CN113507307A - 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 PDFInfo
- Publication number
- CN113507307A CN113507307A CN202111053717.9A CN202111053717A CN113507307A CN 113507307 A CN113507307 A CN 113507307A CN 202111053717 A CN202111053717 A CN 202111053717A CN 113507307 A CN113507307 A CN 113507307A
- Authority
- CN
- China
- Prior art keywords
- signal
- interference
- interference suppression
- space
- weight vector
- 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
- 238000000034 method Methods 0.000 title claims abstract description 114
- 238000004891 communication Methods 0.000 title claims abstract description 30
- 239000013598 vector Substances 0.000 claims abstract description 75
- 230000001629 suppression Effects 0.000 claims abstract description 62
- 238000012545 processing Methods 0.000 claims abstract description 33
- 238000005457 optimization Methods 0.000 claims abstract description 24
- 238000003672 processing method Methods 0.000 claims abstract description 12
- 239000011159 matrix material Substances 0.000 claims description 15
- 230000008569 process Effects 0.000 claims description 8
- 238000012549 training Methods 0.000 claims description 8
- 238000001514 detection method Methods 0.000 claims description 6
- 238000007476 Maximum Likelihood Methods 0.000 claims description 5
- 238000007635 classification algorithm Methods 0.000 claims description 5
- 230000007480 spreading Effects 0.000 claims description 3
- 238000004422 calculation algorithm Methods 0.000 abstract description 10
- 238000005516 engineering process Methods 0.000 description 20
- 238000004088 simulation Methods 0.000 description 6
- 230000008901 benefit Effects 0.000 description 5
- 230000002452 interceptive effect Effects 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 230000002829 reductive effect Effects 0.000 description 3
- 108010076504 Protein Sorting Signals Proteins 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000004590 computer program Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000005764 inhibitory process Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 238000001228 spectrum Methods 0.000 description 2
- 244000068485 Convallaria majalis Species 0.000 description 1
- 235000009046 Convallaria majalis Nutrition 0.000 description 1
- 235000000836 Epigaea repens Nutrition 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000002401 inhibitory effect Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000000452 restraining effect Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000010845 search algorithm Methods 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Noise Elimination (AREA)
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
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:
wherein,a constraint matrix constructed by steering vectors corresponding to the directions of arrival of the resulting signals;is a constraint vector related to the desired signal direction;a sampled covariance matrix of the signal is received for 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 weight vectors obtained by solvingTo the firstTime antenna array receiving signalA weighting process of outputting a signal of。
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 guide vector according to normal direction of antenna arrayTo pairPerforming expansion with dimension ofMThe signal after spreading is。
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:
Similarly, the matrix is respectively calculated by combining the training sequence T known by the receiving endFurther constructing a matrix;
Solving forFeature vector corresponding to minimum feature valueThen the channel vector is estimated as;
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 weight vector obtained by solving againFor signals after the dimension expansionThe weighting process is obtainedAnd 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 space-time joint anti-interference device suitable for satellite communication.
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.
Drawings
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 =16, the number of multipaths, 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). 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 the training sequence length is 26, the information sequence length is 114, the number of antenna elements M =16, the number of multipaths, the channel memory length is 4, the number of interfering users is 2, and the modulation method is BPSK, and when the signal to interference ratios are different. 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 =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-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 =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:
wherein the constraint matrixConstructing a steering vector corresponding to the direction of arrival of the signal obtained in step 101,is related to the desired signal directionAnd (5) restraining the vector.
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 obtained by solving according to the step 102To the firstTime antenna array receiving signalA weighting process of outputting a signal of。
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 according to the normal direction of the antenna arrayTo pairPerforming expansion with dimension ofMThe signal after spreading isWhereinMIs 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:
Similarly, the matrix is respectively calculated by combining the training sequence T known by the receiving endFurther constructing a matrix;
Step 202, solvingFeature vector corresponding to minimum feature valueThen the channel vector is estimated as;
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 obtained by the re-solvingFor signals after the dimension expansionThe weighting process is obtainedAnd 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.
This embodiment step 107 is based on the obtained channel vectorFor signals after the second stage interference suppressionAnd detecting and recovering the 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 by adopting an LCMV (liquid Crystal display television) optimization criterion based on the direction of the expected signalsAccording to the resultReceiving signals to an antenna arrayAnd carrying out weighting processing to realize first-stage interference suppression, wherein the energy of the interference signal is fully reduced after the first-stage suppression. Then, according to the principle of guide vector, the signal after the first stage interference suppression is carried outDimension is expanded, and then a space-time processing method based on a maximized signal-to-interference-and-noise ratio criterion is adopted to solve channel vectorsSum beamforming weight vectorAccording to the resultFor signals after the dimension expansionPerforming weighting processing to realize second-stage interference suppression, and finally obtaining channel vectorAnd the signal sequence subjected to two-stage interference suppression is detected by adopting a standard MLSE method, so that the anti-interference performance of the algorithm is further improved.
