CN110850445B - Pulse interference suppression method based on space-time sampling covariance inversion - Google Patents
Pulse interference suppression method based on space-time sampling covariance inversion Download PDFInfo
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Classifications
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- 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
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- 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
- G01S19/24—Acquisition or tracking or demodulation of signals transmitted by the system
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 a space-time sampling covariance inversion anti-interference algorithm and a pulse period are related by an algorithm. The invention does not need to know the number of the pressed pulse interference and estimate the incoming wave direction, can adaptively form the null in the incoming wave direction of the interference, and achieves the purpose of inhibiting 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
The satellite navigation system (GPS, beidou, GLONASS) can provide all-weather and high-precision navigation positioning information for various users worldwide, but the 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, which is submerged in the noise of the receiver, and is extremely susceptible to various kinds of suppression interference, so that the satellite receiver cannot work because the satellite signal cannot be locked. Experiments show that a GPS civil receiver with power of 1W can not work within 85 km around. In order for a receiver to operate with high reliability in a peripherally 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, spatial filtering, space-time filtering and the like, wherein the most effective method is space-time filtering technology based on an array antenna.
The pulse type interference mainly comprises signals radiated by Bluetooth, civil aviation DME transponder, radio stations, radar and the like in the environment, and also comprises malicious interference applied by people. At present, the domestic anti-interference array antenna technology is greatly developed, but the anti-interference array antenna has own weaknesses aiming at pulse interference, and the anti-interference capability of different degrees is reduced according to different implementation algorithms. At present, the time-frequency domain anti-pulse interference is researched by domestic literature, but the method can only be effective for the pulse interference with smaller duty cycle, and the method is not specially researched systematically for the array antenna anti-pulse interference. The anti-pulse interference of the array antenna is a spatial filtering method, and interference can be distinguished from a spatial domain to act on interference with any duty ratio, so that a pulse interference suppression method based on the array antenna is necessary.
Disclosure of Invention
In order to solve the problems, the invention aims to provide a pulse interference suppression method based on space-time sampling covariance inversion, which ensures good anti-interference performance of an algorithm when the convergence time of a weight and a pulse period are related, so that a receiver can normally capture satellite signals.
The technical scheme of the invention is as follows: a pulse interference suppression method based on space-time sampling covariance inversion is characterized by adjusting a suppression strategy of pulse interference, and comprises the following operation steps:
1) AD sampling is carried out on signals received by an antenna array, and the signals are converted into multipath digital signals;
2) Calculating the period of pulse interference;
3) Judging whether the convergence time of the weight is related to the pulse period or not, if not, performing weight calculation according to an original algorithm implementation program, and completing space-time domain filtering; if the correlation is carried out, the number of accumulated points of the covariance matrix is increased by four times, the weight convergence time is increased by four times, and the problem of poor anti-interference performance when the correlation with the weight convergence time is carried out is solved by adopting a method for 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), the basic framework of the algorithm adopts a space-time two-dimensional filtering mode, and different antenna array elements form spatial filtering when seen from the same time delay node, so that spatial interference sources can be distinguished, and spatial null suppression spatial interference is formed; from each antenna array element channel, each stage of delay forms time domain FIR filtering, interference cancellation is carried out in the time domain, and the signals can be deeply analyzed in the time domain so as to inhibit interference.
The algorithm in the step 3) adopts a sampling covariance inversion (SMI) algorithm to calculate the weight, and the covariance matrix is estimated by using the received snapshot data, so as to obtain the weight vector, namely:
wherein the method comprises the steps ofIs the estimated value of covariance matrix, L is the accumulated data length, X (t i ) For sampling a data vector, H is the matrix operator, representing the conjugate transpose of the matrix.
When the pulse width and the weight convergence time are related in the algorithm in the step 3), the covariance matrix accumulated point number 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 combines 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 interference under the condition that the direction of arrival and the number of the interference are not required to be known, improves the capability of the navigation receiver for resisting various interferences, and has certain practical value. The invention is simple to realize and can be used as an independent anti-interference module to be embedded into a common receiver.
Drawings
FIG. 1 is a schematic block diagram of the basic flow of the present invention (improved strategy for space-time anti-interference algorithm);
FIG. 2 is a schematic block diagram of the hollow anti-jamming algorithm of the present invention;
fig. 3 is a block diagram of a space-time anti-interference algorithm implementation flow (to improve a specific implementation manner of the space-time anti-interference algorithm, the specific implementation manner of fig. 1 and 2:
FIG. 4 is a schematic diagram of pulse duty cycle;
FIG. 5 is a diagram of a three wideband pulse interference airspace pattern;
fig. 6 is a plot of useful signal acquisition correlation peaks after interference suppression.
Detailed Description
The pulse interference suppression method based on space-time sampling covariance inversion provided by the invention is described in detail below with reference to the accompanying drawings and specific embodiments.
