CN107276932B - Blind source signal separation method and device - Google Patents
Blind source signal separation method and device Download PDFInfo
- Publication number
- CN107276932B CN107276932B CN201710431161.XA CN201710431161A CN107276932B CN 107276932 B CN107276932 B CN 107276932B CN 201710431161 A CN201710431161 A CN 201710431161A CN 107276932 B CN107276932 B CN 107276932B
- Authority
- CN
- China
- Prior art keywords
- signal
- strong interference
- unknown
- weak
- mixed
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/0202—Channel estimation
- H04L25/0238—Channel estimation using blind estimation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L25/03012—Arrangements for removing intersymbol interference operating in the time domain
- H04L25/03019—Arrangements for removing intersymbol interference operating in the time domain adaptive, i.e. capable of adjustment during data reception
- H04L25/03082—Theoretical aspects of adaptive time domain methods
- H04L25/03089—Theory of blind algorithms, recursive or not
Abstract
The invention discloses a method and a device for separating blind source signals, which relate to the technical field of signal processing, and the method comprises the following steps: performing first blind source separation operation on an unknown strong interference signal in a source mixed signal to obtain parameter characteristics of the unknown strong interference signal; according to the parameter characteristics of the obtained unknown strong interference signal, carrying out recombination processing on the unknown strong interference signal to obtain a strong interference cancellation signal for canceling the unknown strong interference signal in the source mixed signal; and carrying out cancellation operation on the unknown strong interference signal in the source mixed signal by using the obtained strong interference cancellation signal to obtain a weak mixed target signal, and carrying out second blind source separation operation on the obtained weak mixed target signal to obtain a separated weak target signal.
Description
Technical Field
The present invention relates to the field of signal processing technologies, and in particular, to a method and an apparatus for blind source signal separation.
Background
The blind source separation of weak signals under unknown strong interference is a difficult problem of blind source separation, and no ideal method exists. In recent years, a common method is empirical mode decomposition. The EMD (Empirical Mode decomposition) method proposes the concept of IMF (Intrinsic Mode Function) by Huang hua Huang on the basis of deeply researching the concept of instantaneous frequency, and can decompose any signal into fundamental Mode components by using EMD.
Based on empirical Mode decomposition, a signal is decomposed into a sum of a series of IMFs (Intrinsic Mode functions), Hilbert transformation is performed on each Intrinsic Mode Function to obtain an instantaneous frequency of the Intrinsic Mode Function, and the instantaneous frequency is expressed by a plane with time-frequency as a coordinate to obtain a distribution of time-frequency-energy, which is called a Hilbert spectrum. Theoretically, HHT not only solves the resolution problem of wavelet analysis in the case of multiple radiation sound sources and the adaptability problem of different sound source signals, but also solves the cross term problem of multi-component signals of Winger-Ville distribution. The separation of strong interference and weak signals can adopt an EMD method to decompose an actually measured signal into a series of IMFs, and as a result, the fluctuation or trend of different scales in the signal is decomposed step by step to generate a series of data sequences with different characteristic scales, so as to achieve the purpose of separating trend items.
The EMD decomposition method is based on the following assumptions that (1) the signal has at least two extreme points, one maximum and one minimum, or the number of the maximum or minimum is more than 2 (or more than 2) than the number of the zero points; (2) the characteristic time scale of the signal is determined by the time interval between the extreme points; (3) if the extreme points are absent in the data but the singular points exist, the extreme points can be obtained through one or more times of difference.
The specific processing method of EMD decomposition is to find the maximum point set and the minimum point set of the data x (t), and then fit the upper envelope line and the lower envelope line of x (t) by an interpolation method. Calculating the average value of the two envelope lines, and recording the average value as m1(t) of (d). Calculating to obtain x (t) and m1The difference of (t) is denoted by h1(t, i.e. h)1(t)＝x(t)-m1(t), in general, h1(t) is still not an IMF component for which the above process needs to be repeated. I.e. h1(t) fitting the upper envelope and the lower envelope of the new data sequence to obtain an average value m of the two envelopes11(t) and calculating h1(t) and m11The difference of (t) is recorded as h11(t, i.e. h)11(t)＝h1(t)-m11(t), repeating the above operation i times until h1i(t) until the IMF condition is satisfied, the first IMF component of signal x (t) is obtained, noted as IMF1(t)＝h1i(t) separating imf from the data1I.e. r1(t)＝x(t)-imf1(t) if the residual r1(t) still contains longer period components, then it is considered as new data, and the above steps are repeated,and (3) decomposing to obtain new IMF:
r1-imf2＝r2,
r2-imf3＝r3
...