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 =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 FIG. 4, the anti-interference performance of the method of the invention is superior to that of a JST method. When the code rate isCompared 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 error rate isCompared 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, compared with the conventional interference rejection methodThe method has better anti-interference performance. When the error rate isCompared 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 (8)
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;
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.
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:
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:
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:
5. A space-time joint anti-interference method suitable for satellite communication according to claim 4, wherein the step of solving the beamforming weight vector again by using a space-time processing method based on a maximized signal interference-to-noise ratio criterion specifically comprises:
throughReceiving sequence after sub-snapshotComputing assistantVariance matrixSimilarly, the matrix is calculated respectively by combining the training sequence T known by the receiving endFurther constructing a matrix;
Solving forFeature vector corresponding to minimum feature valueThen the channel vector is estimated as;
6. A space-time joint anti-interference method suitable for satellite communication according to claim 5, 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:
7. 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;
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.
8. A satellite communication device, characterized by comprising the space-time joint interference rejection apparatus suitable for satellite communication according to claim 7.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111053717.9A CN113507307B (en) | 2021-09-09 | 2021-09-09 | Space-time joint anti-interference method, device and equipment suitable for satellite communication |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111053717.9A CN113507307B (en) | 2021-09-09 | 2021-09-09 | Space-time joint anti-interference method, device and equipment suitable for satellite communication |
Publications (2)
Publication Number | Publication Date |
---|---|
CN113507307A true CN113507307A (en) | 2021-10-15 |
CN113507307B CN113507307B (en) | 2021-12-07 |
Family
ID=78016769
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202111053717.9A Active CN113507307B (en) | 2021-09-09 | 2021-09-09 | Space-time joint anti-interference method, device and equipment suitable for satellite communication |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113507307B (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114325600A (en) * | 2021-12-22 | 2022-04-12 | 广东邦盛北斗科技股份公司 | Anti-interference method, system and device for Beidou navigation system and cloud platform |
Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101079662A (en) * | 2006-05-25 | 2007-11-28 | 上海原动力通信科技有限公司 | Method, system and device for uplink communication of multi-antenna terminal |
US20090175366A1 (en) * | 2005-09-30 | 2009-07-09 | Alexander Maltsev | Method and scheme for space-time coded cochannel interference cancellation |
WO2010016924A1 (en) * | 2008-08-06 | 2010-02-11 | Atc Technologies, Llc | Systems, methods and devices for overlaid operation of satellite and terrestrial wireless communications systems |
CN101718873A (en) * | 2009-11-13 | 2010-06-02 | 西安电子科技大学 | Homing signal space-time anti-interference digital signal processor |
EP2352326A1 (en) * | 2008-10-30 | 2011-08-03 | Mitsubishi Electric Corporation | Communication device and communication system |
EP2484027A1 (en) * | 2009-09-28 | 2012-08-08 | ATC Technologies, LLC | Systems and methods for adaptive interference cancellation beamforming |
US20130154880A1 (en) * | 2011-12-15 | 2013-06-20 | Jeff Dickman | Digital beamforming for simultaneously mitigating weak and strong interference in a navigation system |
CN108663693A (en) * | 2018-07-25 | 2018-10-16 | 电子科技大学 | A kind of high-dynamic GNSS null broadening disturbance restraining method based on space time processing |
CN111211826A (en) * | 2020-01-10 | 2020-05-29 | 中国人民解放军战略支援部队航天工程大学 | Recursive structure beam forming method and device |
CN111537958A (en) * | 2020-06-10 | 2020-08-14 | 成都电科慧安科技有限公司 | Beam forming method of wide-linearity reduced-rank minimum entropy distortion-free response |
CN111880198A (en) * | 2020-07-28 | 2020-11-03 | 中国海洋大学 | Space-time polarization anti-interference method based on alternating polarization sensitive array |
-
2021
- 2021-09-09 CN CN202111053717.9A patent/CN113507307B/en active Active
Patent Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20090175366A1 (en) * | 2005-09-30 | 2009-07-09 | Alexander Maltsev | Method and scheme for space-time coded cochannel interference cancellation |
