CN113507307B - Space-time joint anti-interference method, device and equipment suitable for satellite communication - Google Patents

Space-time joint anti-interference method, device and equipment suitable for satellite communication Download PDF

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CN113507307B
CN113507307B CN202111053717.9A CN202111053717A CN113507307B CN 113507307 B CN113507307 B CN 113507307B CN 202111053717 A CN202111053717 A CN 202111053717A CN 113507307 B CN113507307 B CN 113507307B
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interference
interference suppression
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weight vector
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CN113507307A (en
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张颉
杨迎春
付重
徐厚东
邹仕富
甘炜
唐勇
傅宁
李里
贺洪星
张凌浩
王海
唐超
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Electric Power Research Institute of State Grid Sichuan Electric Power Co Ltd
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Electric Power Research Institute of State Grid Sichuan Electric Power Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/086—Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/21—Interference related issues ; Issues related to cross-correlation, spoofing or other methods of denial of service
    • 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

Abstract

The invention discloses a space-time joint anti-interference method, a device and equipment suitable for satellite communication, wherein the method comprises the following steps: estimating the direction of arrival of the received signal by adopting an MUSIC algorithm; solving a beam forming weight vector by adopting a linear constraint minimum variance optimization criterion; performing first-stage interference suppression processing on the received signals according to the beamforming weight vector; expanding dimensionality of the signal subjected to the first-stage interference suppression processing; solving the beamforming weight vector again by adopting a space-time processing method based on a maximized signal interference-to-noise ratio criterion; performing second-stage interference suppression processing on the signals subjected to the dimensionality extension according to the beamforming weight vector obtained by solving again; and detecting the signal subjected to the second-stage interference suppression by adopting a standard MLSE method, and recovering a useful symbol sequence. The invention adopts a two-stage interference suppression method, and improves the reliability of the Beidou satellite navigation system for providing wireless communication service for power grid equipment in an interference scene.

Description

Space-time joint anti-interference method, device and equipment suitable for satellite communication
Technical Field
The invention relates to the technical field of antenna array signal processing, in particular to a space-time joint anti-interference method, a space-time joint anti-interference device and space-time joint anti-interference equipment suitable for satellite communication.
Background
At present, the Beidou satellite navigation system completely realizes the services of providing accurate navigation, time service, positioning, short message communication and the like for all weathers of China, and plays an increasingly important role in the development process of the economic society of China. The satellite communication mode has obvious advantages and is less limited by objective factors such as geographic position, time and the like, so the development is rapid, but certain problems still face in the development process, and one of the challenges is an increasingly complex electromagnetic environment. Satellite signals are extremely vulnerable due to the presence of significant amounts of electromagnetic interference, and even malicious interference, in space, particularly terrestrial space. On the other hand, in a power grid application scene, a large number of power equipment are usually arranged in remote areas, and the functions of power grid time reference unification, power station environment monitoring, electric vehicle monitoring and the like are mainly realized through time service, positioning and other services provided by a Beidou satellite navigation system. When the interference is serious, the quality of a signal received by the ground navigation receiver is reduced, the service quality of the Beidou satellite navigation system is seriously influenced, and further electric power application loss which is difficult to compensate is possibly caused. Therefore, how to inhibit interference, improve the reliability and safety of communication of the Beidou satellite navigation system and guarantee the service quality of the Beidou satellite navigation system has important significance.
Disclosure of Invention
In order to solve the problem of insufficient interference suppression capability in satellite communication, the invention provides a space-time joint anti-interference method suitable for satellite communication. The invention adopts a two-stage interference suppression method, and improves the reliability of the Beidou satellite navigation system for providing wireless communication service for power grid equipment in an interference scene.
