CN109639303A - A kind of Interference Detection and suppressing method based on windowing process - Google Patents
A kind of Interference Detection and suppressing method based on windowing process Download PDFInfo
- Publication number
- CN109639303A CN109639303A CN201811638158.6A CN201811638158A CN109639303A CN 109639303 A CN109639303 A CN 109639303A CN 201811638158 A CN201811638158 A CN 201811638158A CN 109639303 A CN109639303 A CN 109639303A
- Authority
- CN
- China
- Prior art keywords
- windowing process
- signal
- interference
- sequence
- digital signal
- 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.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
- H04B1/06—Receivers
- H04B1/10—Means associated with receiver for limiting or suppressing noise or interference
- H04B1/1027—Means associated with receiver for limiting or suppressing noise or interference assessing signal quality or detecting noise/interference for the received signal
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
- H04B1/06—Receivers
- H04B1/10—Means associated with receiver for limiting or suppressing noise or interference
- H04B1/1027—Means associated with receiver for limiting or suppressing noise or interference assessing signal quality or detecting noise/interference for the received signal
- H04B1/1036—Means associated with receiver for limiting or suppressing noise or interference assessing signal quality or detecting noise/interference for the received signal with automatic suppression of narrow band noise or interference, e.g. by using tuneable notch filters
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
- H04B1/06—Receivers
- H04B1/16—Circuits
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Noise Elimination (AREA)
Abstract
The invention discloses a kind of Interference Detection and suppressing method based on windowing process.The method comprising the steps of frequency-domain transform, Interference Detection, AF panel and time domain transformation, overlapping windowing process has wherein been carried out after frequency-domain transform, it has then carried out going overlap processing after time domain transformation, in addition it can including carrying out ambient noise estimation to transformed frequency domain digital signal and adaptive determining interference detection threshold in Interference Detection, the accuracy to interferer signal detection is improved, the noise specific loss of windowing process bring is thus also reduced.This method is versatile, especially suitable for the interferer signal detection in satellite communication, microwave communication.
Description
Technical field
The present invention relates to signal of communication processing technology fields, more particularly to are based on windowing process for one kind of interference signal
Interference Detection and suppressing method.
Background technique
In the radio communications such as satellite communication, mobile communication, signal of communication is often mixed into when receiving end receives
Various interference signals are conducive to be properly received signal of communication to detecting and eliminating for these interference signals.
In the prior art, it will appear the noise specific loss to signal of communication to interferer signal detection and during eliminating, with
And due to cannot accurate estimating background noise comprising and cause to be difficult to being optimal to the thresholding setting of Interference Detection.
Summary of the invention
The invention mainly solves the technical problem of providing a kind of Interference Detection and suppressing method based on windowing process, solution
Certainly in the prior art to interference signal the problems such as detecting and eliminating existing ambient noise detection inaccuracy, signal-to-noise ratio reduction.
In order to solve the above technical problems, one technical scheme adopted by the invention is that providing a kind of dry based on windowing process
Disturb detection and suppressing method, comprising the following steps: frequency-domain transform, the signal of communication for being mixed with interference signal first pass through AD sampler
It is transformed to input time-domain digital signal, is frequency using FFT transform after carrying out windowing process to the input time-domain digital signal
Domain digital signal;Interference Detection carries out ambient noise estimation to frequency domain digital signal, then determines interference detection threshold;Interference
Inhibit, the component that the interference detection threshold is greater than in the frequency domain digital signal is then considered interference signal component, to described
Interference signal component carries out inhibition processing;Time domain converts, and after interference signal component is suppressed in the frequency domain digital signal, then passes through
IFFT transformation is crossed, output time-domain digital signal is reduced to.
The present invention is based in the Interference Detection of windowing process and another embodiment of suppressing method, the windowing process is used
Window function include using bartlett window, Hanning window, Hamming window, Blackman window or Blackman-Karris window to institute
It states input time-domain digital signal and carries out windowing process.
The present invention is based in the Interference Detection of windowing process and another embodiment of suppressing method, the input time-domain digital
Signal is sequence x (k):
X (k)=Ap (k)+n (k)
Wherein, p (k) is the PN sequence of equiprobability value ± l, and the length is N;N (k) be mean value be zero, variance is's
Gaussian sequence, A are the amplitude of signal of communication;
Windowing process is carried out to x (k), window function is w (k), the sequence after adding window are as follows:
xw(k)=Ap (k) w (k)+n (k) w (k).
The present invention is based in the Interference Detection of windowing process and another embodiment of suppressing method, the windowing process is attached most importance to
Folded windowing process, it is corresponding that overlapping is carried out to the time-domain digital signal of IFFT transformation output in time domain transformation
Reason.
The present invention is based in the Interference Detection of windowing process and another embodiment of suppressing method, the input time-domain digital
For the data sequence of signal by equal equal segments, the length of each data segment is N, when being overlapped windowing process, front and back adjacent data section
Coincidence length be Nr, r (0≤r < 1) be overlap factor.
The present invention is based in the Interference Detection of windowing process and another embodiment of suppressing method, the overlap factor r=
1/2, the input time-domain digital signal is sequence x (k)=Ap (k)+n (k), wherein p (k) is the PN sequence of equiprobability value ± l
Column, the length is N;N (k) be mean value be zero, variance isGaussian sequence, A be signal of communication amplitude;
Overlapping windowing process after output sequence be
Wherein,W (k) is window function.
The present invention is based in the Interference Detection of windowing process and another embodiment of suppressing method, the overlap factor r=
1/2, the input time-domain digital signal is sequence x (k)=Ap (k)+n (k), wherein p (k) is the PN sequence of equiprobability value ± l
Column, the length is N;N (k) be mean value be zero, variance isGaussian sequence, A be signal of communication amplitude;
Overlapping windowing process after output sequence be
Wherein,W (k) is window function.
