CN109031207A - A kind of emitter Signals method for separating based on background characteristics - Google Patents
A kind of emitter Signals method for separating based on background characteristics Download PDFInfo
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- G—PHYSICS
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract
The invention belongs to signal sorting technical fields, particularly relate to a kind of emitter Signals method for separating based on background characteristics.Since emitter Signals are inevitably influenced by background environment in transmission process, receiving signal centainly includes the feature that can characterize background information, and this background characteristics becomes the new point of penetration that can distinguish radiation source.In the present invention, its reception signal of radiation source in different location has differences, based on this, using the method for restoring transmitting signal by filtering from reception signal, calculate the logarithm 1- norm of filter weight vector, the background characteristics of radiation source present position environment is extracted, and for realizing emitter Signals sorting.
Description
Technical field
The invention belongs to signal sorting technical fields, particularly relate to a kind of emitter Signals based on background characteristics
Method for separating.
Background technique
Signal sorting and signature analysis have a very important role in the signal processing.Either Radar emitter is still
Radiation source is communicated, the analysis and research to its feature are always unknown ginseng under hot research field, especially complex electromagnetic environment
Several emitter Signals sortings and identification are the important components in electronic intelligence reconnaissance system and electronic support system.In thunder
Up to field, its feature can be divided into: feature based on conventional five parameters, based on feature in arteries and veins etc..And the communications field can then be divided into:
Instantaneous parameters feature, Higher-Order Statistics Characteristics, Wavelet Transform Feature, circulation spectrum signature etc..
In field of radar, early stage is main using conventional five parameters as feature, i.e. radar pulse arrival time (TOA), carries
Wave frequency rate (RF), arrival bearing angle (DOA), impulse amplitude (PA) and pulse width (PD).When electromagnetic environment is relatively easy,
Five parameter attributes can be distinguished effectively.It is increasingly fierce with Radar ECM, various New Complex radars and changeable
Electromagnetic environment make five parameter attributes be difficult to obtain satisfied effect.For example, arrival time (TOA) is to intensive radar signal ring
Border and the decline of complicated its sorting capability of Radar jam signal type；Carrier frequency (RF) does not adapt to frequency agile radar；It arrives
Remote position cannot be distinguished at a distance of closer multiple emitter Signals up to azimuth (DOA).And for intrapulse feature, it is resonable
Although having better separating effect by upper, to the more demanding of radar receiver.In the communications field, instantaneous parameters feature calculation
Simply, but to signal-to-noise ratio it requires high.Higher Order Cumulants can inhibit Gauss white noise as a kind of common Higher-Order Statistics Characteristics
Sound.Wavelet Transform Feature and Cyclic Spectrum characteristic performance are preferable, but computationally intensive, and complexity is high.
Emitter Signals sorting is exactly to distinguish different radiation sources by finding each metastable feature of radiation source.And
Background environment must generate a fixing as intermediate link essential between radiation source and receiver to emitter Signals
It rings.In other words, receiving signal centainly includes the characteristic parameter that can characterize background information.Therefore, the background characteristics of emitter Signals
As the new point of penetration that can distinguish radiation source.If emitter Signals in time, there is sequencing, it is arranged successively and does not weigh mutually
It is folded；During electromagnetic transmission, transmission medium that different transmission paths is passed through, reflection angle, scattering degree are also different.
The then otherness that the background characteristics of emitter Signals has, this provides new foundation for emitter Signals sorting.
Emitter Signals are acted in transmission process by background environment, then it includes background information that receiving end, which receives signal,.When
When background environment locating for radiation source has differences, this species diversity is also embodied in receiving signal.Background environment and signal
Interactively may be expressed as:
Y=HX+N
Wherein: Y and X is the vector of receiving end and emitter Signals respectively, and H and N are background environment matrix and additivity respectively
White noise.It include the information of H in Y, if background environment H locating for different radiation sources is different, the spy of the characterization H information implied in Y
It levies also not identical.
H directly is sought, is acquired a certain degree of difficulty.And the thinking for restoring X by filtering from Y is used, the information of H can be obtained, again
It can avoid directly seeking H.Restoring the essence of X from Y is the process inverted to H, and the input of inverse filter at this time and output are distinguished
For Y and X.Therefore, the weight vector of inverse filter can characterize the background information of emitter Signals, and point for emitter Signals
Choosing.
Summary of the invention
The purpose of the present invention sorts problem aiming at emitter Signals, provides a kind of radiation source based on background characteristics
Signal sorting method is substantially a kind of extraction emitter Signals background characteristics and the thinking for sorting.Compared to existing
Emitter Signals method for separating, this method are focused on to study the background characteristics of emitter Signals, be provided for emitter Signals sorting
New approaches.