The invention is realized by the following technical scheme:
a space-time joint anti-interference method suitable for satellite communication comprises the following steps:
estimating the direction of arrival of the received signal by adopting a multiple signal classification algorithm;
solving a beamforming weight vector by adopting a linear constraint minimum variance optimization criterion based on the direction of arrival of the expected signal; the direction of arrival of the expected signal is the direction of arrival of a useful signal in the received signal;
performing first-stage interference suppression processing on the received signals according to the beamforming weight vector;
performing dimensionality extension on the signal subjected to the first-stage interference suppression processing according to a guide vector principle;
solving the beamforming weight vector again by adopting a space-time processing method based on a maximized signal interference-to-noise ratio criterion;
performing second-stage interference suppression processing on the signals subjected to the dimensionality extension according to the beamforming weight vector obtained by solving again;
and detecting the signal subjected to the second-stage interference suppression by adopting a standard maximum likelihood sequence estimation method to recover the useful symbol sequence.
Preferably, the beamforming weight vector obtained by solving by adopting the linear constraint minimum variance optimization criterion in the invention is as follows:
w1＝R-1C(CHR-1C)-1f
wherein, C is a constraint matrix constructed by a steering vector corresponding to the direction of arrival of the obtained signal; f is a constraint vector relating to the desired signal direction; and R is a sampling covariance matrix of signals received by the antenna array.
Preferably, the step of performing the first-stage interference suppression processing on the received signal according to the beamforming weight vector of the present invention specifically includes:
using the weight vector w obtained by solving1Weighting the received signal x (k) of the antenna array at the k-th time, and outputting the signal
Figure GDA0003324024770000021
Preferably, the step of performing the dimension expansion on the signal subjected to the first-stage interference suppression processing according to the steering vector principle of the present invention specifically includes:
corresponding to the steering vector a according to the normal direction of the antenna array0Expanding x' (k) with the dimension of the guide vector a0The dimension M of (a), the expanded signal being y (k) a0x′(k)。
Preferably, the step of solving the beamforming weight vector again by using the space-time processing method based on the criterion of maximizing the signal-to-interference ratio specifically includes:
after N snapshots, the sequence Y ═ Y (1) Y (2) Y (3.. Y (N))]Calculating a covariance matrix
Figure GDA0003324024770000031
Similarly, the matrix is respectively calculated by combining the training sequence T known by the receiving end
Figure GDA0003324024770000032
Figure GDA0003324024770000033
Further constructing a matrix
Figure GDA0003324024770000034
Wherein, YHDenotes the conjugate transpose of Y, THThe conjugate transpose of T is represented,
Figure GDA0003324024770000035
to represent
Figure GDA0003324024770000036
The inverse matrix of (d);
solving for RsIf the characteristic vector q corresponding to the minimum characteristic value is the channel vector, estimating h as q;
re-solving beamforming weight vectors
Figure GDA0003324024770000037
Preferably, the step of performing the second-stage interference suppression processing on the signals subjected to the dimension expansion according to the beamforming weight vector obtained by the re-solving in the present invention specifically includes:
according to the beam forming weight vector w obtained by solving again2Weighting the signals y (k) after the dimension expansion to obtain
Figure GDA0003324024770000038
And realizing second-stage interference suppression.
In a second aspect, the invention provides a space-time joint anti-jamming device suitable for satellite communication, which comprises a direction-of-arrival estimation module, a primary interference suppression module, a secondary interference suppression module and a sequence detection module;
the direction-of-arrival estimation module estimates the direction of arrival of the received signal by adopting a multi-signal classification algorithm;
the primary interference suppression module solves a beamforming weight vector by adopting a linear constraint minimum variance optimization criterion, and performs weighting processing on a received signal to realize primary interference suppression;
the secondary interference suppression module firstly performs dimensionality extension on the signals subjected to the primary interference suppression according to a guide vector principle, then solves a beam forming weight vector again by adopting a space-time processing method based on a maximized signal interference-to-noise ratio criterion, and performs weighting processing on the signals subjected to the dimensionality extension to realize secondary interference suppression;
and the sequence detection module detects the signal subjected to the second-stage interference suppression by adopting a standard maximum likelihood sequence estimation method, and recovers a useful symbol sequence.