The present invention is based in the Interference Detection of windowing process and another embodiment of suppressing method, the input time-domain digital
Signal is divided into two-way list entries, and first via list entries is after windowing process, using FFT transform, Interference Detection, interference
Inhibit and obtain first via output sequence after IFFT transformation, the second road list entries carries out at adding window again after first passing through N/2 delay
Reason, then also over obtaining the second road output sequence after FFT transform, Interference Detection, AF panel and IFFT transformation, described first
Road output sequence obtains the output time-domain digital signal after being added with the second road output sequence.
The beneficial effects of the present invention are: the invention discloses a kind of Interference Detection and suppressing method based on windowing process.
The method comprising the steps of frequency-domain transform, Interference Detection, AF panel and time domain transformation, is wherein weighed after frequency-domain transform
Folded windowing process has then carried out going overlap processing, in addition it can include to change in Interference Detection after time domain transformation
Frequency domain digital signal after changing carries out ambient noise estimation and adaptive determining interference detection threshold, improves and examines to interference signal
Thus the accuracy of survey also reduces the noise specific loss of windowing process bring.This method is versatile, especially suitable in satellite
Interferer signal detection in communication, microwave communication.
Detailed description of the invention
Fig. 1 is the principle composition figure of one embodiment of the Interference Detection based on windowing process and suppressing method according to the present invention;
Fig. 2 is the flow chart of the Interference Detection based on windowing process and another embodiment of suppressing method according to the present invention;
Fig. 3 is according to the present invention at the overlapping adding window of the Interference Detection based on windowing process and another embodiment of suppressing method
Reason composition figure;
Fig. 4 is according to the present invention at the overlapping adding window of the Interference Detection based on windowing process and another embodiment of suppressing method
Manage explanatory diagram;
Fig. 5 is according to the present invention at the overlapping adding window of the Interference Detection based on windowing process and another embodiment of suppressing method
Manage schematic diagram;
Fig. 6 is the flow chart of the Interference Detection based on windowing process and another embodiment of suppressing method according to the present invention;
Fig. 7 is the AF panel door of the Interference Detection based on windowing process and another embodiment of suppressing method according to the present invention
Limit and bit error rate relation figure;
Fig. 8 is the sunken amplitude and mistake of the Interference Detection based on windowing process and another embodiment of suppressing method according to the present invention
Code rate relational graph;
Fig. 9 is the adding window degree of overlapping of the Interference Detection based on windowing process and another embodiment of suppressing method according to the present invention
With bit error rate relation figure;
Figure 10 is that the principle of the Interference Detection based on windowing process and another embodiment of suppressing method forms according to the present invention
Figure.
Specific embodiment
To facilitate the understanding of the present invention, in the following with reference to the drawings and specific embodiments, the present invention will be described in more detail.
A better embodiment of the invention is given in the attached drawing.But the invention can be realized in many different forms, and unlimited
In this specification described embodiment.On the contrary, purpose of providing these embodiments is makes to the disclosure
Understand more thorough and comprehensive.
It should be noted that unless otherwise defined, all technical and scientific terms used in this specification with belong to
The normally understood meaning of those skilled in the art of the invention is identical.Used term in the description of the invention
It is the purpose in order to describe specific embodiment, is not intended to the limitation present invention.Term "and/or" packet used in this specification
Include any and all combinations of one or more related listed items.
In conjunction with Fig. 1 schematic diagram and Fig. 2 flow chart, open the present invention is based on the Interference Detections of windowing process and suppressing method one
The flow chart of embodiment.The method comprising the steps of:
First step S101: frequency-domain transform, the signal of communication for being mixed with interference signal first pass through AD sampler and are transformed to input
Time-domain digital signal, the input time-domain digital signal are transformed to frequency domain digital signal after FFT transform;
Second step S102: Interference Detection carries out ambient noise estimation to frequency domain digital signal, then determines Interference Detection door
Limit;
Third step S103: AF panel, the component that the interference detection threshold is greater than in the frequency domain digital signal are then recognized
To be interference signal component, inhibition processing is carried out to the interference signal component, to eliminate interference signal energy.
Here, the interference signal component for detecting, it is necessary to the amplitude of interference signal component is modified, also referred to as
Be threshold process, this process handle interference while loss inevitably can be brought to useful signal of communication, lead
Output signal-to-noise ratio is caused to reduce.
4th step S104: time domain converts, after interference signal component is suppressed in the frequency domain digital signal, using IFFT
Transformation, is reduced to output time-domain digital signal.
Preferably, windowing process also is carried out to the input time-domain digital signal before first step S101 frequency-domain transform.
Here, it is a critically important improvement by windowing process, if not windowing process, carries out the FFT operation of N point just
It is equivalent to the rectangular window for having added a N point, its first secondary lobe is only 13dB lower than main lobe, i.e., Sidelobe Suppression degree only has -13dB, right
For the interference signal of tens dB bigger than signal of communication, its secondary lobe is also more much bigger than signal of communication.In this way from the point of view of frequency domain,
Entire signal of communication frequency domain is all disturbed to be polluted.Therefore it needs to carry out windowing process, assembles the main lobe of signal of communication more
Energy, sidelobe magnitudes reduce.From time domain, windowing process is exactly to be weighted to input data, and window function coefficient is from center
Gradually decay to both ends, guarantees that data segment both ends are smooth, to reduce spectrum leakage.But it since window function is decayed to both ends, leads
It causes input signal to be distorted, additional snr loss can be brought.
Preferably, x (k) is the time-domain digital signal sequence of input:
X (k)=Ap (k)+n (k)
Wherein, p (k) is the PN sequence of equiprobability value ± l, the length is N, shows the sequence for Direct Sequence Spread Spectrum letter
Number;N (k) be mean value be zero, variance isGaussian sequence, A is signal amplitude.