rn-1-imfn＝rn
the data screening ends when the residual becomes a constant, or a monotonic function, or a function with one and only one pole. At this time rn(t) is called the remainder, each of the screened IMF components having a lower frequency characteristic than the previously screened IMF component. Finally, the original data sequence can be represented by these IMF components and a mean or trend term:
the above method adopts a simple convergence criterion, i.e. the screening process terminates as long as the number of the extreme points and the zero-crossing points of the signal is equal. The stopping criterion is simple, and the definition of IMF is considered, so that the stopping criterion tends to be more reasonable.
Although the EMD can be used for blind source signal separation under strong interference, the situation of high computational complexity and poor separation performance can be met under the condition of high interference-to-signal ratio.
Disclosure of Invention
The technical problem solved by the scheme provided by the embodiment of the invention is that the existing blind source signal separation has high computational complexity and poor performance.
The blind source signal separation method provided by the embodiment of the invention comprises the following steps:
performing first blind source separation operation on an unknown strong interference signal in a source mixed signal to obtain parameter characteristics of the unknown strong interference signal;
according to the parameter characteristics of the obtained unknown strong interference signal, carrying out recombination processing on the unknown strong interference signal to obtain a strong interference cancellation signal for canceling the unknown strong interference signal in the source mixed signal;
and carrying out cancellation operation on the unknown strong interference signal in the source mixed signal by using the obtained strong interference cancellation signal to obtain a weak mixed target signal, and carrying out second blind source separation operation on the obtained weak mixed target signal to obtain a separated weak target signal.
Preferably, the first blind source separation refers to a separation process of an unknown strong interference signal in the source mixed signal; the second blind source separation refers to the separation processing of each weak target signal in the weak mixed target signal.
Preferably, the obtaining the parameter characteristics of the unknown strong interference signal by performing the first blind source separation operation on the unknown strong interference signal in the source mixed signal includes:
determining a first initial point for separating the source mix signal;
performing first blind source separation operation on an unknown strong interference signal in a source mixed signal by using the determined first initial point to obtain parameter characteristics of the unknown strong interference signal;
wherein the parameter characteristics include characteristics of frequency, power, phase, amplitude, sampling rate, frequency modulation rate, and transmission bit rate.
Preferably, the performing a cancellation operation on the unknown strong interference signal in the source mixed signal by using the obtained strong interference cancellation signal to obtain a weak mixed target signal includes:
acquiring parameter characteristics of the strong interference cancellation signal;
according to the parameter characteristics of the unknown strong interference signal and the acquired parameter characteristics of the strong interference signal, carrying out cancellation operation on the unknown strong interference signal in the source mixed signal to obtain a weak mixed target signal;
and the parameter characteristics of the unknown strong interference signal and the parameter characteristics of the strong interference signal have the same frequency, power, amplitude, sampling rate, frequency modulation rate and transmission bit rate, but have opposite phases.
Preferably, the obtaining the separated weak target signal by performing a second blind source separation operation on the obtained weak mixed target signal includes:
determining a second initial point for separating the weakly mixed target signal;
and performing second blind source separation operation on a plurality of weak target signals in the weak mixed target signal by using the determined second initial point to obtain separated weak target signals.
The blind source signal separation device provided by the embodiment of the invention comprises:
the signal separation module is used for performing first blind source separation operation on an unknown strong interference signal in a source mixed signal to obtain parameter characteristics of the unknown strong interference signal, and performing second blind source separation operation on an obtained weak mixed target signal to obtain a separated weak target signal;
the signal recombination module is used for carrying out recombination processing on the unknown strong interference signal according to the parameter characteristics of the obtained unknown strong interference signal to obtain a strong interference cancellation signal for canceling the unknown strong interference signal in the source mixed signal;
and the signal cancellation module is used for carrying out cancellation operation on the unknown strong interference signal in the source mixed signal by using the obtained strong interference cancellation signal to obtain a weak mixed target signal.
Preferably, the first blind source separation refers to a separation process of an unknown strong interference signal in the source mixed signal; the second blind source separation refers to the separation processing of each weak target signal in the weak mixed target signal.