CN101079662A (en) * | 2006-05-25 | 2007-11-28 | 上海原动力通信科技有限公司 | Method, system and device for uplink communication of multi-antenna terminal |
WO2010016924A1 (en) * | 2008-08-06 | 2010-02-11 | Atc Technologies, Llc | Systems, methods and devices for overlaid operation of satellite and terrestrial wireless communications systems |
EP2352326A1 (en) * | 2008-10-30 | 2011-08-03 | Mitsubishi Electric Corporation | Communication device and communication system |
EP2484027A1 (en) * | 2009-09-28 | 2012-08-08 | ATC Technologies, LLC | Systems and methods for adaptive interference cancellation beamforming |
CN101718873A (en) * | 2009-11-13 | 2010-06-02 | 西安电子科技大学 | Homing signal space-time anti-interference digital signal processor |
US20130154880A1 (en) * | 2011-12-15 | 2013-06-20 | Jeff Dickman | Digital beamforming for simultaneously mitigating weak and strong interference in a navigation system |
CN108663693A (en) * | 2018-07-25 | 2018-10-16 | 电子科技大学 | A kind of high-dynamic GNSS null broadening disturbance restraining method based on space time processing |
CN111211826A (en) * | 2020-01-10 | 2020-05-29 | 中国人民解放军战略支援部队航天工程大学 | Recursive structure beam forming method and device |
CN111537958A (en) * | 2020-06-10 | 2020-08-14 | 成都电科慧安科技有限公司 | Beam forming method of wide-linearity reduced-rank minimum entropy distortion-free response |
CN111880198A (en) * | 2020-07-28 | 2020-11-03 | 中国海洋大学 | Space-time polarization anti-interference method based on alternating polarization sensitive array |
Non-Patent Citations (2)
Title |
---|
VALERY N.TYAPKIN: "Interference cancelling response for various configurations of antenna arrays for angular measuring navigation equipment", 《2015 INTERNATIONAL SIBERIAN CONFERENCE ON CONTROL AND COMMUNICAITONS》 * |
王琼: "卫星导航终端智能天线抗干扰技术应用研究", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114325600A (en) * | 2021-12-22 | 2022-04-12 | 广东邦盛北斗科技股份公司 | Anti-interference method, system and device for Beidou navigation system and cloud platform |
CN114325600B (en) * | 2021-12-22 | 2023-09-26 | 广东邦盛北斗科技股份公司 | Anti-interference method, system and device for Beidou navigation system and cloud platform |
Also Published As
Publication number | Publication date |
---|---|
CN113507307B (en) | 2021-12-07 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN102474333B (en) | Base station device and method and communication system thereof | |
US20070249350A1 (en) | Apparatus and method for canceling neighbor cell interference in broadband wireless communication system | |
CN108322277B (en) | Frequency spectrum sensing method based on inverse eigenvalue of covariance matrix | |
CN101291165A (en) | Sequence detecting method and apparatus for multi-antenna system | |
Kabeel et al. | A utilization of multiple antenna elements for matched filter based spectrum sensing performance enhancement in cognitive radio system | |
CN113507307B (en) | Space-time joint anti-interference method, device and equipment suitable for satellite communication | |
CN110932806A (en) | Multi-antenna spectrum sensing method under alpha stable noise fading channel | |
CN103701515B (en) | Digital multi-beam forming method | |
JP5506109B2 (en) | Perturbation decoder and decoding method in communication system and apparatus using the same | |
CN112910518A (en) | Method for estimating number of transmitting antennas of MIMO system under non-Gaussian noise in unmanned aerial vehicle communication | |
CN113556157B (en) | Method and system for estimating number of transmitting antennas of MIMO system under non-Gaussian interference | |
Zheng et al. | Uplink channel estimation and signal extraction against malicious IRS in massive MIMO system | |
Jeon et al. | Superresolution TOA estimation with computational load reduction | |
Lu et al. | Variable step-size normalized subband adaptive filtering algorithm for self-interference cancellation | |
EP1585245A1 (en) | Estimation method for noise space correlated characteristics in time slot cdma system | |
Wang et al. | Blind spectrum sensing by information theoretic criteria | |
Siriteanu et al. | Maximal-ratio eigen-combining: a performance analysis | |
CN101582703B (en) | Method and device for signal channel estimation denoising post-treatment in multiantenna system | |
Nishimura et al. | Space domain multistage interference canceller for SDMA | |
Abdo et al. | Adaptive Direction of Arrival Estimation Algorithms for 5G Network and Beyond | |
CN111929707B (en) | Interference suppression method, device, electronic equipment and readable storage medium | |
Nicoli et al. | Reduced rank channel estimation and rank order selection for CDMA systems | |
CN118549953B (en) | Satellite navigation anti-interference method and system based on parallel hierarchical diagonal loading | |
CN118033583B (en) | Method for detecting distance expansion target under Gaussian clutter background | |
CN1588931A (en) | Channel elaluation method based on iterative interference reduction |
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 |