Windowing process is carried out to x (k), window function is w (k), the sequence after adding window:
xw(k)=Ap (k) w (k)+n (k) w (k)
To xw(k) it carries out the coherently despreading that length is N and integrates:
The mean value and variance of sequence z:
Sequence signal-to-noise ratio after adding window are as follows:
The not correlation output signal-to-noise ratio of adding window are as follows:
So adding window bring snr loss are as follows:
As it can be seen that the loss of signal-to-noise ratio is related with the coefficient of window function, different window function bring snr loss is different.
Table 1 gives the characteristic for commonly using several window functions and its caused snr loss, while also compared each window letter
Several opposite side lobe peak amplitudes and main lobe bandwidth.In given length, the main lobe of rectangular window is most narrow, but its opposite sidelobe magnitudes
It is maximum.From top to bottom, the main lobe of various windows broadens, and opposite sidelobe magnitudes become smaller.
1 window function fundamental characteristics of table and caused snr loss
It is a limited number of by selecting the lower window function of secondary lobe that can be limited to most of energy of narrow-band interference signal
Within root spectral line, to reduce the radical for needing the spectral line inhibited, farthest reduce influence of the interference to useful signal;Together
The lesser main lobe broadband Shi Xuanyong can reduce the distortion of useful signal.
The selection of window function needs to consider the compromise of side lobe attenuation and main lobe broadband in practical application.The lower window letter of secondary lobe
Number, main lobe is wider, and it is also bigger to the damage of useful signal while interference to inhibit narrowband, therefore when selecting window function, to tie
It closes the dynamic range of the reception signal of receiver and the intensity for needing that narrowband is inhibited to interfere selects suitable window function.
It is further preferred that needing to carry out the frequency domain digital signal in order to compensate for noise specific loss caused by adding window
It is overlapped windowing process.Windowing process is overlapped to increase computational complexity as cost, advantage is the damage for reducing adding window to signal-to-noise ratio
Consumption.Also, influence the fenestrate type function of principal element of noise specific loss, window length, adding window degree of overlapping.
From the point of view of the selection of window function type, when low due to the secondary lobe relative amplitude of window function, main lobe bandwidth is wider, needs to locate
The frequency point of reason is more, and secondary lobe relative amplitude is high when main lobe narrow bandwidth, and spectral leakage is serious, and contaminated frequency point is more, therefore
When selecting window function, the intensity for the narrow-band interference signal that the dynamic range for receiving signal and needs inhibit, selection are considered
Suitable window function reduces the loss to signal-to-noise ratio.And for adding window degree of overlapping, adding window overlap proportion is bigger, damages to signal-to-noise ratio
Consume smaller, but implementation complexity is big and hardware resource consumption is more, and need to compromise consideration.
It is further corresponding with overlapping windowing process in conjunction with Fig. 3, it is preferred that after the transformation of the 4th step S104 time domain also
Overlap processing is carried out to output time-domain digital signal.
Windowing process will cause the distortion of useful signal, in order to compensate for noise specific loss caused by adding window, to input data
Carry out overlapping adding window.Assuming that the data length that signal sequence is segmented into is N, overlap factor r (0≤r < 1), overlapping adding window is former
Reason is as shown in Figure 4.Here the data sequence inputted after adding window is segmented, and each section of data length is N, and is worked as and be overlapped
When, the length of every one piece of data is also N, but two segment data of front and back has coincidence, and being overlapped length is Nr.Therefore, when to letter
After number carrying out overlapping adding window, another question in need of consideration is how two paths of data to be synthesized a circuit-switched data as finally
Export result.
Preferably, there are two types of methods for overlapping windowing process: back-and-forth method and additive process.By taking 1/2 overlapping adding window as an example, back-and-forth method
It is 1/2 piece of data of the window center of the road Qu Mei signal, gives up each 1/4 piece of data of the right and left, by 1/2 piece of upper and lower two-way
Data form a complete data sequence.Sum rule is to be added the lap of two segment datas to believe as final output
Number.
Lower surface analysis overlap factor is the snr loss of the back-and-forth method and additive process overlapping output in the case of 1/2.It is preferred that
, the output sequence under the back-and-forth method way of output, after being overlapped adding window are as follows:
Wherein
w1It (k) is the lower signal weighting value of back-and-forth method output, by the derivation result of snr loss it is found that back-and-forth method output
Snr loss under mode are as follows:
Preferably, the output sequence under the additive process way of output, after being overlapped adding window are as follows:
Wherein
w2(k) be additive process output under signal weighting value, the snr loss of additive process such as following formula:
Table 2 gives the output of the back-and-forth method under different overlap factors and additive process exports bring snr loss feelings
Condition.
The letter to credit ratio of 2 two kinds of Data Synthesis mode difference overlap factors of table is lost
As known from Table 2, when overlap factor is identical, additive process is smaller than back-and-forth method bring signal-to-noise ratio, this species diversity can be from
Time domain is intuitively explained.In view of hardware realization, output is added than selection and exports more N × r sub-addition operations;For non-square
For shape window, theoretically, continuous two segment datas overlap proportion is bigger, and smaller, corresponding operand is lost in the adding window of introducing
It is bigger, it is not easy to realize, the selection of overlap proportion depends on hardware condition and the requirement of system design performance in practical application.