In a third aspect, the invention provides satellite communication equipment, which comprises the anti-interference device.
The invention has the following advantages and beneficial effects:
compared with the existing airspace processing method and JST method, the method has better anti-interference capability and obvious performance gain in the severe interference environment. Therefore, the method is beneficial to improving the reliability of the Beidou satellite navigation system in providing communication services such as positioning, time service and the like for national power grid equipment in a severe interference environment.
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The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
fig. 1 is a schematic flow chart of an anti-interference method according to the present invention.
FIG. 2 is a schematic diagram of the apparatus of the present invention.
Fig. 3 is a schematic block diagram of the interference rejection apparatus of the present invention.
Fig. 4 is a Bit Error Rate (BER) comparison curve of the method of the present invention and the JST method when the training sequence length is 26, the information sequence length is 114, the number of antenna elements M is 16, the number of multipaths is 3, the channel memory length is 4, the number of interfering users is 2, and the modulation scheme is BPSK. The abscissa of the graph is the signal-to-interference ratio (unit: dB) and the ordinate is the Bit Error Rate (BER). The symbol ". smallcircle" in the figure represents the JST method and "□" represents the method of the present invention.
Fig. 5 is a Bit Error Rate (BER) comparison curve of the method of the present invention and the anti-interference method based on the LCMV optimization criterion when different signal to interference ratios are used when the training sequence length is 26, the information sequence length is 114, the number of antenna elements M is 16, the number of multipaths is 3, the channel memory length is 4, the number of interfering users is 2, and the modulation method is BPSK. The abscissa of the graph is the signal-to-interference ratio (unit: dB) and the ordinate is the Bit Error Rate (BER). In the figure, the mark ". smallcircle" represents an anti-interference method based on LCMV optimization criteria, and "□" represents the method of the invention.
Fig. 6 is a Bit Error Rate (BER) comparison curve when the length of the training sequence is 26, the length of the information sequence is 114, the number of antenna elements M is 16, the number of multipaths is 3, the length of channel memory is 4, the number of interfering users is 2, and the modulation method is BPSK. The abscissa of the graph is the signal-to-interference ratio (unit: dB) and the ordinate is the Bit Error Rate (BER). In the figure, the mark ". smallcircle" represents an anti-interference method based on LCMV optimization criteria, and "□" represents the method of the invention.
Fig. 7 is a Bit Error Rate (BER) comparison curve when the length of the training sequence is 26, the length of the information sequence is 114, the number of antenna elements M is 16, the number of multipaths is 3, the length of channel memory is 4, the number of interfering users is 2, and the modulation method is BPSK, and the method of the present invention is adopted at different signal-to-noise ratios. The abscissa of the graph is the signal-to-noise ratio (unit: dB) and the ordinate is the Bit Error Rate (BER). In the figure, the symbol "x" represents the error rate curve of the method according to the invention at a signal to interference ratio of-40 dB, ". o" represents the error rate curve of the method according to the invention at a signal to interference ratio of-30 dB, ". o" represents the error rate curve of the method according to the invention at a signal to interference ratio of-20 dB, and "□" represents the error rate curve of the method according to the invention at a signal to interference ratio of 0 dB.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
Example 1
The current anti-interference technology mainly comprises the following technologies:
time domain anti-interference technology: the core idea is to design an adaptive filter by using a digital signal processing technology and process a received signal in a time domain so as to suppress interference. The time domain filtering technology has a strong inhibition effect on the narrow-band interference, for example, a time domain anti-interference chip developed by Mayflower corporation in usa still has a good inhibition effect on the narrow-band interference with interference power greater than 30 dB.