Preferably, the signal separation module includes:
a first signal separation unit, configured to determine a first initial point for separating the source mixed signal, and perform a first blind source separation operation on an unknown strong interference signal in the source mixed signal by using the determined first initial point, so as to obtain a parameter characteristic of the unknown strong interference signal;
wherein the parameter characteristics include characteristics of frequency, power, phase, amplitude, sampling rate, frequency modulation rate, and transmission bit rate.
Preferably, the signal cancellation module is specifically configured to obtain a parameter characteristic of the strong interference cancellation signal, and perform cancellation operation on the unknown strong interference signal in the source mixed signal according to the parameter characteristic of the unknown strong interference signal and the obtained parameter characteristic of the strong interference signal, so as to obtain a weak mixed target signal;
and the parameter characteristics of the unknown strong interference signal and the parameter characteristics of the strong interference signal have the same frequency, power, amplitude, sampling rate, frequency modulation rate and transmission bit rate, but have opposite phases.
Preferably, the signal separation module includes:
and the second signal separation unit is used for determining a second initial point for separating the weak mixed target signals and performing second blind source separation operation on a plurality of weak target signals in the weak mixed target signals by using the determined second initial point to obtain the separated weak target signals.
According to the scheme provided by the embodiment of the invention, the method has the advantages of low calculation complexity, less requirement on prior information of strong interference and good separation performance.
Drawings
Fig. 1 is a flow chart of a method for blind source signal separation according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an apparatus for blind source signal separation according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a blind source signal separation architecture provided by an embodiment of the present invention;
fig. 4 is a schematic structural diagram of cancellation of an unknown strong interference signal in a blind source signal according to an embodiment of the present invention;
fig. 5 is a schematic diagram illustrating channel parameter estimation errors of blind source signals according to an embodiment of the present invention;
fig. 6 is a schematic diagram of blind source signal separation performance provided by an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, and it should be understood that the preferred embodiments described below are only for the purpose of illustrating and explaining the present invention, and are not to be construed as limiting the present invention.
Fig. 1 is a flowchart of a blind source signal separation method according to an embodiment of the present invention, as shown in fig. 1, including:
step S101: performing first blind source separation operation on an unknown strong interference signal in a source mixed signal to obtain parameter characteristics of the unknown strong interference signal;
step S102: according to the parameter characteristics of the obtained unknown strong interference signal, carrying out recombination processing on the unknown strong interference signal to obtain a strong interference cancellation signal for canceling the unknown strong interference signal in the source mixed signal;
step S103: and carrying out cancellation operation on the unknown strong interference signal in the source mixed signal by using the obtained strong interference cancellation signal to obtain a weak mixed target signal, and carrying out second blind source separation operation on the obtained weak mixed target signal to obtain a separated weak target signal.
The first blind source separation refers to separation processing of an unknown strong interference signal in the source mixed signal; the second blind source separation refers to the separation processing of each weak target signal in the weak mixed target signal.
Obtaining the parameter characteristics of the unknown strong interference signal by performing a first blind source separation operation on the unknown strong interference signal in the source mixed signal includes: determining a first initial point for separating the source mix signal; performing first blind source separation operation on an unknown strong interference signal in a source mixed signal by using the determined first initial point to obtain parameter characteristics of the unknown strong interference signal; wherein the parameter characteristics include characteristics of frequency, power, phase, amplitude, sampling rate, frequency modulation rate, and transmission bit rate.
The method for canceling the unknown strong interference signal in the source mixed signal by using the obtained strong interference canceling signal to obtain a weak mixed target signal includes: acquiring parameter characteristics of the strong interference cancellation signal; according to the parameter characteristics of the unknown strong interference signal and the acquired parameter characteristics of the strong interference signal, carrying out cancellation operation on the unknown strong interference signal in the source mixed signal to obtain a weak mixed target signal; and the parameter characteristics of the unknown strong interference signal and the parameter characteristics of the strong interference signal have the same frequency, power, amplitude, sampling rate, frequency modulation rate and transmission bit rate, but have opposite phases.
Obtaining a separated weak target signal by performing a second blind source separation operation on the obtained weak mixed target signal, including: determining a second initial point for separating the weakly mixed target signal; and performing second blind source separation operation on a plurality of weak target signals in the weak mixed target signal by using the determined second initial point to obtain separated weak target signals.
