CN110850445A - Pulse interference suppression method based on space-time sampling covariance inversion - Google Patents
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- G—PHYSICS
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- 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
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Abstract
The invention discloses a pulse interference suppression method based on space-time sampling covariance inversion, which belongs to the technical field of array signal processing, and aims at the phenomenon that the anti-interference performance is reduced when the weight convergence time of an anti-interference algorithm of space-time sampling covariance inversion is coherent with a pulse period. The invention can adaptively form the null in the interference incoming wave direction without knowing the number of the suppressed pulse interference and estimating the incoming wave direction, thereby achieving the purpose of suppressing the interference. The method is simple to implement and can be embedded into a satellite receiver as an independent anti-interference module.
Description
Technical Field
The invention belongs to the technical field of array signal processing, and particularly relates to a pulse interference suppression method based on space-time sampling covariance inversion.
Background
Satellite navigation systems (GPS, beidou, GLONASS) can provide all-weather, high-precision navigation positioning information for various users all over the world, but satellite navigation signals reaching the ground are extremely weak. Taking GPS as an example, the power of the satellite navigation signal radiated to the ground is only about-130 dBm, and the signal is submerged in the noise of the receiver itself, which is easily affected by various kinds of suppression interference, so that the satellite receiver cannot work because the satellite signal cannot be locked. Experiments show that the jammer with the power of 1W can prevent a GPS civil receiver within 85 kilometers around from working. In order to enable a receiver to operate with high reliability in a surrounding complex electromagnetic environment, it is necessary to add an anti-interference function to the receiver. The anti-interference method is various, such as time domain filtering, frequency domain filtering, side lobe cancellation, space domain filtering, space-time filtering and the like, wherein the most effective method is the space-time filtering technology based on the array antenna.
The pulse interference mainly comprises signals radiated by Bluetooth, civil aviation DME answering machines, radio stations, radars and the like in the environment and also comprises malicious interference applied artificially. At present, the technology of the anti-interference array antenna in China is greatly developed, but the anti-interference array antenna has own weakness aiming at pulse type interference, and the anti-interference capability is reduced in different degrees according to different implementation algorithms. At present, in China, documents are researched for resisting pulse interference in a time-frequency domain, but only pulse interference with small duty ratio can be effectively conducted, and the research on resisting pulse interference by specially aiming at an array antenna is not seen. The anti-pulse interference of the array antenna is a spatial filtering method, and the interference can be distinguished from the spatial domain to have an effect on the interference of any duty ratio, so that a pulse interference suppression method based on the array antenna is needed to be provided.
Disclosure of Invention
In order to solve the above problems, an object of the present invention is to provide a method for suppressing pulse interference based on space-time sampling covariance inversion, so as to ensure good anti-interference performance of an algorithm when weight convergence time is coherent with a pulse period, so that a receiver can normally capture a satellite signal.
The technical scheme of the invention is as follows: a method for suppressing pulse interference based on space-time sampling covariance inversion is characterized in that a suppression strategy of pulse interference is adjusted, and the operation steps are as follows:
1) performing AD sampling on signals received by the antenna array to convert the signals into multi-path digital signals;
2) calculating the period of the pulse interference;
3) judging whether the weight convergence time is coherent with the pulse period, if not, calculating the weight according to the original algorithm implementation program to complete space-time domain filtering; if the correlation exists, the accumulated point number of the covariance matrix is increased by four times, the weight convergence time is increased by four times, and the problem that the anti-interference performance is poor when the correlation exists with the weight convergence time is solved by adopting a method of moving the sensitive area.
When the pulse interference period is calculated in the step 2), the number of points exceeding a blanking threshold is judged by adopting a sliding window method to determine the pulse interference period;
in the step 3), a basic framework of the algorithm adopts a space-time two-dimensional filtering mode, and different antenna array elements form space-domain filtering from the same time delay node, so that spatial interference sources can be distinguished, and space-domain null is formed to inhibit space-domain interference; from each antenna array element channel, each stage of time delay forms time domain FIR filtering, interference cancellation is carried out in the time domain, and signals can be deeply analyzed in the time domain so as to inhibit interference.
In the algorithm in step 3), the weight calculation adopts an algorithm of sampling covariance inversion (SMI), a covariance matrix is estimated by using the received snapshot data, and a weight vector is obtained, namely:
wherein
Is an estimate of the covariance matrix, L is the accumulated data length, X (t)i) For sampled data vectors, H is the matrix operator, representing the conjugate transpose of the matrix.
In the algorithm in the step 3), when the pulse width is coherent with the weight convergence time, the number of the accumulated points of the covariance matrix is increased by a certain multiple, and the weight convergence time is correspondingly increased, so that the sensitive area can be moved, and a better pulse interference suppression effect is achieved.
The invention has the beneficial effects that: the method is combined with the traditional space-time two-dimensional anti-interference algorithm, can effectively inhibit pulse interference of different pulse periods, adaptively forms null in the direction of arrival of the interference under the condition of not knowing the direction of arrival and the number of the interference, improves the capability of resisting various interferences of a navigation receiver, and has certain practical value. The invention is simple to realize and can be embedded into a common receiver as an independent anti-interference module.
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FIG. 1 is a schematic block diagram of the basic process (improved strategy for space-time anti-interference algorithm) of the present invention;
FIG. 2 is a schematic block diagram of a space-time anti-interference algorithm according to the present invention;
fig. 3 is a block diagram of a space-time anti-interference algorithm implementation flow (a specific implementation manner of the improved space-time anti-interference algorithm, which is the specific implementation manner of fig. 1 and fig. 2:
FIG. 4 is a schematic diagram of pulse duty cycle;
FIG. 5 is a three broadband impulse interference spatial directional diagram;
fig. 6 is a plot of useful signal acquisition correlation peaks after interference suppression.
Detailed Description
The impulse interference suppression method based on the space-time sampling covariance inversion provided by the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.
As shown in fig. 1 and fig. 2, the impulse interference suppression method based on space-time sampling covariance inversion provided by the present invention includes the following steps performed in sequence:
1) conversion of the received signal: and AD sampling is carried out on the signals received by the antenna array, and the signals are converted into multi-path digital signals.
Aiming at the characteristic of interference suppression in signal receiving processing, the method can be equivalent to that P far-field signals are incident on a certain array in space, wherein the array antenna consists of M array elements, and after receiving the signals, each array element is sent to a processor through a respective transmission channel, namely the processor receives data from M channels. The received signal may be represented in the form of a complex envelope as follows:
in the above formula, τ represents time delay, ui(t) is the amplitude of the received signal,
is the phase of the received signal. Omega0Is the frequency of the received signal or signals,
c is the speed of light and λ is the wavelength of the incident signal. Under the assumption of a narrow-band far-field signal source, there are:
from the above two equations, the following holds:
then, the m-th array element received signal can be obtained as:
wherein M is the number of antenna elements, gmiRepresenting the gain of the ith signal over the m-th element, nm(t) represents the noise of the m-th array element at time t, τmiRepresenting the time delay of the ith signal arriving at the mth array element relative to the reference array element.
Arranging the signals received by the M array elements at a specific time into a column vector to obtain:
in an ideal situation, assuming that each array element in the array is isotropic and has no influence of factors such as channel inconsistency and mutual coupling, normalization processing can obtain:
written in vector form as follows:
X(t)＝AS(t)+N(t)
where x (t) is an M × 1 dimensional snapshot data vector of the array, s (t) is an N × 1 dimensional vector of the spatial signal, N (t) is an M × 1 dimensional noise data vector of the array, a is an M × N dimensional flow pattern matrix (also referred to as a steering vector matrix) of the spatial array, and:
A＝[a1(ω0) a2(ω0) … aP(ω0)]
wherein the steering vector is:
from the above discussion, it can be seen that for a general far-field narrow-band signal, the time delay τ between array elements results in the phase difference Φ ═ e between array elements-jωτThereby forming an array flow pattern of the array space. And performing beam forming and spatial spectrum estimation by using the phase difference information among the array elements, and further suppressing the interference signals.
2) Calculate (impulse) interference period:
calculating the pulse period, namely judging the number of points exceeding a blanking threshold by adopting a sliding window method to judge the period of pulse interference;
3) and judging whether the weight convergence time is coherent with the pulse period. If the two are not coherent, performing weight calculation according to an original algorithm implementation program to complete space-time domain filtering; if the correlation exists, the number of the accumulated points of the covariance matrix is increased by four times, the weight convergence time is increased by four times, and the problem that the anti-interference performance is poor when the correlation exists with the weight convergence time is solved by moving away the sensitive area.
The basic frame of the algorithm adopts a space-time two-dimensional filtering method, as shown in fig. 2, from the same time delay node, different antenna array elements form adaptive filtering of a space domain, namely space domain filtering, so that spatial interference sources can be distinguished, and space domain null is formed to suppress space domain interference; from each antenna array element channel, each stage of time delay forms time domain FIR filtering, interference cancellation is carried out in the time domain according to the self-adaptive filtering principle, and signals can be deeply analyzed in the time domain so as to inhibit interference. The space-time joint processing can suppress interference on a two-dimensional plane of a space domain and a frequency domain. The degree of freedom is higher compared with that of spatial filtering, and the electromagnetic interference on the periphery can be better dealt with.
In the algorithm in the step 3), a sampling covariance inversion mode (SMI algorithm) is adopted for obtaining the weight, and the SMI algorithm is to estimate a covariance matrix by using received snapshot data and then obtain a weight vector. The specific implementation steps are shown in fig. 3, and the detailed steps are as follows:
estimation of covariance matrix: in the anti-interference algorithm, M array elements and P taps are adopted, and the snapshot vector received at time k is X ═ X11x12…x1Px21x22…x2P……xM1xM2…xMP]T. Collecting N space-time snapshots, the space-time covariance matrix is
Calculating a self-adaptive weight: after the covariance matrix is obtained, the adaptive weight can be calculated according to the following formula.
Wherein the content of the first and second substances,
as＝[1 1 1 1]，at＝[1 0 0 0]。
and carrying out complex multiplication on the self-adaptive weight and the delayed signal and weighting to synthesize a path of signal so as to finish self-adaptive space-time filtering of the signal. The received total signal X and the space-time weight vector W are respectively converted into an MP multiplied by 1 dimensional column vector after passing through a matrix vectorization operator:
X＝[x11x12…x1Px21x22…x2P……xM1xM2…xMP]T
W＝[w11w12…w1Pw21w22…w2P……wM1wM2…wMP]T
the output of the space-time processing is:
y＝WHX
the output signal to interference and noise ratio is then:
wherein R isη＝E(ηηH) For the interference plus noise covariance matrix, Rs＝E(ssH) For the covariance matrix of the navigation signal
In the algorithm in the step 3), when the pulse width is coherent with the weight convergence time, the number of the accumulated points of the covariance matrix is increased by a certain multiple, and the weight convergence time is correspondingly increased, so that the sensitive area can be moved, and a better pulse interference suppression effect is achieved.
Because the pulse period interval with poor anti-interference performance is related to the weight convergence time, a combined filtering method with adjustable weight convergence time is provided to solve the problem of pulse interference suppression of the SMI algorithm. The core idea is as follows: when the pulse period is in the weight convergence time coherent interval, the weight convergence time is adjusted to remove the sensitive region, and the adjusted weight convergence time coherent interval is not overlapped with the original weight convergence time coherent region by a method of prolonging the accumulation time of the covariance matrix. For example, when the cumulative covariance point number is 1024 points, the weight convergence time is 25us, the sensitive region is 30 us-80 us, while the cumulative covariance point number is 4096 points, the weight convergence time is 200us, and the sensitive region is 160 us-240 us. The detailed description is shown in fig. 4.
Fig. 5 is a three-wideband impulse interference spatial domain directional diagram of the proposed algorithm. Simulation conditions are as follows: the interference mode adopts band-limited white Gaussian noise, the bandwidth is 20MHz, the signal is a Beidou signal, the signal-to-noise ratio is-25 dB, and simulation is carried out according to three-broadband interference. Under the condition of three-broadband interference, the interference-to-noise ratio is set to be 90dB (the interference-to-signal ratio is 115dB), the pitch angle of interference 1 is 50 degrees, the azimuth angle is 60 degrees, the pitch angle of interference 2 is 50 degrees, the azimuth angle is 180 degrees, the pitch angle of interference 3 is 50 degrees, the azimuth angle is 300 degrees, the period of three interference pulses is 1ms, and the duty ratio is 50%. As seen from the figure, the three interference directions all form a null no less than 100dB, and the three pulse interference is effectively suppressed.
Fig. 6 is a useful signal acquisition correlation peak curve after interference resistance. The simulation conditions are the same as those in fig. 5, and it is seen from the figure that the interference is effectively suppressed, and the useful navigation signal can be normally captured.
Through the test of an actual hardware platform, the improved SMI algorithm can effectively inhibit various pulse interferences of pulse period change and ensure the normal work of a receiver.
Claims (5)
1. A method for suppressing pulse interference based on space-time sampling covariance inversion is characterized in that a suppression strategy of pulse interference is adjusted, and the operation steps are as follows:
1) performing AD sampling on signals received by the antenna array to convert the signals into multi-path digital signals;
2) calculating the period of the pulse interference;
3) judging whether the weight convergence time is coherent with the pulse period, if not, calculating the weight according to the original algorithm implementation program to complete space-time domain filtering; if the correlation exists, the accumulated point number of the covariance matrix is increased by four times, the weight convergence time is increased by four times, and the problem that the anti-interference performance is poor when the correlation exists with the weight convergence time is solved by adopting a method of moving the sensitive area.
2. A method for suppressing impulse interference based on space-time sampling covariance inversion according to claim 1, wherein when the impulse interference period is calculated in step 2), a sliding window method is used to determine the number of points exceeding a blanking threshold to determine the impulse interference period.
3. A pulse interference suppression method based on space-time sampling covariance inversion according to claim 1, wherein a basic framework of an algorithm in step 3) adopts a space-time two-dimensional filtering mode, and different antenna array elements form space filtering from the same time delay node, so that spatial interference sources can be resolved, and space-domain null steering suppression space-domain interference is formed; from each antenna array element channel, each stage of time delay forms time domain FIR filtering, interference cancellation is carried out in the time domain, and signals can be deeply analyzed in the time domain so as to inhibit interference.
4. A method for suppressing impulse interference based on space-time sampling covariance inversion as claimed in claim 1, wherein the algorithm in step 3) adopts sampling covariance inversion (SMI) algorithm to obtain weights, estimates covariance matrix by using received snapshot data, and obtains weight vector, that is:
wherein
Is an estimate of the covariance matrix, L is the accumulated data length, X (t)i) For sampled data vectors, H is the matrix operator, representing the conjugate transpose of the matrix.
5. The impulse interference suppression method based on space-time sampling covariance inversion according to claim 1, wherein in the algorithm in step 3), when the pulse width and the weight convergence time are coherent, the number of covariance matrix accumulation points is increased by a certain multiple, and the weight convergence time is correspondingly increased, so that a sensitive area can be moved, thereby achieving a better impulse interference suppression effect.
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| CN112737616A (en) * | 2020-12-29 | 2021-04-30 | 成都国星通信有限公司 | Beidou communication antenna pulse interference suppression method and suppression circuit |
| CN114785426A (en) * | 2022-03-30 | 2022-07-22 | 西安宇飞电子技术有限公司 | Multi-antenna anti-interference method, device, equipment and computer readable storage medium |
| CN116449398A (en) * | 2023-04-10 | 2023-07-18 | 中国矿业大学 | Self-adaptive anti-interference method for satellite navigation receiver in antenna array element mutual coupling environment |
| CN117233804A (en) * | 2023-11-13 | 2023-12-15 | 中国船舶集团有限公司第七〇七研究所 | Pulse interference detection and identification method and system based on space time domain peak-to-average ratio |
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| CN114785426A (en) * | 2022-03-30 | 2022-07-22 | 西安宇飞电子技术有限公司 | Multi-antenna anti-interference method, device, equipment and computer readable storage medium |
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| CN116449398A (en) * | 2023-04-10 | 2023-07-18 | 中国矿业大学 | Self-adaptive anti-interference method for satellite navigation receiver in antenna array element mutual coupling environment |
| CN116449398B (en) * | 2023-04-10 | 2023-11-03 | 中国矿业大学 | Self-adaptive anti-interference method for satellite navigation receiver in antenna array element mutual coupling environment |
| CN117233804A (en) * | 2023-11-13 | 2023-12-15 | 中国船舶集团有限公司第七〇七研究所 | Pulse interference detection and identification method and system based on space time domain peak-to-average ratio |
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