Frequency domain anti-interference technology: the technology mainly utilizes Fast Fourier Transform (FFT) to Transform signals from a time domain to a frequency domain, and further inhibits an interference component power spectral line on the frequency domain to achieve the aim of resisting interference. The frequency domain anti-jamming technology is easy to realize, and can provide a lower null depth compared with the time domain anti-jamming technology, but the frequency domain anti-jamming technology can weaken satellite signals while inhibiting interference.
The airspace anti-interference technology is as follows: according to the difference of the directions of arrival of the expected signals and the interference signals in the space, the technology adopts a reasonable optimization criterion to adaptively solve the beam forming weight vector, and through weighting processing of array elements of the antenna array, a main beam is aligned to the direction of the expected signals, and a null position is aligned to the direction of the interference signals, so that interference is suppressed. The airspace anti-interference technology is widely concerned by scientific researchers due to the excellent anti-interference performance.
The space-time joint anti-interference technology comprises the following steps: the method combines the time domain processing technology on the basis of the space domain anti-interference technology, overcomes the defect that the interference suppression capability of the pure space domain anti-interference technology is limited by the number of array elements, greatly improves the degree of freedom of antenna array interference suppression, and further improves the anti-interference performance by introducing the time domain processing technology. The technology is one of the hot spots of the anti-interference research of the satellite communication at present.
In practical applications, the power of the interference signal is usually large, and the satellite signal is not gained by using more power inversion methods, or even weakened. Therefore, in view of the excellent performance of the Space-domain Interference rejection method and the Space-Time Joint (JST) Interference rejection method, the present embodiment proposes a Space-Time Joint Interference rejection method suitable for satellite communication, in which the method of the present embodiment first estimates the Direction of Arrival (DOA) of a Signal by using a Multiple Signal Classification algorithm (MUSIC Signal Classification), then solves a beamforming weight vector by using an optimization criterion based on a Linear Constraint Minimum Variance (LCMV) according to an expected Signal Direction, performs weighting processing on a received Signal to achieve first-stage Interference rejection, then solves a channel vector and a beamforming weight vector by using a Space-Time processing method based on a Signal to Interference Noise Ratio (SINR) criterion, and performs weighting processing on the Signal after the first-stage Interference rejection to achieve second-stage Interference rejection, and finally, receiving the received signal Sequence subjected to the two-stage interference suppression by adopting a standard Maximum Likelihood Sequence Estimation (MLSE) method. Compared with an anti-interference method based on an LCMV optimization criterion, a JST method, a Least Mean Square error (LMS) method, a Recursive Least Square (RLS) method and a Constant Modulus Algorithm (CMA), the method provided by the embodiment has better interference suppression capability and beamforming gain.
Specifically, as shown in fig. 1, the method of this embodiment includes:
step 101, estimating the direction of arrival of the received signal.
In step 101 of this embodiment, a MUSIC algorithm is used to achieve estimation of the direction of arrival of a signal, that is: and (3) carrying out characteristic decomposition on the sampling covariance matrix R of the signals received by the antenna array, constructing a signal subspace and a noise subspace according to the obtained characteristic vectors, further obtaining an array space spectrum function, and finally estimating the signal arrival direction by a spectrum peak search algorithm.
And 102, solving a beamforming weight vector by adopting a linear constraint minimum variance optimization criterion (LCMV optimization criterion) based on the direction of arrival of the expected signal. The direction of arrival of the expected signal is the direction of arrival of the useful signal in the actual received signal.
The beamforming weight vector solved in this embodiment is:
w1＝R-1C(CHR-1C)-1f
wherein the constraint matrix C is constructed by the steering vectors corresponding to the directions of arrival of the signals obtained in step 101, and f is a constraint vector related to the desired signal direction.
And 103, performing first-stage interference suppression processing on the received signal according to the beam forming weight vector.
