CN111447045B - Signal separation method of short burst mixed signal - Google Patents

Signal separation method of short burst mixed signal Download PDF

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CN111447045B
CN111447045B CN202010234190.9A CN202010234190A CN111447045B CN 111447045 B CN111447045 B CN 111447045B CN 202010234190 A CN202010234190 A CN 202010234190A CN 111447045 B CN111447045 B CN 111447045B
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CN111447045A (en
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刘子威
曾敬
张更新
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Nanjing Microstar Communication Technology Co ltd
Nanjing University of Posts and Telecommunications
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0047—Decoding adapted to other signal detection operation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0052—Realisations of complexity reduction techniques, e.g. pipelining or use of look-up tables
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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    • H04L27/0014—Carrier regulation
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/0014—Carrier regulation
    • H04L2027/0024—Carrier regulation at the receiver end
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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    • H04L27/0014—Carrier regulation
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Abstract

The invention discloses a signal separation method of a short burst mixed signal, which comprises the steps of carrying out corresponding pretreatment on the mixed signal under the condition of obtaining the mixed signal and a local reference signal, adopting a high-precision spectrum estimation algorithm to obtain the frequency and the phase of a peak value of the pretreated signal, reconstructing the local reference signal by utilizing the obtained frequency and phase, respectively calculating a covariance matrix and a cross-correlation vector by utilizing the reconstructed local reference signal and the mixed signal, and carrying out self-adaptive weight calculation and cancellation processing to realize the signal separation of the mixed signal; the technical scheme provided by the invention can accurately separate the covering signal and the communication signal at the receiving end, reduce the operation complexity as much as possible, and effectively apply the signal separation method to the receiving end of satellite communication.

Description

Signal separation method for short burst mixed signal
Technical Field
The invention relates to the technical field of satellite communication, in particular to a signal separation method of short burst mixed signals.
Background
Satellite communication is an important modern communication means and is widely applied to the field of communication in developed countries. The signal interception resistance is a main consideration in system design. The original design idea of anti-interception was to hope to destroy the energy accumulation effect of the interception end as much as possible. Conventional methods include spreading, reducing transmission rate, shortening transmission time, employing array antennas and beamforming, etc. However, with the development of signal processing technology, the effect of the conventional method has gradually decreased due to the improvement of device indexes such as processing delay, instantaneous receiving bandwidth and the like. In recent years, an anti-interception technique has appeared which uses high-power signal concealment as a core and assists a receiving-end signal separation technique, and it is desired to reduce the probability of the concealed signal being discovered by the concealment of the high-power signal. The technology is a brand new solution for the satellite communication system.
The signal covering technology is theoretically suitable for continuous signals and short burst signals, and the signal separation technology is adopted at a receiving end to realize the signal receiving and detection of a partner. However, most of the signal separation methods disclosed in the prior publications are designed for continuous signals, and the received signals are separated in a loop tracking synchronization mode. However, in special scenes such as limited power and limited working time, short burst signals are needed to work. Aiming at the separation of short burst signals, the problems of short time length of the short burst signals, limited samples and the like are required to be researched in few researches in published documents, and an efficient and robust separation method is researched.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the defects in the prior art, the invention provides a signal separation method of a short burst mixed signal, which enables a covering signal and a communication signal at a receiving end to be accurately separated, reduces the operation complexity as much as possible and enables the signal separation method to be effectively applied to the receiving end of satellite communication.
