CN106599531B - A kind of single channel multicycle signal aliasing situation estimation method of lower signal period - Google Patents
A kind of single channel multicycle signal aliasing situation estimation method of lower signal period Download PDFInfo
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Abstract
The invention discloses a kind of single channel multicycle signal aliasing situation estimation methods of lower signal period, comprising steps of acquiring single channel multicycle aliasing signal prolonged enough, and are stored as digital signal；The aliasing signal is modeled；The combination of possible period for traversing all signals reconstructs multicycle aliasing signal under the conditions of the combination of each period；The period combination of the smallest one group of signal of target function value is found out in the combination of all periods, this group of signal period combination is the period of each signal.The beneficial effects of the present invention are compared with prior art, have easy to accomplish, feature easy to operate, the period of Overlapped Periodic Signals is pre-estimated using the method for the present invention, provides cycle information for the Blind Signal Separation of next stage, is conducive to improve blind separation efficiency.
Description
Technical field
The present invention relates to signals under electronic information counted fields more particularly to a kind of single channel multicycle signal aliasing situation
Phase estimate method.
Background technique
Blind separation (Blind Source Separation, BSS) is field of signal processing one research for being rich in challenge
Project.Since blind separation is logical in speech recognition, signal denoising, wireless telecommunications, sonar problem, processing of biomedical signals, optical fiber
Numerous application fields such as letter have extensive and tempting application prospect, and blind separation is from the beginning at field of signal processing and mind
Research hotspot through network field.
Single channel blind separation is the extreme situation of one kind of blind separation, is to realize multiple time-frequencies according to single channel mixed signal
The separation of aliasing signal.Containing multiple signals in reality, in the signal that single channel receives is a very universal phenomenon:
In processing of biomedical signals, biomedicine signals generally comprise multiple electricity physiological signal ingredients, as removed brain in electroencephalogram
The outer past contact of electric signal includes that electrocardio is dynamic, eye movement artefact, interference signal caused by flesh point signal and other interference sources；
In a communications system, there are co-channel interferences etc.；In radar, Sonar system, the signal received is multiple with different propagation
Delay and decline echo and superposition.
Since number of active lanes is less than signal number, cause to can get information content deficiency, single channel signal separation becomes especially
It is difficult.It excavates and is currently to solve the problems, such as an important method of single channel blind separation using the priori knowledge of targeted problem.
In real world, many physical signals inherently have periodically or can be approached by periodic signal.It is mixed using single channel
Periodically this property of signal is conducive to the separation of subsequent multiple signals in folded signal.
Summary of the invention
In order to overcome the deficiencies of the prior art, the present invention proposes a kind of single channel multicycle signal aliasing situation lower signal period
Estimation method.
The technical scheme of the present invention is realized as follows:
A kind of single channel multicycle signal aliasing situation estimation method of lower signal period, including step
S1: acquisition single channel multicycle aliasing signal prolonged enough, and it is stored as digital signal；
S2: the aliasing signal is modeled；
S3: the combination of possible period for traversing all signals reconstructs multicycle aliasing under the conditions of the combination of each period
Signal；
S4: the period combination of the smallest one group of signal of target function value, this group of signal week are found out in the combination of all periods
Phase combination is the period of each signal.
Further, the method for the modeling of aliasing signal described in step S2 are as follows:
If N is signal sampling points, F is sample frequency, and t is the sampling time, indicates that single channel aliasing is believed with sampling number N
The sampling time of number x, with each signal s1,s2...,snSampling number T in one cycle1,T2,...,TnIndicate the week of signal
Phase, wherein n is the number of signal, then aliasing signal x may be expressed as:
Wherein, For signal siMonocycle signal,A=[A1 A2 ...
An], IiIt is T for dimensioniThe unit matrix of (i=1,2 ..., n).
Further, the method that multicycle aliasing signal is reconstructed in step S3 is minimal square error method, objective function
Are as follows:
The beneficial effects of the present invention are compared with prior art, have feature easy to accomplish, easy to operate, utilize
The method of the present invention pre-estimates the period of Overlapped Periodic Signals, provides cycle information for the Blind Signal Separation of next stage, has
Conducive to raising blind separation efficiency.
Detailed description of the invention
Fig. 1 is single channel multicycle signal aliasing situation estimation method of lower signal period flow chart of the present invention.
Fig. 2 is one embodiment of the invention two-way period aliasing signal schematic diagram.
Fig. 3 is a single channel periodic signal of the aliasing signal after present invention reconstruct in Fig. 2.
Fig. 4 is another single channel periodic signal of aliasing signal after present invention reconstruct in Fig. 2.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Referring to Figure 1, phase estimate method of the invention including the following steps:
S1: acquisition aliasing signal prolonged enough, and it is stored as digital signal, if aliasing signal has been several
Word signal, then the step for skipping；
S2: aliasing signal is modeled.Present invention assumes that single channel aliasing signal x is by n periodic signal s1,s2...,sn
Linear superposition forms, and shares N number of sampled point x (t), t=1 ..., N.Periodic signal s1,s2...,snAdopting in one cycle
Number of samples is respectively T1,T2,...,Tn,For periodic signal siMonocycle signal, then aliasing signal can be expressed as
Wherein,A=[A1 A2... An],IiIt is T for dimensioniThe list of (i=1,2 ..., n)
Position battle array.
S3: traversing the combination of possible period of all signals, following excellent by solving under the conditions of the combination of each period
Change problem reformulation aliasing signal:
In formulaMatrixFor the pseudo inverse matrix of A, the reconstruct of aliasing signal
S4: the period combination of the smallest one group of signal of target function value, as each signal are found out in the combination of all periods
Period.Objective function is defined as follows:
The two-way periodic signal used is emulated as shown in Fig. 2, s1It is the periodic signal for being 7 sampled points in the period, s2It is the period
For the periodic signal of 5 sampled points, x=s1+s2For aliasing signal, the sampling number N=100 of signal.Assuming that known signal s1,
s2Possible periodic regime is 2~50 sampled point each periods, and signal s1Cycle T1Greater than signal s2Cycle T2, i.e. T1
> T2.The combination in all possible period is traversed, totally 1176 kinds of possible combinations.Each corresponding period combines (T1,T2), I
Carry out the reconstruct of aliasing signal by solving following optimization problem,
Wherein,A=[A1 A2],I1It is T for dimension1Unit matrix, I2It is T for dimension2List
Position battle array.The optimal solution for easily acquiring above-mentioned objective function isMatrixFor the pseudo inverse matrix of A.Therefore the weight of aliasing signal
StructureAliasing signal in Fig. 2 reconstructs latter two single channel periodic signal such as Fig. 2 and Fig. 3 institute through the present invention
Show.
On the basis of step S3 has acquired reconstruction signal, following optimization problem is solved:
Wherein,(T is combined in the period for aliasing signal x1,T2) when reconstruction signal.Above-mentioned objective function is not only
The reconstructed error of aliasing signal is measured, and requiring the period of each signal is minimum positive period.(T is combined when the period1,T2)=(7,
5) or when its multiple, reconstruction signal can be fitted aliasing signal well, but work as T1=7, T2When=5, T1+T2=12；And work as T1
=14, T2When=5, T1+T2=19,12 < 19, so above-mentioned objective function final choice T1=7, T2=5 week as signal
Phase.
The above is a preferred embodiment of the present invention, it is noted that for those skilled in the art
For, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also considered as
Protection scope of the present invention.
Claims (1)
1. a kind of single channel multicycle signal aliasing situation estimation method of lower signal period, which is characterized in that including step
S1: acquisition single channel multicycle aliasing signal prolonged enough, and it is stored as digital signal；
S2: the aliasing signal is modeled；
S3: traversing the combination of possible period of all signals, under the conditions of the combination of each period, reconstruct multicycle aliasing letter
Number；
S4: the period combination of the smallest one group of signal of target function value, this group of signal period group are found out in the combination of all periods
Close the period of as each signal；
The method of the modeling of aliasing signal described in step S2 are as follows:
If N is signal sampling points, F is sample frequency, and t is the sampling time, indicates single channel aliasing signal x with sampling number N
Sampling time, with each signal s1,s2...,snSampling number T in one cycle1,T2,...,TnIndicate the period of signal,
Wherein, n is the number of signal, then aliasing signal x may be expressed as:
Wherein, For signal siMonocycle signal,IiFor
Dimension is TiThe unit matrix of (i=1,2 ..., n)；
The method that multicycle aliasing signal is reconstructed in step S3 is minimal square error method, is reconstructed by solving following optimization problem
Aliasing signal:
In formulaMatrixFor the pseudo inverse matrix of A, the reconstruct of aliasing signal
Objective function is defined as follows in step S4:
The objective function not only measures the reconstructed error of aliasing signal, but also requiring the period of each signal is minimum positive period.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1609843A (en) * | 2004-11-24 | 2005-04-27 | 南京大学 | An estimating method for periodic signal period under strong background noise |
| CN101853240A (en) * | 2009-03-31 | 2010-10-06 | 华为技术有限公司 | Signal period estimation method and device |
| CN102288285A (en) * | 2011-05-24 | 2011-12-21 | 南京航空航天大学 | Blind source separation method for single-channel vibration signals |
| CN102299894A (en) * | 2011-09-30 | 2011-12-28 | 重庆邮电大学 | Superimposed-periodic-sequence-based channel estimation method for asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) wireless optical communication system |
-
2016
- 2016-10-28 CN CN201610961190.2A patent/CN106599531B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1609843A (en) * | 2004-11-24 | 2005-04-27 | 南京大学 | An estimating method for periodic signal period under strong background noise |
| CN101853240A (en) * | 2009-03-31 | 2010-10-06 | 华为技术有限公司 | Signal period estimation method and device |
| CN102288285A (en) * | 2011-05-24 | 2011-12-21 | 南京航空航天大学 | Blind source separation method for single-channel vibration signals |
| CN102299894A (en) * | 2011-09-30 | 2011-12-28 | 重庆邮电大学 | Superimposed-periodic-sequence-based channel estimation method for asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) wireless optical communication system |
Non-Patent Citations (6)
| Title |
|---|
| Blind Deconvolution Algorithm For MIMO Channel;Zhao Min et al;《International Conference on Computational Intelligence and Security》;20081217;470-474 |
| On blind separability based on the temporal predictability method;Xie shengli et al;《 Neural Computation》;20091231;第21卷(第12期);3519-3531 |
| 一种单通道的周期性信号盲分离算法;王荣杰等;《集美大学学报（自然科学版）》;20140131;第19卷(第1期);75-80 |
| 单通道时频混叠通信信号的分离算法研究;李玉芬;《万方学位论文库》;20160129;第2章 |
| 基于QR分解的盲源分离几何算法;何昭水等;《控制理论与应用》;20050228;第22卷(第1期);17-22 |
| 多个源信号混叠的盲分离几何算法;章晋龙等;《计算机学报》;20050930;第28卷(第9期);1575-1581 |
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