Step 103 of this embodiment specifically includes: the weight vector w obtained by solving according to the step 1021Weighting the received signal x (k) of the antenna array at the k-th time, and outputting the signal
Figure GDA0003324024770000071
And 104, performing dimensionality extension on the signal subjected to the first-stage interference suppression according to a guide vector principle.
Step 104 of this embodiment corresponds to the steering vector a according to the normal direction of the antenna array0Spreading x' (k) with a spreading dimension M, and the signal after spreading is y (k) a0x′(k)Wherein M is the number of array elements.
And 105, solving the beamforming weight vector again by adopting a space-time processing method (JST algorithm) based on a maximized signal interference-to-noise ratio (SINR) criterion.
Step 105 of this embodiment specifically includes:
step 201, after N snapshots, receiving a sequence Y ═ Y (1) Y (2) Y (3.. Y (N))]Calculating a covariance matrix
Figure GDA0003324024770000081
Similarly, the matrix is respectively calculated by combining the training sequence T known by the receiving end
Figure GDA0003324024770000082
Further constructing a matrix
Figure GDA0003324024770000083
Wherein, YHDenotes the conjugate transpose of Y, THThe conjugate transpose of T is represented,
Figure GDA0003324024770000084
to represent
Figure GDA0003324024770000085
The inverse matrix of (d);
step 202, solving for RsIf the characteristic vector q corresponding to the minimum characteristic value is the channel vector, estimating h as q;
step 203, solving the beamforming weight vector again
Figure GDA0003324024770000086
And step 106, performing second-stage interference suppression processing on the signals after dimensionality extension according to the weight vector obtained by re-solving.
Step 106 of this embodiment is based on the weight vector w obtained by re-solving2Weighting the signals y (k) after the dimension expansion to obtain
Figure GDA0003324024770000087
And realizing second-stage interference suppression.
And step 107, detecting the signal subjected to the second-stage interference suppression by adopting a standard MLSE method, and recovering a useful symbol sequence.
In this embodiment, step 107 detects the signal z (k) subjected to the second-stage interference suppression according to the obtained channel vector h, and recovers a useful sequence number sequence.
The method provided by the embodiment adopts a two-stage interference suppression framework to achieve the purpose of anti-interference. Firstly, estimating the direction of arrival of signals, and then solving a beamforming weight vector w by adopting an LCMV (liquid Crystal display Module) optimization criterion based on the direction of the expected signals1According to the obtained w1And weighting the antenna array received signal x (k) to realize first-stage interference suppression, wherein the energy of the interference signal is fully reduced after the first-stage interference suppression. Then, according to the guiding vector principle, the dimensionality of the signal x' (k) subjected to the first-stage interference suppression is expanded, and then a space-time processing method based on the maximization signal-to-interference-and-noise ratio criterion is adopted to solve a channel vector h and a beam forming weight vector w2According to the obtained w2And finally, carrying out weighting processing on the signals y (k) after the dimensionality is expanded to realize second-stage interference suppression, and detecting a signal sequence subjected to the two-stage interference suppression by adopting a standard MLSE (maximum likelihood sequence) method according to the obtained channel vector h, thereby further improving the anti-interference performance of the algorithm.
The present embodiment also proposes a computer device (receiving end device) for executing the above method of the present embodiment.
As shown in fig. 2 in particular, the computer device includes a processor, an internal memory, and a system bus; various device components including internal memory and processors are connected to the system bus. A processor is hardware used to execute computer program instructions through basic arithmetic and logical operations in a computer system. An internal memory is a physical device used to temporarily or permanently store computing programs or data (e.g., program state information). The system bus may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus. The processor and the internal memory may be in data communication via a system bus. Including read-only memory (ROM) or flash memory (not shown), and Random Access Memory (RAM), which typically refers to main memory loaded with an operating system and computer programs.
Computer devices typically include an external storage device. The external storage device may be selected from a variety of computer readable media, which refers to any available media that can be accessed by the computer device, including both removable and non-removable media. For example, computer-readable media includes, but is not limited to, flash memory (micro SD cards), CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer device.