For achieving the above object, the present invention is based on the emitter Signals of background characteristics to sort process, including following step
It is rapid:
S1: set receive signal asN is data length, is normalized, and μ is the mean value for receiving signal, and σ is to connect
The standard deviation of the collection of letters number normalizes formula are as follows:
S2: data sectional, N are total length of data, and L is each segment data length, then segments is M=N/L；
S3: setting iteration step length μ and weight vector ωi(k) initial value.
S4: each segment data is filtered using MCMA algorithm is improved, is generated error signal e (k), formula are as follows:
E (k)=eR(k)+jeI(k)
Wherein,
S5: filter weight vector the number of iterations takes k=L, iteration more new formula are as follows:
ωi(k+1)=ωi(k)+μe(k)y(k-i)
Wherein, e (k) is error signal, and μ is iteration step length, and i is tap number, and k is the number of iterations.
S6: tap coefficient excess mean-square error rms is usedkAs the evaluation index of constringency performance, formula are as follows:
Wherein, ωk,iFor weight vector ωi(k) i-th of tap coefficient.
S7: weight vector ω is calculatedi(k) 1- norm, and logarithm is taken, formula are as follows:
S8: to different reception signals, executing S1 to S7, acquires all weight vectors of the different reception signals after region filtering
Logarithm 1- norm.Thresholding τ is set1With τ2, sorted for emitter Signals.
Beneficial effects of the present invention are that the present invention is based on the emitter Signals method for separating of background characteristics, and difference is utilized
Radiation source present position environment bring differentiation background characteristics；In fact, in the present invention, different reception signals is seen as
Therefore emitter Signals are realized emitter Signals using the background characteristics for receiving signal by the exercising result of different background environment
Sorting.
Detailed description of the invention
Fig. 1 is present invention actual measurement experimental system block diagram；
Fig. 2 is present invention actual measurement experiment scene figure；
Fig. 3 is the flow chart of realization process of the present invention；
Fig. 4 is the steadiness of emitter Signals background characteristics in the embodiment of the present invention 1；
Fig. 5 is the separation results of different emitter Signals in the embodiment of the present invention 2；
Fig. 6 is the separation results of different emitter Signals in the embodiment of the present invention 3.
Specific embodiment
A specific embodiment of the invention is described with reference to the accompanying drawing, preferably so as to those skilled in the art
Understand the present invention.Requiring particular attention is that in the following description, when known function and the detailed description of design perhaps
When can desalinate main contents of the invention, these descriptions will be ignored herein.
The feasibility of signal sorting method with measured signal data verification based on background characteristics.Rely on YunSDR-y420
Portable software radio platforms, the baseband signal data that transmitting Matlab programming obtains is by actual channel and receives processing,
Carrier frequency is 2370M, and transmitting antenna and receiving antenna are log-periodic antenna, and experimental system block diagram is as shown in Figure 1.
Experimental Hardware platform includes that a processor is Pentium (R) Dual-Core 3.2GHz, inside saves as the desk-top of 6G
Computer, a YunSDR-y420 portable software radio platforms；Software platform is WIN7 operating system,
Matlab2015b。
Fig. 2 is actual measurement experiment scene figure of the invention.As shown in Fig. 2, S is receiver, X, Y, Z are background environment in the presence of poor
Three different positions, i.e. h1, h2, h3 is different, and the difference of specific background environment is as shown in table 1:
The difference of 1 background environment of table
A~F is to penetrate source, is all made of the QPSK signal of identical modulation system, is located at tri- positions X, Y, Z.
Fig. 3 is execution step of the present invention when application is sorted with emitter Signals.As shown in figure 3, radiation of the invention
Source signal method for separating the following steps are included:
S1: set receive signal asN is data length, is normalized, and μ is the mean value for receiving signal, and σ is to connect
The standard deviation of the collection of letters number normalizes formula are as follows:
S2: data sectional receives data length N=100000, each segment data length L=25000, segments M=4；
S3: setting iteration step length μ=0.01 and weight vector ωi(k) initial value centre cap is 1, remaining is all 0.
S4: each segment data is filtered using MCMA algorithm is improved, is generated error signal e (k), formula are as follows:
E (k)=eR(k)+jeI(k)
Wherein,
S5: filter weight vector the number of iterations takes k=25000, iteration more new formula are as follows:
ωi(k+1)=ωi(k)+μe(k)y(k-i)
Wherein, e (k) is error signal, μ 0.01, i 15.