Preferably, the overlap factor of selection is 1/2 additive process Data Synthesis mode, the interference based on overlapping windowing process
Detection and another embodiment of suppressing method are as shown in figure 5, the input time-domain digital signal is divided into two-way list entries, the first via
List entries x (n) is after windowing process, using obtaining the after FFT transform, Interference Detection, AF panel and IFFT transformation
Output sequence all the way, the second road list entries first passes through N/2 delay x (n+N/2) and carries out windowing process again, then also over FFT
The second road output sequence, the first via output sequence and second are obtained after transformation, Interference Detection, AF panel and IFFT transformation
Road output sequence obtains the output time-domain digital signal after being added.Here, the first via is the waveform after one-channel signal adding window, the
Two tunnels are signal x (n) waveforms after N/2 postpones adding window.The data fidelity of window center be it is highest, closer to window two
End is distorted more serious.But two paths of signals is complementary, wherein distortion most serious place can use benefit of in addition coming all the way
It repays.Useful signal can preferably be restored by being overlapped adding window when interference carries out IFFT transformation after eliminating by time domain.Preferably, it selects
The Blackman for being N=1024 with length is overlapped adding window to verify the effect that overlapping adding window reduces distorted signals, overlap factor 1/
2, overlapping adding window number is 2.
It is further preferred that ambient noise estimation is the fundamental prerequisite of Interference Detection, if background is made an uproar in Interference Detection
Acoustical power size isFFT is after windowing process, then the component of interfering frequency concentrates in main lobe.If interference signal
The non-seizing signal bandwidth of frequency band more than half, and useful signal of communication very little and be submerged in noise, so not interfering with
Frequency band in mainly white Gaussian noise frequency component.Mathematic expectaion is zero, and variance isStable Gaussian band-limited noise,
The one-dimensional distribution of envelope is Rayleigh distributed.Because the frequency component of white Gaussian noise is Normal Distribution, variance isSo the amplitude Rayleigh distributed of frequency component, can obtain entire frequency component according to the statistical property of rayleigh distributed
The mean value of amplitude, and ambient noise frequency domain components amplitude side is estimated by the mean value of rayleigh distributed and the relationship of Variance of Normal Distribution
Poor size, and the size of time domain variance namely the size of Background Noise Power have just been obtained according to the property of Fourier transformation.
Here, if the amplitude x Rayleigh distributed of the frequency component of white Gaussian noise, then its probability density function:
The probability-distribution function of amplitude x:
The mean value of amplitude x are as follows:
Taking proportion from small to large is 1/2 frequency component data, F (A)=1/2 is enabled, if in the acquirement point of frequency domain
There are many number, then selecting half smallest point, then can fall in section [0, A].Mean value of the variable x on section [0, A] can be calculated,
It is denoted as μ1, the as mean value of frequency component half smallest point compares μ and μ1, both available relationship, and then can be
The mean value of entire frequency component is derived in practical application from undisturbed frequency component.As F (A)=1/2, obtainμ1Are as follows:
Relationship u/u between frequency component half smallest point mean value and the mean value of entirety1=3.4328, that is, obtaining μ1Afterwards
μ can be calculated multiplied by 3.4328.So showing that the mean value of entire frequency component is frequency component by the statistical property of rayleigh distributed
3.4328 times of half smallest point mean value.
Further according to the mean value of rayleigh distributedσFFor the mean square deviation of frequency component normal distribution, according toObtain Background Noise Power.
Therefore μ can be first found out, then finds out μ1, then find out σF, finally find outSo far, ambient noise is completed
Estimation.
It is further preferred that the quality of the threshold scheme of Interference Detection directly affects interference free performance, interference detection threshold
Design be the key that entire Interference Detection and elimination.On the one hand, interference and signal in practice is all time-varying, so interference
Detection threshold should not be fixed and invariable, and selecting for thresholding should be to receive the statistical property of signal as foundation.On the other hand,
For the disadvantage for overcoming Threshold detection algorithm not strong to environmental suitability, it is desirable to be able to the interference of dynamic self-adapting multi-threshold Interference Detection
Signal.
Preferably, by counting to the X (k) after input time-domain digital signal progress FFT transform, mean value is obtainedAnd mean square errorN is spectral line number, ζnFor the amplitude of corresponding spectral line.In turn
It determines interference threshold, filters off the interference signal for being higher by thresholding.Wherein the threshold de of first moment algorithm is Th=θ μ, and θ is interference
The optimized coefficients of detection threshold.The threshold de of second moment algorithm is Th=μ+β * σ, and β is thresholding Optimization Factor, can be according to difference
Channel circumstance situations such as (such as decline, multidiameter) concentrate and choose from preset weighted factor.
When inputting in time-domain digital signal there are when the interference signal that power is much larger than spread-spectrum signal and ambient noise, pass through
FFT transform exports there are the subband of interference and is unsatisfactory for Gaussian Profile, and the subband output power polluted by strong jamming is much larger than quilt
The subband of weak jamming pollution or not disturbed pollution, causes the missing inspection that part is disturbed subband, so that output judgment variables
Signal-to-noise ratio becomes smaller, and error rate of system increases.In addition, common Interference Detection algorithm is not strong to the adaptability of environment, choose every time
Threshold value all needs in advance the characteristics of to channel, interference and signal to pre-estimate situations such as multidiameter, decline in transmission process.
Adaptive threshold needs to meet two conditions, first is that adaptive threshold value should when not interfering with signal
Higher than the spectral line of most signals of communication, the spectral line of useful signal of communication cannot be handled as interference, make false-alarm probability
It is minimum;Second is that adaptive threshold value should be lower than the spectral line of all interference signals when having interference signal, and it is higher than exhausted
The spectral line of most of signals of communication keeps detection probability maximum.