The technical scheme is as follows: in order to achieve the purpose, the invention adopts the technical scheme that:
a signal separation method for a short burst mixed signal, comprising the steps of:
step 1, in the mixed signal separation stage, after down-conversion and analog-to-digital conversion, the receiving end can obtain the mixed signal r ═ r 1 ,r 2 ,…,r n ,…,r N ] T And local reference signal s ═ s 1 ,s 2 ,…s n …,s N ] T Where N is 1,2, …, and N represents the number of sampling points, [ · N] T Representing a transpose;
and step 2, performing demodulation preprocessing s ' ═ rxs by using the mixed signal r and the local reference signal s to obtain a preprocessed signal s ' ═ s ' 1 ,s′ 2 ,…,s′ n ,…,s′ N ] T ；
And 3, performing low-pass filtering on the preprocessed signal s 'to obtain a filtered signal d ═ s' × h 1 ,d 2 ,…,d n ,…,d N ] T Where h is the impulse response of the low pass filter, representing the signal convolution; the low pass filter may be based onDesigning a sampling frequency and a carrier frequency of a system;
step 4, calculating the frequency spectrum alpha (omega) and the amplitude spectrum | alpha (omega) | of the signal d after filtering by adopting a high-precision spectrum estimation method, wherein omega belongs to [ -pi, pi ];
step 5, searching the amplitude spectrum | alpha (omega) | obtained in the step 4 to obtain a frequency value corresponding to the position with the maximum amplitude, and recording the frequency value as the estimated omega of the angular frequency of the signal k ；
Step 6, estimating omega according to the angular frequency of the signal obtained in the step 5 k To obtain omega k Phase of
Figure BDA0002430414940000021
Figure BDA0002430414940000022
Wherein, α (ω) k ) Is omega k Processing the corresponding spectral values;
step 7, utilizing the frequency omega obtained in the step 6 k And phase
Figure BDA0002430414940000023
Compensating the frequency and phase of the local reference signal s to obtain a reconstructed signal x ═ x 1 ,x 2 ,…,x n ,…,x N ] T ；
Step 8, calculating a covariance matrix V and a cross correlation vector p by using the reconstructed signal x and the mixed signal r in the step 1;
step 9, calculating a mixed signal separation weight w as V according to the covariance matrix V and the cross-correlation vector p obtained in step 8 -1 p, wherein [ ·] -1 Representing matrix inversion;
step 10, utilizing the separation weight w to perform cancellation processing on the mixed signal, wherein z is r-w H x, signal separation of the mixed signal is achieved, wherein [. ]] H Representing a conjugate transpose.
Further, the specific steps of calculating the frequency spectrum α (ω) and the amplitude spectrum | α (ω) | of the signal in step 4 are as follows:
step 4.1 resolution according to the low pass filter in step 3Determining the order M of the filter according to the rate and the precision, and obtaining a snapshot c by passing the filtered signal d through a filter sliding window t ＝[c t ,c t+1 ,…c t+z ,…c t+M-1 ] T Forming an estimated signal matrix b ═ c 1 ,c 2 ,…c t ,…c N-M ]Wherein z is 0,1, …, M-1, t is 1,2, …, N-M;
and 4.2, calculating a correlation matrix K according to the estimated signal matrix b:
Figure BDA0002430414940000024
wherein [ ·] H Represents a conjugate transpose;
step 4.3, obtaining a snapshot c according to the sliding window t And the correlation matrix K, calculating g (ω) and Q (ω):
Figure BDA0002430414940000031
Q(ω)＝K-g(ω)g H (ω)
wherein, L is N + M-1;
step 4.4, calculating the frequency spectrum alpha (omega) of the signal according to g (omega) and Q (omega):
Figure BDA0002430414940000032
wherein a (ω) ═ 1, e -jω ,…,e -j(M-1)ω ] T Is the pilot vector of the filtered signal [ ·] -1 Representing matrix inversion;
step 4.5, according to the signal spectrum α (ω), obtaining a magnitude spectrum | α (ω) |:
Figure BDA0002430414940000033
further, ω in said step 6 k Phase of (b)
Figure BDA0002430414940000034
The angle () is used for calculating the phase of a certain frequency point in the frequency spectrum, and the arctan () arc tangent operation is adopted to calculate the phase of the frequency point.
Further, the step 8 of calculating the covariance matrix V and the cross-correlation vector p includes the following steps:
step 8.1, calculating a covariance matrix V by using the reconstructed signal x:
Figure BDA0002430414940000035
and 8.2, calculating a cross-correlation vector p by using the reconstructed signal x and the mixed signal r in the step 1:
Figure BDA0002430414940000036
wherein [ ·] * Representing the conjugation.
Further, the signal separation by using the separation weight w in the step 10 includes the following steps:
step 10.1, using the separation weight to estimate a masking signal in the mixed signal to obtain an output y of the adaptive filter:
y＝w H x
step 10.2, carrying out cancellation processing on the mixed signal and the output of the filter to realize the signal separation of the mixed signal:
z＝r-y＝r-w H x
has the advantages that: the signal separation method of the short burst mixed signal enables a covering signal and a communication signal of a receiving end to be accurately separated, reduces the operation complexity as much as possible, enables the signal separation method to be effectively applied to the receiving end of satellite communication, estimates compensation parameters by using a de-modulation processing and high-precision spectrum estimation method, can effectively overcome the frequency phase difference of a transmitting party and a receiving party, and remarkably improves the subsequent offset processing effect; meanwhile, based on the characteristic of short-time stationarity of a satellite channel, aiming at the problem of signal separation of a signal and a communication signal covered by a receiving end, an open-loop adaptive filtering method is provided for signal separation of a mixed signal.
Drawings
FIG. 1 is a flow chart of a signal separation method provided by the present invention;
FIG. 2 is a simulation diagram of a mixed signal and a local reference signal before signal separation provided by the present invention;
FIG. 3 is a graph of a superimposed signal spectrum after high-precision spectral estimation;
FIG. 4 is a comparison of signal simulation plots before and after signal separation according to the present invention;
fig. 5 is a graph of the performance of the invention for the bit error rate after demodulating the separated signal.
Detailed Description
The present invention will be further described with reference to the accompanying drawings.
Fig. 1 shows a signal separation method of a short burst mixed signal, comprising the steps of:
step 1, in the mixed signal separation stage, after down-conversion and analog-to-digital conversion, a receiving end can obtain a mixed signal r ═ r 1 ,r 2 ,…,r n ,…,r N ] T And local reference signal s ═ s 1 ,s 2 ,…s n …,s N ] T Where N is 1,2, …, and N represents the number of sampling points [. cndot.] T Representing a transpose;
and step 2, performing demodulation preprocessing s ' ═ rxs by using the mixed signal r and the local reference signal s to obtain a preprocessed signal s ' ═ s ' 1 ,s′ 2 ,…,s′ n ,…,s′ N ] T ；
And 3, performing low-pass filtering on the preprocessed signal s 'to obtain a filtered signal d ═ s' × h 1 ,d 2 ,…,d n ,…,d N ] T Where h is the impulse response of the low pass filter, which represents the signal convolution; the low pass filter may be based on sampling of the systemFrequency and carrier frequency;
step 4, calculating the frequency spectrum alpha (omega) and the amplitude spectrum | alpha (omega) | of the signal d after filtering by adopting a high-precision spectrum estimation method, wherein the omega belongs to [ - π, π ]; after the low-pass filtering in step 3, the signal does not contain a modulation item, only one narrow-band signal containing frequency difference and phase difference is left, and the frequency difference and the phase difference can be estimated by adopting a high-precision spectrum estimation method. In this step, the present invention takes an APES method as an example to describe the spectrum estimation process, and other parameter estimation methods may be adopted if the conditions allow.
Step 4.1, determining the order M of the filter according to the resolution and the precision of the low-pass filter in the step 3, and obtaining a snapshot c by passing the filtered signal d through a filter sliding window t ＝[c t ,c t+1 ,…c t+z ,…c t+M-1 ] T Forming an estimated signal matrix b ═ c 1 ,c 2 ,…c t ,…c N-M ]Wherein z is 0,1, …, M-1, t is 1,2, …, N-M;
and 4.2, calculating a correlation matrix K according to the estimated signal matrix b:
Figure BDA0002430414940000051
wherein [ ·] H Represents a conjugate transpose;
step 4.3, obtaining a snapshot c according to the sliding window t And the correlation matrix K, calculating g (ω) and Q (ω):
Figure BDA0002430414940000052
Q(ω)＝K-g(ω)g H (ω)
wherein L is N + M-1;
step 4.4, calculating the frequency spectrum alpha (omega) of the signal according to g (omega) and Q (omega):
Figure BDA0002430414940000053
wherein a (ω) ═ 1, e -jω ,…,e -j(M-1)ω ] T Is a pilot vector of the filtered signal [ ·] -1 Representing a matrix inversion;
step 4.5, according to the signal spectrum α (ω), obtaining a magnitude spectrum | α (ω) |:
Figure BDA0002430414940000054
step 5, searching the amplitude spectrum | alpha (omega) | obtained in the step 4 to obtain a frequency value corresponding to the position with the maximum amplitude, and recording the frequency value as the estimation omega of the angular frequency of the signal k ；
Step 6, estimating omega according to the angular frequency of the signal obtained in the step 5 k To obtain omega k Phase of
Figure BDA0002430414940000055
Figure BDA0002430414940000061
Wherein, α (ω) k ) Is omega k Processing the corresponding spectral values; the angle () is used to find the phase of a frequency point in the spectrum, and in this step, arctan () arc tangent operation is used to find the phase, and if conditions allow, other methods to find the phase may be used.
Step 7, utilizing the frequency omega obtained in step 6 k And phase
Figure BDA0002430414940000062
Compensating the frequency and phase of the local reference signal s to obtain a reconstructed signal x ═ x 1 ,x 2 ,…,x n ,…,x N ] T (ii) a In practice, the frequency and phase of the local reference signal s may be adjusted by mixing or numerical control according to the generation of analog or digital frequency used by the system.
Step 8, calculating a covariance matrix V and a cross-correlation vector p by using the reconstructed signal x and the mixed signal r in the step 1;
step 8.1, calculating a covariance matrix V by using the reconstructed signal x:
Figure BDA0002430414940000063
and 8.2, calculating a cross-correlation vector p by using the reconstructed signal x and the mixed signal r in the step 1:
Figure BDA0002430414940000064
wherein [ ·] * Representing conjugation.
Step 9, calculating a mixed signal separation weight w as V according to the covariance matrix V and the cross-correlation vector p obtained in step 8 -1 p, wherein [ ·] -1 Representing matrix inversion;
step 10, utilizing the separation weight w to perform cancellation processing on the mixed signal, wherein z is r-w H x, signal separation of the mixed signal is achieved, wherein [. ]] H Representing a conjugate transpose.
Step 10.1, estimating a masking signal in the mixed signal by using the separation weight to obtain an output y of the adaptive filter:
y＝w H x
step 10.2, carrying out cancellation processing on the mixed signal and the output of the filter to realize the signal separation of the mixed signal:
z＝r-y＝r-w H x
the following provides a specific embodiment to verify the technical solution provided by the present invention:
taking BPSK signals as an example, the length of a transmission data packet is 50 bits, the data rate is 100 bits/s, the sampling rate is 1kHz, the carrier frequency of a transmission signal at a transmitting end is 200Hz, the initial phase is pi rad, the carrier frequency of a local reference signal is 300Hz, the initial phase is 0rad, and the signal-to-noise ratio difference between a received interference signal and a communication signal is 15 dB.
Experiment 1, calculating signal simulation graphs before and after separation of a mixed signal by using the method of the present invention for simulation data, wherein a simulation graph of a local reference signal of the mixed signal and an interference signal sent by a transmitting terminal is shown in fig. 2, a spectrum of a superimposed signal estimated by using an APES spectrum is shown in fig. 3, and a comparison graph of a communication signal separated by using the method of the present invention and a communication signal of the transmitting terminal before separation is shown in fig. 4.
It can be seen from fig. 4 that the communication signal separated by the method of the present invention substantially coincides with the communication signal of the transmitting end. The simulation result is basically consistent with the theoretical analysis, which shows that the method can separate the communication signal from the mixed signal at the receiving end.
Experiment 2, in order to better evaluate the performance of the method of the present invention, the separated communication signal is demodulated, and then the error code performance is analyzed by the monte carlo method, and a bit error rate curve is drawn and compared with a theoretical bit error rate curve, as shown in fig. 5. Wherein, the solid line represents the bit error rate curve obtained by the theoretical method, and the hollow triangular line represents the bit error rate curve obtained by the method.
It can be seen from FIG. 5 that the simulated bit error rate performance curve and the theoretical bit error rate performance curve are in E b /N 0 Smaller substantially coincide, and at E b /N 0 If the ratio is large, a certain degree of deviation occurs. The simulation result is basically consistent with the theoretical analysis, and the method can realize the signal separation of the short-burst mixed signal and can obtain better separation performance.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.

Claims (5)

1. A method for signal separation of a short burst mixed signal, comprising the steps of:
step 1, in the mixed signal separation stage, after down-conversion and analog-to-digital conversion, the receiving end can obtain the mixed signal r ═ r 1 ,r 2 ,…,r n ,…,r N ] T And local reference signal s ═ s 1 ,s 2 ,…s n …,s N ] T Where N is 1,2, …, and N represents the number of sampling points [. cndot.] T Representing a transpose;
and 2, performing demodulation preprocessing s '═ r × s by using the mixed signal r and the local reference signal s to obtain a preprocessed signal s' ═ s 1 ′,s 2 ′,…,s n ′,…,s′ N ] T ；
And 3, performing low-pass filtering on the preprocessed signal s 'to obtain a filtered signal d ═ s' × h 1 ,d 2 ,…,d n ,…,d N ] T Where h is the impulse response of the low pass filter, representing the signal convolution; the low-pass filter can be designed according to the sampling frequency and the carrier frequency of the system;
step 4, calculating the frequency spectrum alpha (omega) and the amplitude spectrum | alpha (omega) | of the signal d after filtering by adopting a high-precision spectrum estimation method, wherein the omega belongs to [ - π, π ];
step 5, searching the amplitude spectrum | alpha (omega) | obtained in the step 4 to obtain a frequency value corresponding to the position with the maximum amplitude, and recording the frequency value as the estimated omega of the angular frequency of the signal k ；
Step 6, estimating omega according to the angular frequency of the signal obtained in the step 5 k To obtain omega k Phase of
Figure FDA0003747449550000011
Figure FDA0003747449550000012
Wherein, α (ω) k ) Is omega k Processing the corresponding spectral values;
step 7, utilizing the frequency omega obtained in step 6 k And phase
Figure FDA0003747449550000013
Compensating the frequency and phase of the local reference signal s to obtain a reconstructed signal x ═ x 1 ,x 2 ,…,x n ,…,x N ] T ；
Step 8, calculating a covariance matrix V and a cross-correlation vector p by using the reconstructed signal x and the mixed signal r in the step 1;
step 9, calculating a mixed signal separation weight w as V according to the covariance matrix V and the cross-correlation vector p obtained in step 8 -1 p, wherein [ ·] -1 Representing matrix inversion;
step 10, utilizing the separation weight w to perform cancellation processing on the mixed signal, wherein z is r-w H x, signal separation of the mixed signal is achieved, wherein [. ]] H Representing a conjugate transpose.
2. The signal separation method of the short-burst mixed signal according to claim 1, wherein the specific steps of calculating the frequency spectrum α (ω) and the amplitude spectrum | α (ω) | of the signal in step 4 are as follows:
step 4.1, determining the order M of the filter according to the resolution and the precision of the low-pass filter in the step 3, and obtaining a snapshot c by passing the filtered signal d through a filter sliding window t ＝[c t ,c t+1 ,…c t+z ,…c t+M-1 ] T Forming an estimated signal matrix b ═ c 1 ,c 2 ,…c t ,…c N-M ]Wherein, z is 0,1, …, M-1, t is 1,2, …, N-M;
step 4.2, calculating a correlation matrix K according to the estimated signal matrix b:
Figure FDA0003747449550000021
wherein [ ·] H Represents a conjugate transpose;
step 4.3, obtaining a snapshot c according to the sliding window t And the correlation matrix K, calculating g (ω) and Q (ω):
Figure FDA0003747449550000022
Q(ω)＝K-g(ω)g H (ω)
wherein, L is N + M-1;
step 4.4, calculating the frequency spectrum alpha (omega) of the signal according to g (omega) and Q (omega):
Figure FDA0003747449550000023
wherein a (ω) ═ 1, e -jω ,…,e -j(M-1)ω ] T Is the pilot vector of the filtered signal [ ·] -1 Representing matrix inversion;
step 4.5, according to the signal spectrum α (ω), a magnitude spectrum | α (ω) | of the signal can be obtained:
Figure FDA0003747449550000024
3. the method according to claim 1, wherein ω is ω in step 6 k Phase of (b)
Figure FDA0003747449550000025
The angle () is used for calculating the phase of a certain frequency point in the frequency spectrum, and the arctan () arc tangent operation is adopted to calculate the phase of the frequency point.
4. The signal separation method of a short burst mixed signal according to claim 1, wherein the step 8 of calculating the covariance matrix V and the cross-correlation vector p comprises the steps of:
step 8.1, calculating a covariance matrix V by using the reconstructed signal x:
Figure FDA0003747449550000031
and 8.2, calculating a cross-correlation vector p by using the reconstructed signal x and the mixed signal r in the step 1:
Figure FDA0003747449550000032
wherein [ ·] * Representing conjugation.
5. The method as claimed in claim 1, wherein the step 10 of signal separation using the separation weight w comprises the steps of:
step 10.1, using the separation weight to estimate a masking signal in the mixed signal to obtain an output y of the adaptive filter:
H
y＝wx
step 10.2, carrying out cancellation processing on the mixed signal and the output of the filter to realize the signal separation of the mixed signal:
z＝r-y＝r-w H x。
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