S6: tap coefficient excess mean-square error rms is usedkAs the evaluation index of constringency performance, formula are as follows:
Wherein, ωk,iFor weight vector ωi(k) i-th of tap coefficient.
S7: weight vector ω is calculatedi(k) 1- norm, and logarithm is taken, formula are as follows:
S8: to different reception signals, executing S1 to S7, acquires all weight vectors of the different reception signals after region filtering
Logarithm 1- norm.Thresholding τ is set1With τ2, sorted for emitter Signals.
Embodiment 1
The present embodiment is to survey the stability that experimental data verifies emitter Signals background characteristics.In experiment, transmitting antenna
With receiving antenna at a distance of 18m, background environment is actual channel.5 groups of transmitting signals are all made of QPSK modulation system, and every group 20000
Point, each group of data interval 1min transmitting, 1h repeat identical experiment in same position later, then share M=10 group and receive data.
As shown in figure 4, M=10 point respectively indicate 10 groups of normalization actual measurement receive data through filtering processing gained last
The logarithm 1- norm value of a weight vector.5 groups of data break 1min emit, and 5 groups of data are equally spaced 1min transmitting after 1h.By scheming
4 as can be seen that the logarithm 1- norm value of weight vector is substantially at same level, and numerical fluctuations are less than 0.05.So background environment
It changes with time less, it is believed that be stable.Therefore, the background characteristics of emitter Signals has stability, and can be used for
Emitter Signals sorting.
Embodiment 2
The present embodiment is to survey the feasibility that experimental data verifies the signal sorting method based on background characteristics.A, B, C are
Radiation source, transmitting signal use QPSK modulation system.In experiment, background environment is actual channel, and h1, h2, h3 background environment are deposited
In difference.
As shown in figure 5, every group of M=4 point, which respectively indicates 25000 points of normalization actual measurements, receives data through filtering processing gained
The logarithm 1- norm value of weight vector.Take thresholding τ1=1, τ2=0.8, as seen from Figure 5, the reception signal of radiation source A, B, C by
The logarithm 1- norm value of the last one weight vector obtained by process flow of the present invention has differences, and radiation source A, B, C can realize sorting.
Therefore, when the background environment difference locating for the radiation source, radiation source receives the background characteristics of signal, and there is also differences.Also, this
Kind background characteristics can be used for the signal sorting of radiation source.
Embodiment 3
The present embodiment is to survey the feasibility that experimental data verifies the signal sorting method based on background characteristics.D, E, F are
Radiation source, transmitting signal use QPSK modulation system.In experiment, background environment is actual channel, and h1, h2, h3 background environment are deposited
In difference.
As shown in fig. 6, every group of M=4 point, which respectively indicates 25000 points of normalization actual measurements, receives data through filtering processing gained
The logarithm 1- norm value of weight vector.Take thresholding τ1=0.8, τ2=0.7, as seen from Figure 6, radiation source D, E, F are received at signal
The logarithm 1- norm value of the last one weight vector of reason gained has differences, and radiation source D, E, F can realize sorting.It can equally obtain, no
With when background environment difference, the background characteristics for receiving signal is also different locating for radiation source.Therefore, this background characteristics can be used for spoke
Penetrate the signal sorting in source.
Claims (1)
1. a kind of emitter Signals method for separating based on background characteristics, which comprises the following steps:
S1, set receive signal asN is data length, is normalized:
Wherein μ is the mean value for receiving signal, and σ is the standard deviation for receiving signal；
S2, data sectional: N are total length of data, and L is each segment data length, then segments is M=N/L；
S3, setting iteration step length μ and weight vector ωi(k) initial value；
S4: each segment data is filtered using MCMA algorithm is improved, is generated error signal e (k):
E (k)=eR(k)+jeI(k)
Wherein,
S5, filter weight vector the number of iterations take k=L, iteration more new formula are as follows:
ωi(k+1)=ωi(k)+μe(k)y(k-i)
Wherein, e (k) is error signal, and i is tap number, and k is the number of iterations；
S6, using tap coefficient excess mean-square error rmskEvaluation index as constringency performance:
Wherein, ωk,iFor weight vector ωi(k) i-th of tap coefficient；
S7, weight vector ω is calculatedi(k) 1- norm, and take logarithm:
S8, to different reception signals, execute step S1 to S7, acquire the different all weight vectors for receiving signals after region filtering
Logarithm 1- norm, be arranged thresholding τ1With τ2, sorted for emitter Signals.
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Application publication date: 20181218 |