Fig. 2 is a schematic diagram of an apparatus for blind source signal separation according to an embodiment of the present invention, as shown in fig. 2, including: a signal separation module 201, configured to perform a first blind source separation operation on an unknown strong interference signal in a source mixed signal to obtain a parameter characteristic of the unknown strong interference signal, and perform a second blind source separation operation on an obtained weak mixed target signal to obtain a separated weak target signal; a signal recombination module 202, configured to recombine the unknown strong interference signal according to the obtained parameter characteristics of the unknown strong interference signal, so as to obtain a strong interference cancellation signal for canceling the unknown strong interference signal in the source mixed signal; and the signal cancellation module 203 is configured to perform cancellation operation on the unknown strong interference signal in the source mixed signal by using the obtained strong interference cancellation signal, so as to obtain a weak mixed target signal.
The first blind source separation refers to separation processing of an unknown strong interference signal in the source mixed signal; the second blind source separation refers to the separation processing of each weak target signal in the weak mixed target signal.
Wherein the signal separation module 201 comprises: a first signal separation unit, configured to determine a first initial point for separating the source mixed signal, and perform a first blind source separation operation on an unknown strong interference signal in the source mixed signal by using the determined first initial point, so as to obtain a parameter characteristic of the unknown strong interference signal; wherein the parameter characteristics include characteristics of frequency, power, phase, amplitude, sampling rate, frequency modulation rate, and transmission bit rate.
The signal cancellation module 203 is specifically configured to obtain parameter characteristics of the strong interference cancellation signal, and perform cancellation operation on the unknown strong interference signal in the source mixed signal according to the parameter characteristics of the unknown strong interference signal and the obtained parameter characteristics of the strong interference signal, so as to obtain a weak mixed target signal; and the parameter characteristics of the unknown strong interference signal and the parameter characteristics of the strong interference signal have the same frequency, power, amplitude, sampling rate, frequency modulation rate and transmission bit rate, but have opposite phases.
Wherein the signal separation module 201 comprises: and the second signal separation unit is used for determining a second initial point for separating the weak mixed target signals and performing second blind source separation operation on a plurality of weak target signals in the weak mixed target signals by using the determined second initial point to obtain the separated weak target signals.
In the passive radar system, the received source mixed signal comprises a strong interference signal and a weak target signal, wherein the strong signal is an unknown interference signal, and the weak signal is a target signal, which is often encountered in covert communication and practical engineering application.
The signal model of the invention is considered based on a linear instantaneous mixed model of blind source signal separation, the linear instantaneous mixed model is the most common mixed mode in the blind source signal separation, and other complex mixed models can be converted into the linear instantaneous mixed model through certain transformation.
The invention comprises three parts:
firstly, directly carrying out blind source signal separation on mixed signals including unknown strong interference signals by using an optimized FastICA algorithm, and comprising the following steps of:
the method comprises the following steps: and optimizing the initial data by means of a K-means optimization algorithm to obtain an initial point which can enable the blind source signal separation performance to be excellent, so that the blind source signal separation effect is stable.
The invention gives an initial point W0The selection method comprises the following steps:
the K-means optimization algorithm is an important classification method based on data feature classification, and is realized by minimizing the mean square distance between each data and the related data center. The K-means optimization algorithm mainly comprises the following steps:
(1) providing a classification number K;
(2) calculating the mean square distance between each target data and each class, and classifying each target into the nearest class;
(3) minimizing the value of the formula WCSS (Within Cluster Sum of Squares), and updating the Cluster center for each class;
(4) calculating mean square distance based on each new type of target data;
(5) and (4) repeating the step (3) and the step (4) until no target data can be moved.
In the formula, muiIs SiThe mean vector of classes, i ═ 1,2, ·, K.
The output of the K-means optimization algorithm is the mean vector mu of each classi(i ═ 1,2,. K). Mean vector mui(i ═ 1,2,. cndot., K) is both the cluster center for each class and represents a common feature of that class. Thus, from the mean vector μi(i ═ 1,2, ·, K) an initial vector W of the FastICA algorithm (optimized FastICA algorithm) is selected0The method has the advantages of low calculation complexity and good separation performance.
Step two: and (4) performing blind source signal separation by using a FastICA algorithm according to the initial point obtained in the first step.
And performing blind source signal separation on the mixed signal containing the unknown strong interference signal by using the optimized FastICA algorithm to obtain a strong interference mixed signal, and then using the obtained strong interference signal as a known signal to counteract the strong interference by using an interference cancellation method.