As shown in fig. 1 and fig. 2, the pulse interference suppression method based on space-time sampling covariance inversion provided by the invention comprises the following steps in sequence:
1) Conversion of the received signal: AD sampling is carried out on signals received by the antenna array, and the signals are converted into multipath digital signals.
For the characteristics 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 is composed of M array elements, and each array element receives signals and then sends the signals to a processor through respective transmission channels, 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 the time delay, u i (t) is the amplitude of the received signal,is the phase of the received signal. Omega 0 Is the frequency of the received signal,/-, is>c is the speed of light and λ is the wavelength of the incident signal. Under the assumption of a narrowband far-field signal source, there are:
according to the above two formulas, the following formulas hold:
the mth array element receiving signal can be obtained as follows:
wherein M is the number of antenna elements, g mi Representing the ith signal at the mth arrayGain on element, n m (t) represents noise of the mth array element at the time t, τ mi Representing the delay of the ith signal to the mth element relative to the reference element.
The signals received by M array elements at a specific moment are arranged into a column vector, and the following can be obtained:
under ideal conditions, assuming that each array element in the array is isotropic and has no influence of factors such as channel inconsistency, mutual coupling and the like, the method can be obtained through normalization processing:
the written vector form is as follows:
X(t)＝AS(t)+N(t)
where X (t) is an mx 1-dimensional snapshot data vector of the array, S (t) is an nx1-dimensional vector of the spatial signal, N (t) is an mx 1-dimensional noise data vector of the array, a is an mx N-dimensional flow pattern matrix (also referred to as a steering vector array) of the spatial array, and:
A＝[a 1 (ω 0 ) a 2 (ω 0 ) … a P (ω 0 )]
wherein, the direction vector is:
from the above discussion, it can be seen that for a typical far-field narrowband signal, the time delay τ between the elements results in a phase difference of φ=e between the elements -jωτ Thereby forming an array flow pattern of the array space. And carrying out beam forming and space spectrum estimation by utilizing the phase difference information among the array elements, and further carrying out interference signal suppression.
2) Calculating (pulse) interference period:
calculating pulse period, judging the number of points exceeding a blanking threshold by adopting a sliding window method to judge the period of pulse interference;
3) Judging whether the convergence time of the weight is related to the pulse period. If the two types of the space-time domain filtering are not related, performing weight calculation according to an original algorithm implementation program to finish space-time domain filtering; if the correlation is carried out, the number of accumulated points of the covariance matrix is increased by four times, the convergence time of the weight is increased by four times, and the problem that the anti-interference performance is poor when the correlation with the convergence time of the weight is carried out is solved by adopting a method for moving the sensitive area away.
The algorithm basic framework adopts a space-time two-dimensional filtering method, as shown in fig. 2, different antenna array elements form adaptive filtering of a space domain, namely space domain filtering, can distinguish space interference sources and form space domain null notch restraining space domain interference when seen from the same time delay node; from each antenna array element channel, each stage of delay forms time domain FIR filtering, interference cancellation is carried out in the time domain according to the self-adaptive filtering principle, and the 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. Compared with spatial filtering, the method has higher freedom degree and can better cope with peripheral electromagnetic interference.
In the algorithm in the step 3), a sampling covariance inversion mode (SMI algorithm) is adopted for solving the weight, and the SMI algorithm estimates a covariance matrix by using the received snapshot data and then obtains 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 then the snapshot vector received at the moment k is X= [ X ] 11 x 12 …x 1P x 21 x 22 …x 2P ……x M1 x M2 …x MP ] T . Collecting N space-time snapshots, and taking a space-time covariance matrix as
Calculating an adaptive weight: after obtaining the covariance matrix, the adaptive weights can be calculated according to the following formula.
Wherein,a s ＝[1 1 1 1]，a t ＝[1 0 0 0]。
and carrying out complex multiplication on the self-adaptive weight and the delayed signal, and weighting and synthesizing one path of signal to complete self-adaptive space-time filtering of the signal. The received total signal X and the space-time weight vector W are respectively changed into MP multiplied by 1 dimension column vectors after passing through a matrix vectorization operator:
X＝[x 11 x 12 …x 1P x 21 x 22 …x 2P ……x M1 x M2 …x MP ] T
W＝[w 11 w 12 …w 1P w 21 w 22 …w 2P ……w M1 w M2 …w MP ] T
the output of the space-time process is:
y＝W H X
the output signal to interference plus noise ratio is:
wherein R is η ＝E(ηη H ) For interference plus noise covariance matrix, R s ＝E(ss H ) For navigating signal covariance matrix
When the pulse width and the weight convergence time are related in the algorithm in the step 3), the covariance matrix accumulated point number 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 that the SMI algorithm suppresses pulse interference. The core idea is as follows: when the pulse period is in the weight convergence time coherent region, the weight convergence time is adjusted to remove the sensitive region, and the post-adjustment weight convergence time coherent region is not overlapped with the original weight convergence time coherent region by a method of lengthening the accumulation time of the covariance matrix. For example, when the accumulated covariance point number is 1024 points, the weight convergence time is 25us, the sensitive area position is 30 us-80 us, and the accumulated covariance point number is 4096 points, the weight convergence time is 200us, and the sensitive area position is 160 us-240 us. A specific description is shown in fig. 4.
