM), a static RAM (SRAM), a ferro-electric RAM (FRAM), a phase-change RAM (PRAM), a magnetic RAM (MRAM), and the like. The same nonvolatile memory and / or volatile memory such as random access memory (RAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), or the like may be used.

을 이용하여 파워 스펙트럼(power spectrum,

) 정보를 구하고, 이러한 파워스펙트럼 정보를 특징인자인 지니계수의 입력으로 이용하여 주파수 영역에서의 불균형 정도를 정량화한다.When the radar signal is read, the degree of imbalance in the frequency domain of the radar signal is quantified by the quantifier 140 using the Genie coefficient (step S210). In other words, generated by step (S200)

Using power spectrum,

Information), and the power spectrum information is used as an input of the Gini coefficient, a characteristic factor, to quantify the degree of imbalance in the frequency domain.

When the degree of imbalance is quantified, the modulation form of the radar signal is recognized using the degree of imbalance degree quantification and the maximum likelihood (ML) classifier (step S220).

의 주파수 영역에서의 불균형 정도를 정량화하는 과정을 보여주는 흐름도이다. FIG. 3 is a radar signal detected using a Gini coefficient, which is a feature factor of the process shown in FIG.

Is a flow chart showing the process of quantifying the degree of imbalance in the frequency domain.

을 이용하여 우선 다음식과 같이 파워 스펙트럼(Power Spectrum,

)을 연산한다. Referring to FIG. 3, in step S300, the signal extractor 130, which is an arithmetic device, reads a signal from a memory of the digital receiver 110.

First, using Power Spectrum,

).

을 이용하여

을 f(주파수)의 변화에 따라, 그 값이 큰 순서대로 정렬하여 벡터 S를 구한다. 이를 수학식으로 나타내면 다음과 같다.
In step S310, the power spectrum that is a result of the calculation in step S300

Using

According to the change of f (frequency), the values S are arranged in order of increasing value. This is expressed as the following equation.

을 이용하여 모든 주파수 파워의 합(D)을 구한다. In step S320, the power spectrum which is the result of the calculation in step S300

The sum of all frequency powers (D) is obtained by using.

In step S330, the degree of imbalance is quantified using the vectors S and D, which are the results of steps S3100 and S220, as inputs to the Gini's Coefficient, I _G , which is a feature factor. This is shown in the following equation.

)과 분산(

)을 이용하여 다음식과 같이 가우시안 모델링을 한다. Referring to FIG. 2, in step S220, the average of the feature factor values under the assumption that the distribution of feature factor values quantifying the degree of imbalance in step S210 follows a Gaussian distribution.

) And variance (

), Gaussian modeling is done using

을 우도(Likelihood) 함수

라 할 때, 이를 최대화하는 미지의 파라미터

을 찾아 탐지된 레이더 신호

의 변조 형태를 자동으로 분류한다. 이를 나타내면 다음식과 같다.Also, probability density function constructed from feature factor values

Likelihood Function

, An unknown parameter that maximizes this

To detect detected radar signals

Automatically classify the modulation form of. This is shown in the following equation.

4 is a diagram illustrating an example of a calculation value of a power spectrum and a Gini coefficient according to a radar modulation type according to an embodiment of the present invention. Referring to FIG. 4, power spectra 400, 410 and Gini coefficients 420 are displayed according to the types of A, B, C, D, E, F, G, and H.

100: radar modulation mode recognition device
110: digital receiver
111: radar signal receiving unit
112: radar signal storage unit
130: signal extraction unit
140: quantification unit
150: modulation type recognition unit

Claims (7)

In the radar modulation type recognition method using the Genie coefficient to identify the radar signal in the electronic warfare support system,
A signal reading step of reading a radar signal;
An unbalance degree quantification step of quantifying an unbalance degree in a frequency domain of the radar signal using a Genie coefficient; And
A modulation type recognition step of recognizing a modulation form of the radar signal using an imbalance degree quantification and a ML (Maximum Likelihood) classifier;
Radar modulation type recognition method using a genie coefficient, characterized in that it comprises a. The method of claim 1,
Unbalance degree quantification step of quantifying the degree of imbalance in the frequency domain of the radar signal using the Genie coefficient,
Calculating power spectrum information by using the read radar signal;
Calculating a frequency power vector by sorting in order of a large value according to a frequency change using the power spectrum information;
Calculating all frequency power sums using the power spectrum information; And
And calculating a degree of disproportionation using a frequency power vector and a sum of frequency powers as inputs of the Gini coefficients.
3. The method of claim 2,
The radar signal is a radar signal detected by the digital receiver,

(Where φ is an initial phase, f _c is a center frequency, t is time, and k represents a natural number), and the power spectrum information is expressed by the following equation.

(Where s [k] is a radar signal, f is a frequency, and k is a natural number).
The method of claim 3, wherein
And the ML classifier is modeled using the mean and the variance of the feature values using the Gini coefficient as the feature factor, and is assumed to be a Gaussian distribution.
5. The method of claim 4,
The ML classifier is an equation

Where L (g) =

, Z is a natural number,

Is the mean of the Gini coefficient,

Represents the variance of the Gini coefficients).
The method of claim 5, wherein
The Gini's coefficient is,

(S _n is a frequency power vector, and D represents a sum of frequency powers).
The method of claim 3, wherein
The modulation type may be any one of UM (Un-modulated), Linear Frequency Modulation (LFM), Non-LFM (LFM), and Frequency Shift Keying (FSK).

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