A computer device may be logically connected in a network environment to one or more network terminals. The network terminal may be a personal computer, a server, a router, a smart phone, a tablet, or other common network node. The computer apparatus is connected to the network terminal through a network interface (local area network LAN interface). A Local Area Network (LAN) refers to a computer network formed by interconnecting within a limited area, such as a home, a school, a computer lab, or an office building using a network medium. WiFi and twisted pair wiring ethernet are the two most commonly used technologies to build local area networks.
It should be noted that other computer systems including more or less subsystems than computer devices can also be suitable for use with the invention.
As described in detail above, the computer device adapted to the present embodiment can perform the specified operations of the space-time joint anti-interference method. The computer device performs these operations in the form of software instructions executed by a processor in a computer-readable medium. These software instructions may be read into memory from a storage device or from another device via a local area network interface. The software instructions stored in the memory cause the processor to perform the method of processing group membership information described above. Furthermore, the present invention can be implemented by hardware circuits or by a combination of hardware circuits and software instructions. Thus, implementation of the present embodiments is not limited to any specific combination of hardware circuitry and software.
Example 2
The embodiment provides a space-time joint anti-jamming device suitable for satellite communication, and specifically, as shown in fig. 3, the device of the embodiment includes a direction-of-arrival estimation module, a primary interference suppression module, a secondary interference suppression module, and a sequence detection module.
The direction estimation module adopts the MUSIC algorithm to estimate the direction of arrival of the received signal.
The first-stage interference suppression module solves a beamforming weight vector based on an LCMV optimization criterion, and performs weighting processing on a received signal to realize first-stage interference suppression.
The secondary interference suppression module firstly performs dimensionality extension on the signals subjected to the primary interference suppression according to a guide vector principle, then solves the beamforming weight vector and the number of the signals again by adopting a space-time processing method (namely JST algorithm) based on an SINR (signal to interference plus noise ratio) criterion, and performs weighting processing on the signals subjected to the dimensionality extension to realize the secondary interference suppression.
And the sequence detection module detects the signal subjected to the second-stage interference suppression by adopting a standard MLSE method to recover a useful symbol sequence.
The embodiment also provides satellite communication equipment which comprises the anti-interference device.
Example 3
In this embodiment, the anti-interference method provided in the above embodiment is subjected to simulation verification, and the specific conditions of the simulation experiment are as follows: the length of the training sequence is 26, the length of the information sequence is 114, the number of antenna elements M is 16, the number of multipaths is 3, the length of channel memory is 4, the number of interference users is 2, and the modulation mode is BPSK.
Fig. 4 is a Bit Error Rate (BER) comparison curve of the method of the present invention and the JST method under the above specific simulation conditions at different signal to interference ratios. The abscissa of the graph is the signal-to-interference ratio (unit: dB) and the ordinate is the Bit Error Rate (BER). The symbol ". smallcircle" in the figure represents the JST method and "□" represents the method of the present invention.
As can be seen from the view of figure 4,the anti-interference performance of the method is superior to that of a JST method. When the code rate is 10-5Compared with a JST algorithm, the anti-interference performance of the method is improved by about 15 dB.
FIG. 5 is a Bit Error Rate (BER) comparison curve of the method of the present invention and the anti-interference method based on the LCMV optimization criterion under the specific simulation conditions. The abscissa of the graph is the signal-to-interference ratio (unit: dB) and the ordinate is the Bit Error Rate (BER). In the figure, the mark ". smallcircle" represents an anti-interference method based on LCMV optimization criteria, and "□" represents the method of the invention.
As can be seen from FIG. 5, the anti-interference performance of the method of the invention is superior to that of the anti-interference method based on the LCMV optimization criterion. When the bit error rate is 10-5Compared with an anti-interference method based on LCMV optimization criterion, the anti-interference performance of the method is improved by about 18 dB.