To meet the two conditions, the distribution of spectral line is analyzed first.Assuming that input time-domain digital signal is x (n)
=s (n)+n (n), s (n) are signal, and n (n) is noise.Here Adaptive multi-threshold interference detection method is thought to receive signal
In desired signal s (n) flooded by interchannel noise n (n), such as be directed to Direct Sequence Spread Spectrum Signal.N point sequence x's (n)
DFT is defined as:
According to the property of Fourier transformation, the spectral line of output is X (k)=S (k)+N (k), and S (k) is N point sequence s's (n)
DFT, N (k) are the DFT of N point sequence n (n).The DFT transform can also be realized by FFT transform.In glitch-free situation,
|X(k)|2=| S (k)+N (k) |2The exponential distribution that parameter is λ is obeyed, is hadIf from
Adaptation threshold value is Th, then | X (k) |2The Probability p lower than threshold T h are as follows:
It can be calculated, as Th=1/ λ, p=0.6321;As Th=2/ λ, p=0.8647;As Th=3/ λ,
P=0.9502;As Th=4/ λ, p=0.9817;As Th=5/ λ, p=0.9933.
Assuming that output signal is formed by stacking by useful signal of communication with noise, then according to above-mentioned analysis, discrete fourier
N root spectral line amplitude square should obey the exponential distribution that parameter is λ after transformation.In the case where state no interference signal, N root breadth of spectral line
The probability square less than 5/ λ of degree is 0.9933, i.e., the probability greater than 5/ λ is only 0.0067.It is considered that width in N root spectral line
The spectral line square greater than 5/ λ of degree is almost to be not present.If that with the presence of interference, it is believed that discrete fourier
After transformation the spectral line square greater than 5/ λ of spectral line amplitude be containing noisy spectral line, using zero or clamped algorithm to interfere into
Row processing.
But found in actual test, when thresholding is scheduled on 5/ λ of theoretical optimal value, although signal of communication as interfere into
The probability of row processing is almost nil, i.e., false-alarm probability is minimum.But after carrying out clamped process to strong jamming, the effect of AF panel
Fruit is simultaneously not thorough, in addition, can decline to the detection probability of weak jamming.Therefore from false-alarm probability, strong jamming inhibitory effect and weak
The composite factors such as Interference Detection probability are set out, and it is a selection for compromise that thresholding, which is scheduled on 3/ λ,.So if known N point list entries
The discrete Fourier transform of x (n) is X (k), then in practical applications, when the points N of DFT transform is larger, assembly average
The estimated value of 1/ λ can be replaced with the mean value of breadth of spectral line degree quadratic sum, and adaptive threshold is desirable are as follows:
It is exactly the interference for the first time in dynamic self-adapting multi-threshold interference detection technique in addition, there is also an issue here
Thresholding determination can not be completed by itself, do not interfered with signal because analysis above all assumes that or at least to be ensured without strong
Interference threshold is determined under conditions of interference, but actually signal is all often superposition interference signal, so interference threshold for the first time
It determines and needs by other means.
It will assist determining interference threshold for the first time using simplified approximate background noise Estimation Algorithm in the present embodiment.Due to
The desired signal s (n) received in signal is flooded by interchannel noise n (n), that is to say, that having S (k) < < N (k), μ in frequency domain is benefit
With ambient noise algorithm for estimating obtain it is undisturbed when entire frequency component mean value, therefore adaptive threshold is desirable for the first time
For Th0≈5μ.It has at least ensured that most interference are suppressed in this way, has recycled the multi-threshold Interference Detection of dynamic self-adapting
Algorithm further determines that thresholding.Fig. 6 gives the Adaptive multi-threshold Interference Detection algorithm flow based on ambient noise estimation.
As shown in fig. 6, being carried out when the time-domain digital signal of input is expressed as sequence Y (K) after FFT transform to Y (K)
Ambient noise estimation, then determines detection threshold Th for the first time05 μ of ≈, then by the amplitude of each frequency component in sequence Y (K) with
5 μ of threshold value is compared, and when the amplitude for having frequency component is greater than 5 μ, then carries out AF panel processing, example to the frequency component
Such as the amplitude of the frequency component is carried out to fall into width processing, and the amplitude of frequency component is less than and equal to 5 μ when is then not necessarily to carry out
AF panel processing.Thus sequence is obtained after each frequency component in Y (K) being carried out Threshold detection for the first time and AF panel processing
X (K) then carries out adaptive disturbance Threshold detection, detection threshold at this moment are as follows:Then will
The amplitude of each frequency component in sequence X (K) is compared with threshold T h, when the amplitude for having frequency component is greater than Th, then
AF panel processing is carried out to the frequency component, then will be incorporated into again sequence X by the frequency component of AF panel processing
(K), continue compared with current self adaptive detection threshold Th (since the frequency component in sequence X (K) has transformation, the thresholding pair
Also should adaptively be adjusted), until the amplitude of all frequency components is less than or equal to current self adaptive detection threshold
Th is exported after sequence X (K) is then carried out IFFT transformation again at this time.
It is asked it can thus be seen that Interference Detection problem is converted hypothesis testing by dynamic self-adapting multi-threshold Interference Detection
Topic, it is assumed that receive and narrowband interference components are not present in signal, threshold value is then arranged by the distribution obeyed frequency spectrum after transformation
It receives to examine with the presence or absence of interference components in signal, interference detection threshold for the first time is determined by simplified ambient noise estimation.
If finding to assume to set up by detecting, it is believed that receive and narrowband interference is not present in signal, directly can carry out IFFT, transformation to spectral line
To time domain, then data feeding rear stage is handled.If detection discovery is assumed invalid, then it is assumed that receive and exist in signal
Interference, the spectral line for being greater than threshold value to spectral line value carry out interference elimination treatment, the spectral line mean value that then recalculates that treated again,
New thresholding is arranged to detect spectral line, until making to assume that invalid spectral line is not present.In this way by repeatedly adaptive
The setting thresholding answered detect interference frequency point, by interference cancellation algorithm remove interfere, to realize AF panel.