And secondly, recombining the interference signals according to the information of the strong interference signals obtained by the separation of the first part as the prior information of the unknown strong interference, and eliminating the unknown strong interference signals in the source mixed signals by using an interference cancellation method.
The method has low calculation complexity, good separation performance and low requirement on prior information of strong interference, and comprises the following steps:
the method comprises the following steps: interference signal recombination technique
In a passive radar system, referring to fig. 3, a source mix signal is composed of a strong unknown interference signal and a weak mix target signal. Since the strong unknown interference signal is too powerful and unknown relative to the weak target mix, the unknown strong interference signal must be reconstructed according to the FastICA algorithm optimized for use.
Step two: interference signal cancellation techniques
And C, according to the interference signal recombined in the step I, canceling the strong interference signal in the mixed signal of the strong interference signal and the weak target mixed signal by using an interference cancellation technology, thereby obtaining the weak target mixed signal.
In FIG. 3, S1+S2+S3+S4+ n is the source mix signal, S1，S2，S3Is a weak target signal, S4Is that a strong interfering signal is not known,
is a strong interference signal recombined by using the optimized FastICA algorithm. The strong interference signal is then cancelled again from the source mix signal according to fig. 4 using interference cancellation.
In FIG. 4, signal aS1+bS2+cS3+dS4+ n is the source mix signal S1+S2+S3+S4Signals generated via a gaussian channel, where n ═ n1,n2,n3,n4]Is background noise, and a ═ a1,a2,a3,a4]，b＝[b1,b2,b3,b4]，c＝[c1,c2,c3,c4]，d＝[d1,d2,d3,d4]Assuming four receiving antennas, four sets of propagated signals l can be received1，l2，l3，l4Then, there are:
dS 'in FIG. 4'4+ n' is the estimated signal of the strong interfering signal obtained by step one, when the strong interfering signal can be considered as a known signal. Due to | d | | S'4| > | | n' | | | so we get:
the strong interference can then be cancelled using the following method:
thus, a useful weak mixing signal can be obtained, written as: y is1,Y2,Y3Then, there are:
the strong interference signal is effectively cancelled by using the interference cancellation algorithm, and the result of the estimation error of the channel parameter of the strong interference signal under the condition of different dry-to-noise ratios is shown in fig. 5. In the context of figure 5, it is shown,the horizontal axis represents the dry-to-noise ratio Sq/N0(ratio of strong interference to background noise), and the vertical axis is the estimation error of the channel parameter of the strong interference signal, and the calculation formula can be composed of two parts:
(1) vector normalization
Suppose the vector is a ═ a (a)1,a2,a3) The normalized vector is:
(2) calculating strong interference signal channel parameter estimation Error
The strong interference signal channel parameter estimation error calculation formula is as follows:
in the formula, vector
Is vector a ═ a1,a2,a3) An estimate of (d).
It can be seen from fig. 5 that the Error value is dependent on the interference-to-noise ratio Sq/N0Is increased and becomes lower.
Thirdly, performing blind source signal separation on the weak target mixed signal again by using the optimized FastICA algorithm in the first step to the weak mixed signal after the unknown strong interference signal is eliminated to obtain a separated weak target signal, wherein the separation performance is shown in FIG. 6. In FIG. 6, the horizontal axis represents the interference-to-signal ratio SqAnd/s, the vertical axis is the Pearson correlation coefficient, and the Pearson correlation coefficient is calculated by the formula:
it can be seen from fig. 6 that the method has better separation performance than the conventional FastICA algorithm, and has low requirement on a priori information of strong interference signals.
According to the scheme provided by the embodiment of the invention, the method has the advantages of low calculation complexity, less requirement on prior information of strong interference and good separation performance.
Although the present invention has been described in detail hereinabove, the present invention is not limited thereto, and various modifications can be made by those skilled in the art in light of the principle of the present invention. Thus, modifications made in accordance with the principles of the present invention should be understood to fall within the scope of the present invention.