FIG. 6 is a comparison curve of the Bit Error Rate (BER) under different SNR according to the present invention under the above specific simulation conditions. The abscissa of the graph is the signal-to-noise ratio (unit: dB) and the ordinate is the Bit Error Rate (BER). In the figure, the symbol "x" represents the error rate curve of the method according to the invention at a signal to interference ratio of-40 dB, ". o" represents the error rate curve of the method according to the invention at a signal to interference ratio of-30 dB, ". o" represents the error rate curve of the method according to the invention at a signal to interference ratio of-20 dB, and "□" represents the error rate curve of the method according to the invention at a signal to interference ratio of 0 dB.
As can be seen from FIG. 6, when the signal-to-interference ratio is-40 dB and-30 dB, the error rate curve of the method of the present invention has a flat layer phenomenon, and at this time, the anti-interference performance of the algorithm is greatly influenced by the interference power. Along with the increase of the signal-to-interference ratio, the anti-interference capability of the algorithm is improved to some extent, when the signal-to-interference ratio is 0dB, the flat layer phenomenon disappears, and the error rate is rapidly reduced along with the increase of the signal-to-noise ratio.
Fig. 7 is a Bit Error Rate (BER) comparison curve of the method of the present invention with the LMS method, the RLS method, the CMA method, the anti-interference method based on the LCMV optimization criterion, and the JST method under different signal-to-interference ratios under the above specific simulation conditions. The abscissa of the graph is the signal-to-interference ratio (unit: dB) and the ordinate is the Bit Error Rate (BER). In the figure, "+" represents the error rate curve of the LMS method, "×" represents the error rate curve of the RLS method, "-" represents the error rate curve of the CMA method, "diamond-shaped" represents the error rate curve of the anti-interference method based on the LCMV optimization criterion, ". smallcircle" represents the error rate curve of the JST method, and "□" represents the error rate curve of the method of the present invention.
As can be seen from fig. 7, the method of the present invention has better anti-interference performance compared with the conventional anti-interference method. When the bit error rate is 10-5Compared with a JST method, the anti-interference performance of the method is improved by about 15 dB; compared with an anti-interference method based on LCMV optimization criterion, the anti-interference performance of the method is improved by about 18 dB; compared with an LMS method, an RLS method and a CMA method, the method has the advantage that the anti-interference performance is improved more obviously.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (7)

1. A space-time joint anti-interference method suitable for satellite communication is characterized by comprising the following steps:
estimating the direction of arrival of the received signal by adopting a multiple signal classification algorithm;
solving a beamforming weight vector by adopting a linear constraint minimum variance optimization criterion based on the direction of arrival of the expected signal; the direction of arrival of the expected signal is the direction of arrival of a useful signal in the received signal;
performing first-stage interference suppression processing on the received signals according to the beamforming weight vector;
performing dimensionality extension on the signal subjected to the first-stage interference suppression processing according to a guide vector principle;
adopting a space-time processing method based on a maximized signal interference-to-noise ratio criterion to solve the beamforming weight vector again, specifically comprising the following steps:
after N times of snapshotsPost-reception sequence Y ═ Y (1) Y (2) Y (3) … Y (n)]Calculating a covariance matrix
Figure FDA0003324024760000011
Similarly, the matrix is respectively calculated by combining the training sequence T known by the receiving end
Figure FDA0003324024760000012
Figure FDA0003324024760000013
Further constructing a matrix
Figure FDA0003324024760000014
Wherein, YHDenotes the conjugate transpose of Y, THThe conjugate transpose of T is represented,
Figure FDA0003324024760000015
to represent
Figure FDA0003324024760000016
The inverse matrix of (d);
solving for RsIf the characteristic vector q corresponding to the minimum characteristic value is the channel vector, estimating h as q;
re-solving beamforming weight vectors
Figure FDA0003324024760000017
Performing second-stage interference suppression processing on the signals subjected to the dimensionality extension according to the beamforming weight vector obtained by solving again;
and detecting the signal subjected to the second-stage interference suppression by adopting a standard maximum likelihood sequence estimation method to recover the useful symbol sequence.
2. A space-time joint anti-interference method suitable for satellite communication according to claim 1, wherein the beamforming weight vector obtained by solving using a linear constraint minimum variance optimization criterion is:
w1＝R-1C(CHR-1C)-1f
wherein, C is a constraint matrix constructed by a steering vector corresponding to the direction of arrival of the obtained signal; f is a constraint vector relating to the desired signal direction; and R is a sampling covariance matrix of signals received by the antenna array.
3. A space-time joint anti-interference method suitable for satellite communication according to claim 2, wherein the step of performing the first-stage interference suppression processing on the received signal according to the beamforming weight vector specifically comprises:
using the weight vector w obtained by solving1Weighting the received signal x (k) of the antenna array at the k-th time, and outputting the signal
Figure FDA0003324024760000021
4. A space-time joint anti-interference method suitable for satellite communication according to claim 3, wherein the step of performing dimension expansion on the signal subjected to the first-stage interference suppression processing according to the steering vector principle specifically comprises:
corresponding to the steering vector a according to the normal direction of the antenna array0Expanding x' (k) with the dimension of the guide vector a0The dimension M of (a), the expanded signal being y (k) a0x′(k)。
5. A space-time joint anti-interference method suitable for satellite communication according to claim 4, wherein the step of performing the second-stage interference suppression processing on the signals subjected to the dimension expansion according to the beamforming weight vector obtained by the re-solving specifically comprises:
according to the beam forming weight vector w obtained by solving again2Weighting the signals y (k) after the dimension expansion to obtain
Figure FDA0003324024760000022
And realizing second-stage interference suppression.
6. A space-time joint anti-jamming device suitable for satellite communication is characterized by comprising a direction-of-arrival estimation module, a primary interference suppression module, a secondary interference suppression module and a sequence detection module;
the direction-of-arrival estimation module estimates the direction of arrival of the received signal by adopting a multi-signal classification algorithm;
the primary interference suppression module solves a beamforming weight vector by adopting a linear constraint minimum variance optimization criterion, and performs weighting processing on a received signal to realize primary interference suppression;
the secondary interference suppression module firstly performs dimensionality extension on the signals subjected to the primary interference suppression according to a guide vector principle, then solves a beam forming weight vector again by adopting a space-time processing method based on a maximized signal interference-to-noise ratio criterion, and performs weighting processing on the signals subjected to the dimensionality extension to realize secondary interference suppression; the concrete process of solving the beamforming weight vector again by adopting the space-time processing method based on the maximization signal interference-to-noise ratio criterion comprises the following steps:
after N times of snapshots, the sequence Y is received [ Y (1) Y (2) Y (3) … Y (N)]Calculating a covariance matrix
Figure FDA0003324024760000031
Similarly, the matrix is respectively calculated by combining the training sequence T known by the receiving end
Figure FDA0003324024760000032
Figure FDA0003324024760000033
Further constructing a matrix
Figure FDA0003324024760000034
Wherein, YHDenotes the conjugate transpose of Y, THThe conjugate transpose of T is represented,
Figure FDA0003324024760000035
to represent
Figure FDA0003324024760000036
The inverse matrix of (d);
solving for RsIf the characteristic vector q corresponding to the minimum characteristic value is the channel vector, estimating h as q;
re-solving beamforming weight vectors
Figure FDA0003324024760000037
And the sequence detection module detects the signal subjected to the second-stage interference suppression by adopting a standard maximum likelihood sequence estimation method, and recovers a useful symbol sequence.
7. A satellite communication device, characterized in that it comprises the space-time joint interference rejection apparatus suitable for satellite communication according to claim 6.
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