Further, Fig. 6 and embodiment illustrated in fig. 5 can also be combined, two in windowing process can be folded with counterweight in this way
Road sequence can carry out adaptive threshold detecting according to method shown in fig. 6.
Preferably, validity check can be carried out to above-mentioned processing method by emulation.Fig. 7 shows that disturbance detects door
Limit the influence to the bit error rate.Using interference detection threshold as variable, Analysis interference detection threshold is 0 to 10 σFWhen corresponding error code
Rate.As can be seen from Figure 7, interference detection threshold value takes 4 σFWhen the bit error rate it is minimum.Gaussian random is known by " the 3 σ rule " of normal distribution
Variable is with 95% probability distribution in section (- 3 σF,+3σF) inner, the frequency component of ambient noise is mainly distributed on section (- 3 σF,
+3σF) inner, when interference detection threshold value is less than 4 σFWhen, the frequency component of section communication signal can be judged as interfering and being disappeared
It removes, the bit error rate is caused to become larger, when interference detection threshold value is in 4 σFTo 10 σFIn the range of when, interference detection threshold value be greater than communication
Signal frequency component range value remains the frequency component of not disturbed useful signal of communication, while this range is opposite
It is smaller in interference signal amplitude, interference signal frequency component can be effectively eliminated, so interference eliminates threshold value in 4 σFTo 10 σF
In the range of when, the bit error rate is in normal range (NR).
Fig. 8 is shown in AF panel, fall into interference the bit error rate of width processing.Using sunken amplitude as variable, divide
The amplitude of analysis interference frequency component falls into as 0 to 30 σFWhen the corresponding bit error rate fall into amplitude and ambient noise width as can be seen from Figure 8
When spending suitable, the bit error rate is in normal range (NR), when sunken amplitude is 2 σFTo 6 σFWhen, the bit error rate is minimum, when sunken amplitude is greater than 10 σF
When, jamming power is eliminated very few, and with the increase of sunken amplitude, the bit error rate becomes larger rapidly beyond normal range (NR).
Fig. 9 shows influence of the adding window degree of overlapping to the bit error rate, using adding window degree of overlapping as variable, analyzes adding window degree of overlapping
Corresponding bit error rate situation when being 10% to 100%, it can be seen in fig. 9 that adding window degree of overlapping in (0,50%) range and
The corresponding bit error rate is symmetrical in (50%, 100%) range, and when adding window degree of overlapping is 1/2, the bit error rate is minimum.Due to adding
The influence of window, time domain plethysmographic signal is presented the shape of window, the status of window can still be presented by the output signal of AF panel, when adding
When window degree of overlapping is 1/2, two paths of signals is orthogonal, and time domain plethysmographic signal becomes flat after addition.With aforementioned embodiment illustrated in fig. 5 phase
It is corresponding.
Therefore, the simulation analysis based on Fig. 7 to Fig. 9 eliminates threshold value when interference and takes 4 σF, sunken amplitude takes 2 σFTo 6 σF, add
When window degree of overlapping is 1/2, algorithm can get best anti-interference ability performance.
Further, after above-mentioned Interference Detection and AF panel processing, from the output time-domain number of time domain transformation output
The amplitude (either power) of word signal and the amplitude (or power) of input time-domain digital signal are changed, and are wished to thus
Enough amplitudes (or power) that original input time-domain digital signal can also be kept after above-mentioned processing, it is desirable alternatively to export
The amplitude (or power) of time-domain digital signal can be controlled in a stable performance number output.As shown in Figure 10, in Fig. 3 institute
Show to increase on the basis of embodiment and the amplitude of input time-domain digital signal and the amplitude of output time-domain digital signal are examined
The function of survey, i.e. amplitude detection function can be compared further by the amplitude detection to input and output signal in this way, be generated
A gain control signal is exported, which is output to the amplification that gain regulation is carried out to output time-domain digital signal
Device can thus regulate and control the amplitude of output time-domain digital signal, thus Figure 10 with respect to Fig. 3 also add to output when
Domain digital signal carry out gain regulation function, it is possible thereby to make the amplitude of output time-domain digital signal can according to need into
Row gain regulation.
It can be seen that the invention discloses a kind of Interference Detection and suppressing method based on windowing process.This method includes
Step has frequency-domain transform, Interference Detection, AF panel and time domain transformation, has wherein carried out at overlapping adding window after frequency-domain transform
Reason has then carried out going overlap processing, in addition it can include to transformed frequency in Interference Detection after time domain transformation
Domain digital signal carries out ambient noise estimation and adaptive determining interference detection threshold, improves to the accurate of interferer signal detection
Thus degree also reduces the noise specific loss of windowing process bring.This method is versatile, especially suitable in satellite communication, micro-
Interferer signal detection in wave communication.
The above description is only an embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalent structure transformation made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant technical fields,
Similarly it is included within the scope of the present invention.
Claims (8)
1. a kind of Interference Detection and suppressing method based on windowing process, which comprises the following steps:
Frequency-domain transform, the signal of communication for being mixed with interference signal first passes through AD sampler and is transformed to input time-domain digital signal, right
It is frequency domain digital signal using FFT transform after the input time-domain digital signal carries out windowing process;
Interference Detection carries out ambient noise estimation to frequency domain digital signal, then determines interference detection threshold;
AF panel, the component that the interference detection threshold is greater than in the frequency domain digital signal are then considered interference signal point
Amount, carries out inhibition processing to the interference signal component;
Time domain converts, and after interference signal component is suppressed in the frequency domain digital signal, converts using IFFT, is reduced to export
Time-domain digital signal.
2. the Interference Detection and suppressing method according to claim 1 based on windowing process, which is characterized in that the adding window
Handling the window function used includes using bartlett window, Hanning window, Hamming window, Blackman window or Blackman-
Karris window carries out windowing process to the input time-domain digital signal.
3. the Interference Detection and suppressing method according to claim 1 based on windowing process, which is characterized in that the input
Time-domain digital signal is sequence x (k):
X (k)=Ap (k)+n (k)
Wherein, p (k) is the PN sequence of equiprobability value ± l, and the length is N;N (k) be mean value be zero, variance isGauss
White noise sequence, A are the amplitude of signal of communication;
Windowing process is carried out to x (k), window function is w (k), the sequence after adding window are as follows:
xw(k)=Ap (k) w (k)+n (k) w (k).
4. the Interference Detection and suppressing method according to claim 1 based on windowing process, which is characterized in that the adding window
Folded windowing process of attaching most importance to is handled, it is corresponding that the time-domain digital signal of IFFT transformation output is gone in time domain transformation
Overlap processing.
5. the Interference Detection and suppressing method according to claim 4 based on windowing process, which is characterized in that the input
For the data sequence of time-domain digital signal by equal equal segments, the length of each data segment is N, when being overlapped windowing process, front and back phase
The coincidence length of adjacent data segment is Nr, and r (0≤r < 1) is overlap factor.
6. the Interference Detection and suppressing method according to claim 5 based on windowing process, which is characterized in that the overlapping
Factor r=1/2, the input time-domain digital signal be sequence x (k)=Ap (k)+n (k), wherein p (k) be equiprobability value ±
The PN sequence of l, the length is N;N (k) be mean value be zero, variance isGaussian sequence, A be signal of communication width
Degree;
Overlapping windowing process after output sequence be
Wherein,W (k) is window function.
7. the Interference Detection and suppressing method according to claim 6 based on windowing process, which is characterized in that the overlapping
Factor r=1/2, the input time-domain digital signal be sequence x (k)=Ap (k)+n (k), wherein p (k) be equiprobability value ±
The PN sequence of l, the length is N;N (k) be mean value be zero, variance isGaussian sequence, A be signal of communication width
Degree;
Overlapping windowing process after output sequence be
Wherein,W (k) is window function.
8. the Interference Detection and suppressing method according to claim 7 based on windowing process, which is characterized in that the input
Time-domain digital signal is divided into two-way list entries, and first via list entries is after windowing process, using FFT transform, interference
Obtain first via output sequence after detection, AF panel and IFFT transformation, the second road list entries first pass through after N/2 delay again into
Row windowing process obtains the second road output sequence after converting then also over FFT transform, Interference Detection, AF panel and IFFT,
The first via output sequence obtains the output time-domain digital signal after being added with the second road output sequence.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811638158.6A CN109639303B (en) | 2018-12-29 | 2018-12-29 | Interference detection and suppression method based on windowing processing |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811638158.6A CN109639303B (en) | 2018-12-29 | 2018-12-29 | Interference detection and suppression method based on windowing processing |
Publications (2)
Publication Number | Publication Date |
---|---|
CN109639303A true CN109639303A (en) | 2019-04-16 |
CN109639303B CN109639303B (en) | 2021-06-18 |
Family
ID=66054690
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201811638158.6A Active CN109639303B (en) | 2018-12-29 | 2018-12-29 | Interference detection and suppression method based on windowing processing |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109639303B (en) |
Cited By (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110391820A (en) * | 2019-06-11 | 2019-10-29 | 东南大学 | A kind of Novel Communication method of reseptance for evading co-channel interference based on DFT |
CN110441600A (en) * | 2019-07-17 | 2019-11-12 | 纳瓦电子(上海)有限公司 | One kind being based on the jamproof adding window method of anti-leak |
CN110445733A (en) * | 2019-06-27 | 2019-11-12 | 熊军 | Iteration self-adapting channel denoising method and iteration self-adapting channel denoise device |
CN110933007A (en) * | 2019-08-20 | 2020-03-27 | 熊军 | Device and method for eliminating interference aiming at OFDM broadband signals |
CN112003632A (en) * | 2020-07-06 | 2020-11-27 | 南京天际砺剑科技有限公司 | Direct sequence spread spectrum communication multi-address interference suppression method |
CN112649678A (en) * | 2020-12-24 | 2021-04-13 | 广州山锋测控技术有限公司 | Antenna feeder measuring method and device, antenna feeder measuring device and tester |
CN112995084A (en) * | 2021-02-07 | 2021-06-18 | 比科奇微电子(杭州)有限公司 | Signal processing method and processing device |
CN113302511A (en) * | 2021-03-31 | 2021-08-24 | 华为技术有限公司 | Interference processing method and device |
CN113391122A (en) * | 2021-06-09 | 2021-09-14 | 中电科思仪科技股份有限公司 | Method for improving selectivity of frequency spectrum monitoring channel |
CN113541706A (en) * | 2021-06-23 | 2021-10-22 | 中国电子科技集团公司第三十八研究所 | Narrow-band interference suppression method based on transform domain processing |
CN114779282A (en) * | 2022-03-30 | 2022-07-22 | 中国科学院国家授时中心 | Continuous wave interference detection method in Loran-C timing and positioning terminal |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101895370A (en) * | 2010-04-01 | 2010-11-24 | 电子科技大学 | Method for detecting interference of OFDM communication system |
CN105634543A (en) * | 2015-12-30 | 2016-06-01 | 航天恒星科技有限公司 | Narrow-band interference prevention method and system |
-
2018