Claims (10)
1. A method of blind source signal separation, comprising:
performing first blind source separation operation on an unknown strong interference signal in a source mixed signal to obtain parameter characteristics of the unknown strong interference signal;
according to the parameter characteristics of the obtained unknown strong interference signal, carrying out recombination processing on the unknown strong interference signal to obtain a strong interference cancellation signal for canceling the unknown strong interference signal in the source mixed signal;
and carrying out cancellation operation on the unknown strong interference signal in the source mixed signal by utilizing the obtained parameter characteristics of the strong interference cancellation signal and the obtained parameter characteristics of the unknown strong interference signal to obtain a weak mixed target signal, and carrying out second blind source separation operation on the obtained weak mixed target signal to obtain a separated weak target signal.
2. The method according to claim 1, wherein the first blind source separation refers to a separation process of an unknown strong interference signal in the source mixed signal; the second blind source separation refers to the separation processing of each weak target signal in the weak mixed target signal.
3. The method according to claim 1 or 2, wherein obtaining the parameter characteristic of the unknown strong interference signal by performing a first blind source separation operation on the unknown strong interference signal in the source mix signal comprises:
determining a first initial point for separating the source mix signal;
performing first blind source separation operation on an unknown strong interference signal in a source mixed signal by using the determined first initial point to obtain parameter characteristics of the unknown strong interference signal;
wherein the parameter characteristics include characteristics of frequency, power, amplitude, phase, and transmission bit rate.
4. The method of claim 1, wherein the utilizing the obtained strong interference cancellation signal to perform cancellation operation on the unknown strong interference signal in the source mix signal to obtain a weak mix target signal comprises:
acquiring parameter characteristics of the strong interference cancellation signal;
and the parameter characteristics of the unknown strong interference signal and the parameter characteristics of the strong interference cancellation signal have the same frequency, power, amplitude and transmission bit rate but opposite phases.
5. The method of claim 4, wherein obtaining the separated weak target signal by performing a second blind source separation operation on the obtained weak mixed target signal comprises:
determining a second initial point for separating the weakly mixed target signal;
and performing second blind source separation operation on a plurality of weak target signals in the weak mixed target signal by using the determined second initial point to obtain separated weak target signals.
6. An apparatus for blind source signal separation, comprising:
the signal separation module is used for performing first blind source separation operation on an unknown strong interference signal in a source mixed signal to obtain parameter characteristics of the unknown strong interference signal, and performing second blind source separation operation on an obtained weak mixed target signal to obtain a separated weak target signal;
the signal recombination module is used for carrying out recombination processing on the unknown strong interference signal according to the parameter characteristics of the obtained unknown strong interference signal to obtain a strong interference cancellation signal for canceling the unknown strong interference signal in the source mixed signal;
and the signal cancellation module is used for carrying out cancellation operation on the unknown strong interference signal in the source mixed signal by utilizing the obtained parameter characteristics of the strong interference cancellation signal and the obtained parameter characteristics of the unknown strong interference signal to obtain a weak mixed target signal.
7. The apparatus of claim 6, wherein the first blind source separation refers to a separation process of an unknown strong interference signal in the source mix signal; the second blind source separation refers to the separation processing of each weak target signal in the weak mixed target signal.
8. The apparatus of claim 6 or 7, wherein the signal separation module comprises:
a first signal separation unit, configured to determine a first initial point for separating the source mixed signal, and perform a first blind source separation operation on an unknown strong interference signal in the source mixed signal by using the determined first initial point, so as to obtain a parameter characteristic of the unknown strong interference signal;
wherein the parameter characteristics include characteristics of frequency, power, amplitude, phase, and transmission bit rate.
9. The apparatus of claim 6, wherein the signal cancellation module is specifically configured to obtain a parameter characteristic of the strong interference cancellation signal;
and the parameter characteristics of the unknown strong interference signal and the parameter characteristics of the strong interference cancellation signal have the same frequency, power, amplitude and transmission bit rate but opposite phases.