Fig. 5 is a diagram of the spatial domain of the proposed algorithm three wideband pulse interference. Simulation conditions: the interference form adopts band-limited Gaussian white noise, the bandwidth is 20MHz, the signal is Beidou signal, the signal-to-noise ratio is-25 dB, and the simulation is carried out according to three broadband interferences. Under the condition of three broadband interference, the interference-to-noise ratio is set to be 90dB (the interference-to-signal ratio is 115 dB), the pitch angle of the interference 1 is 50 degrees, the azimuth angle is 60 degrees, the pitch angle of the interference 2 is 50 degrees, the azimuth angle is 180 degrees, the pitch angle of the 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 form nulls of not less than 100dB, and the three pulse interference is effectively suppressed.
Fig. 6 is a plot of useful signal acquisition correlation peaks after interference rejection. The simulation conditions are the same as in fig. 5, and the interference is effectively suppressed, so that the useful navigation signal can be normally captured.
Through actual hardware platform test, the improved SMI algorithm can effectively inhibit various pulse interferences of pulse period change, and ensure the normal operation of the receiver.
Claims (4)
1. A pulse interference suppression method based on space-time sampling covariance inversion is characterized by adjusting a suppression strategy of pulse interference, and comprises the following operation steps:
1) AD sampling is carried out on signals received by an antenna array, and the signals are converted into multipath digital signals;
2) Calculating the period of pulse interference;
3) Judging whether the adaptive weight convergence time is related to the pulse period or not, if not, performing weight calculation according to an original algorithm implementation program, and completing space-time domain filtering; if the correlation is adopted, the accumulated point number of the covariance matrix is increased by four times, the convergence time of the adaptive weight is increased by four times, and the problem of poor anti-interference performance when the correlation with the convergence time of the adaptive weight is adopted;
in the step 3), the basic framework of the original algorithm adopts a space-time two-dimensional filtering mode, and different antenna array elements form space domain filtering when seen from the same time delay node, so that space interference sources can be distinguished, and space domain null notch suppression space domain interference is formed; from each antenna array element channel, each stage of delay forms time domain FIR filtering, interference cancellation is carried out in the time domain, and the signal is deeply analyzed in the time domain so as to inhibit interference;
the algorithm in the step 3) adopts an SMI algorithm for obtaining the weight, wherein the SMI algorithm is to estimate a covariance matrix by using the received snapshot data, and then obtains a weight vector, and the detail steps are as follows:
estimation of covariance matrix: m array elements and P taps are adopted in the anti-interference algorithm, and then the snapshot vector received at the moment k is X= [ X11X12 … X1Px21X22 … X2P … … xM1xM2 … xMP ] T; collecting N space-time snapshots, and then the space-time covariance matrix is:
calculating an adaptive weight: after obtaining the covariance matrix, calculating the self-adaptive weight according to the following formula:
wherein,as＝[1 1 1 1]，at＝[1000]。
2. the method of claim 1, wherein the number of points exceeding a blanking threshold is determined by using a sliding window method when calculating the pulse interference period in step 2).
3. The method for impulse interference suppression based on space-time sampling covariance inversion according to claim 1, wherein the algorithm in step 3) adopts sampling covariance inversion (SMI) algorithm to calculate weights, and the received snapshot data is used to estimate covariance matrix, and then weight vectors are obtained, namely:
where L is the accumulated data length, X (ti) is the sampled data vector, and H is the matrix operator, representing the conjugate transpose of the matrix.
4. The method for impulse interference suppression based on space-time sampling covariance inversion according to claim 1, wherein the algorithm in step 3) increases the covariance matrix cumulative point number by a certain multiple and the adaptive weight convergence time by a corresponding increase when the pulse width and the adaptive weight convergence time are related, so that the sensitive area can be moved, thereby achieving the impulse interference suppression effect.
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| CN111628790B (en) * | 2020-05-28 | 2021-06-29 | 成都天奥信息科技有限公司 | High-precision anti-interference method and device based on interference bandwidth detection |
| CN112737616B (en) * | 2020-12-29 | 2022-06-21 | 成都国星通信有限公司 | Beidou communication antenna pulse interference suppression method and suppression circuit |
| CN114785426B (en) * | 2022-03-30 | 2023-11-03 | 西安宇飞电子技术有限公司 | Multi-antenna anti-interference method, device, equipment and computer readable storage medium |
| 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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