- 2018-12-29 CN CN201811638158.6A patent/CN109639303B/en active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101895370A (en) * | 2010-04-01 | 2010-11-24 | 电子科技大学 | Method for detecting interference of OFDM communication system |
CN105634543A (en) * | 2015-12-30 | 2016-06-01 | 航天恒星科技有限公司 | Narrow-band interference prevention method and system |
Non-Patent Citations (5)
Title |
---|
张春海等: "基于自适应多门限算法的变换域窄带干扰抑制", 《电子与信息学报》 * |
曾祥华等: "扩频系统频域窄带干扰抑制算法加窗损耗研究", 《电子与信息学报》 * |
李健伟等: "DSSS系统频域干扰抑制算法的信噪比损耗分析", 《通信技术》 * |
李平博等: "改进的频域窄带干扰抑制方法", 《空军工程大学学报(自然科学版)》 * |
邹宁等: "一种重叠加窗频域抑制窄带干扰算法及研究", 《现代防御技术》 * |
Cited By (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110391820B (en) * | 2019-06-11 | 2021-06-11 | 东南大学 | Communication receiving method for avoiding same frequency interference based on DFT |
CN110391820A (en) * | 2019-06-11 | 2019-10-29 | 东南大学 | A kind of Novel Communication method of reseptance for evading co-channel interference based on DFT |
CN110445733A (en) * | 2019-06-27 | 2019-11-12 | 熊军 | Iteration self-adapting channel denoising method and iteration self-adapting channel denoise device |
CN110441600A (en) * | 2019-07-17 | 2019-11-12 | 纳瓦电子(上海)有限公司 | One kind being based on the jamproof adding window method of anti-leak |
CN110933007A (en) * | 2019-08-20 | 2020-03-27 | 熊军 | Device and method for eliminating interference aiming at OFDM broadband signals |
CN112003632A (en) * | 2020-07-06 | 2020-11-27 | 南京天际砺剑科技有限公司 | Direct sequence spread spectrum communication multi-address interference suppression method |
CN112649678B (en) * | 2020-12-24 | 2024-05-28 | 广州山锋测控技术有限公司 | Antenna feeder measuring method and device, antenna feeder measuring device and tester |
CN112649678A (en) * | 2020-12-24 | 2021-04-13 | 广州山锋测控技术有限公司 | Antenna feeder measuring method and device, antenna feeder measuring device and tester |
CN112995084A (en) * | 2021-02-07 | 2021-06-18 | 比科奇微电子(杭州)有限公司 | Signal processing method and processing device |
CN113302511A (en) * | 2021-03-31 | 2021-08-24 | 华为技术有限公司 | Interference processing method and device |
CN113302511B (en) * | 2021-03-31 | 2022-05-24 | 华为技术有限公司 | Interference processing method and device |
CN113391122A (en) * | 2021-06-09 | 2021-09-14 | 中电科思仪科技股份有限公司 | Method for improving selectivity of frequency spectrum monitoring channel |
CN113541706A (en) * | 2021-06-23 | 2021-10-22 | 中国电子科技集团公司第三十八研究所 | Narrow-band interference suppression method based on transform domain processing |
CN113541706B (en) * | 2021-06-23 | 2022-04-08 | 中国电子科技集团公司第三十八研究所 | Narrow-band interference suppression method based on transform domain processing |
CN114779282A (en) * | 2022-03-30 | 2022-07-22 | 中国科学院国家授时中心 | Continuous wave interference detection method in Loran-C timing and positioning terminal |
CN114779282B (en) * | 2022-03-30 | 2024-05-10 | 中国科学院国家授时中心 | Continuous wave interference detection method in Loran-C timing and positioning terminal |
Also Published As
Publication number | Publication date |
---|---|
CN109639303B (en) | 2021-06-18 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN109639303A (en) | A kind of Interference Detection and suppressing method based on windowing process | |
CN110034834A (en) | A kind of Interference Detection and inhibit optimization method | |
CN106772457B (en) | A kind of satellite navigation anti-interference method based on empty time-frequency framework | |
US5612978A (en) | Method and apparatus for real-time adaptive interference cancellation in dynamic environments | |
CN102121991B (en) | Interference suppression method and device based on BeiDou-I satellite signal reception | |
CN102904604B (en) | Narrow-band interference suppression method and device | |
CN101841349B (en) | Method for inhibiting MPSK narrowband interference of direct sequence spread spectrum system (DSSS) | |
CN109474550A (en) | A kind of Interference Detection suppressor | |
CN106249208B (en) | Signal detecting method under amplitude modulated jamming based on Fourier Transform of Fractional Order | |
CN108880604A (en) | Multi -components frequency modulation disturbance restraining method and device in a kind of spread spectrum communication system | |
CN106772254A (en) | The improved transceiver insulation method based on digital adaptation interference cancellation | |
CN104502925A (en) | Narrowband interference resisting system and method based on adaptive signal processing | |
CN102122972A (en) | Transform-domain-based narrowband interference inhibiting method in shortwave spread spectrum communication | |
CN101252369B (en) | Apparatus and method for frequency modulation interference suppression | |
CN106160786A (en) | Signal processing method and device | |
Abedi et al. | Efficient narrowband interference cancellation in ultra‐wide‐band rake receivers | |
CN110224954A (en) | A kind of anti-tracking interference realization method and system of the communication based on base band signal process | |
CN113824488B (en) | Satellite communication non-malicious interference suppression method based on decision feedback adaptive cancellation | |
CN116155306A (en) | Magnetoelectric combined low-frequency signal receiver and signal receiving method based on wiener filtering and adaptive filtering algorithm | |
CN113541706B (en) | Narrow-band interference suppression method based on transform domain processing | |
Li et al. | Overview of anti-Jamming technology based on GNSS single-antenna receiver | |
El Gebali et al. | Multi-frequency interference detection and mitigation using multiple adaptive IIR notch filter with lattice structure | |
Aldirmaz et al. | Broadband interference excision in spread spectrum communication systems based on short-time Fourier transformation | |
Plotkin | Using linear prediction to design a function elimination filter to reject sinusoidal interference | |
Bellili et al. | Low-complexity DOA estimation from short data snapshots for ULA systems using the annihilating filter technique |
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 |