10. The apparatus of claim 9, wherein the signal separation module comprises:
and the second signal separation unit is used for determining a second initial point for separating the weak mixed target signals and performing second blind source separation operation on a plurality of weak target signals in the weak mixed target signals by using the determined second initial point to obtain the separated weak target signals.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2017101987654 | 2017-03-29 | ||
| CN201710198765 | 2017-03-29 |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107276932A CN107276932A (en) | 2017-10-20 |
| CN107276932B true CN107276932B (en) | 2020-02-21 |
Family
ID=60066016
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710431161.XA Active CN107276932B (en) | 2017-03-29 | 2017-06-09 | Blind source signal separation method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107276932B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109981497B (en) * | 2019-02-22 | 2021-09-03 | 中国人民解放军陆军工程大学 | Pilot pollution elimination method based on blind source separation and angle domain identification |
| CN110213009B (en) * | 2019-07-23 | 2021-08-31 | 电子科技大学 | Safe communication method based on power mixing |
| CN110690937B (en) * | 2019-09-05 | 2023-04-11 | 电子科技大学 | Power-variable safety communication method |
| CN110808926B (en) * | 2019-10-12 | 2022-04-01 | 三维通信股份有限公司 | Interference signal estimation method, apparatus, device and computer readable storage medium |
| CN113671471A (en) * | 2021-08-18 | 2021-11-19 | 中国科学院声学研究所北海研究站 | Underwater sound target detection blind source separation method |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104468436A (en) * | 2014-10-13 | 2015-03-25 | 中国人民解放军总参谋部第六十三研究所 | Communication signal wavelet domain blind source separation anti-interference method and device |
| CN106209715A (en) * | 2016-06-28 | 2016-12-07 | 电子科技大学 | A kind of amplitude modulated jamming suppressing method offseted based on time domain |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7421041B2 (en) * | 2004-03-01 | 2008-09-02 | Qualcomm, Incorporated | Iterative channel and interference estimation and decoding |
-
2017
- 2017-06-09 CN CN201710431161.XA patent/CN107276932B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104468436A (en) * | 2014-10-13 | 2015-03-25 | 中国人民解放军总参谋部第六十三研究所 | Communication signal wavelet domain blind source separation anti-interference method and device |
| CN106209715A (en) * | 2016-06-28 | 2016-12-07 | 电子科技大学 | A kind of amplitude modulated jamming suppressing method offseted based on time domain |
Non-Patent Citations (1)
| Title |
|---|
| A novel blind source separation algorithm and performance analysis of weak signal against strong interference in passive radar system;LI, CJ;《international journal of antennas and propagation》;20161231;第1-10页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107276932A (en) | 2017-10-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107276932B (en) | Blind source signal separation method and device | |
| Ching et al. | On wavelet denoising and its applications to time delay estimation | |
| CN106506430B (en) | A kind of new algorithm of the compensation peak-to-average force ratio non-linear distortion based on compressed sensing technology | |
| CN103778102A (en) | Interference noise matrix reconstitution-based self-adaptive wave beam forming method | |
| Mercorelli | A denoising procedure using wavelet packets for instantaneous detection of pantograph oscillations | |
| CN110187313B (en) | Radar signal sorting and identifying method and device based on fractional order Fourier transform | |
| CN108880713B (en) | Mixed Gaussian spectrum sensing method based on block sparse characteristics | |
| Song et al. | High-resolution time delay estimation algorithms through cross-correlation post-processing | |
| CN108763158B (en) | Time-frequency difference joint calculation method and system | |
| CN113162659A (en) | Power line communication signal denoising method based on power iteration ICA algorithm | |
| Oliinyk et al. | Time delay estimation for noise-like signals embedded in non-Gaussian noise using pre-filtering in channels | |
| CN109558857B (en) | Chaotic signal noise reduction method | |
| Beheshti et al. | Mean square error estimation in thresholding | |
| CN116667920A (en) | Transient signal detection method combining principal component analysis and Hilbert-Huang transform | |
| Washizawa et al. | A flexible method for envelope estimation in empirical mode decomposition | |
| Robinson | A topological low-pass filter for quasi-periodic signals | |
| CN112883787B (en) | Short sample low-frequency sinusoidal signal parameter estimation method based on spectrum matching | |
| CN102509268B (en) | Immune-clonal-selection-based nonsubsampled contourlet domain image denoising method | |
| Deng et al. | Single-channel blind signal separation method for time-frequency overlapped signal based on CEEMD-FastICA | |
| Oliinyk et al. | Center weighted median filter application to time delay estimation in non-Gaussian noise environment | |
| US10958302B1 (en) | Signal cueing using an IIR filter array with inverted state tree | |
| CN111884967B (en) | QPSK signal demodulation method based on time-frequency analysis and convolutional neural network | |
| Li et al. | PCA based Hurst exponent estimator for fBm signals under disturbances | |
| Roienko et al. | An Overview of the Adaptive Robust DFT and it’s Applications | |
| CN109412718A (en) | Broader frequency spectrum signal detecting method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |