CN103777214B - Non-stationary suppression jamming signal inhibition method in satellite navigation system - Google Patents
Non-stationary suppression jamming signal inhibition method in satellite navigation system Download PDFInfo
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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
- G01S19/35—Constructional details or hardware or software details of the signal processing chain
- G01S19/37—Hardware or software details of the signal processing chain
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Abstract
Non-stationary suppression jamming signal inhibition method in a kind of satellite navigation system.It comprises when suppression jamming signal and satellite-signal and noise signal coexist, and utilizes M unit even linear array to form pending array signal; To space, discrete sampling is carried out to whole undesired signal, obtains array signal sparse representation model; By sparse representation model data with the steering vector of likely angle do relevant treatment, find correlative maximal value position in steering vector matrix; Least Square Method is utilized to go out sparse vector corresponding to correlative maximal value; From sparse representation model data, deduct sparse vector obtain surplus; Judge whether interference component suppresses completely, if discontented sufficient iteration; Finally using surplus vector first element as data after current snap AF panel, carry out acquiring satellite tracking and location.This method is without the need to knowing the number of interference in advance, insensitive to DOA sampling interval mismatch, and can process the interference that DOA interval is less than resolution.
Description
Technical Field
The invention belongs to the technical field of satellite navigation interference signal suppression, and particularly relates to a non-stationary suppression interference signal suppression method in a satellite navigation system.
Background
Information such as target position, time and the like can be accurately provided based on satellite navigation, and the satellite navigation plays an important role in numerous civil and military fields, such as GPS navigation and Beidou navigation. However, since the distance between the navigation satellite and the earth is about tens of thousands of kilometers, the satellite signal received by a satellite receiver near the ground is very weak, which is generally 20dB lower than the thermal noise of the receiver, and thus the satellite signal is easily interfered.
A typical approach to satellite navigation signal interference rejection relies on array antennas and array signal processing theory. The main idea of these anti-interference methods is to estimate the direction of arrival (DOA) of the interference signal by using the received data, and then form a null at the interference position by using a subspace projection method to achieve the effect of interference signal suppression as long as the DOA of the interference signal is known. With the improvement of the requirement on the anti-interference capability of the receiver, more complex methods are also proposed, and the anti-interference capability is improved by utilizing information such as interference signals, the incoming direction of satellite signals, the characteristics of the satellite signals and the like.
At present, the relatively mature anti-interference methods based on array processing all utilize the statistic of the covariance matrix of the received satellite signal data, so the covariance matrix must be accurately estimated during processing, and thus the number of interference signals and the DOA of the interference signals need to be kept unchanged within a certain time within a certain sampling time, however, if the interference signals are non-stationary suppressed interference signals, the covariance matrix is time-varying, and the result results cause that the covariance matrix cannot be accurately estimated, so all anti-interference methods based on the covariance matrix processing fail.
Disclosure of Invention
In order to solve the above problems, an object of the present invention is to provide a method for suppressing non-stationary interference signals in a satellite navigation system, which combines the sparse spatial spectrum of the interference signals.
In order to achieve the above object, the method for suppressing non-stationary suppressive interference signals in a satellite navigation system provided by the present invention comprises the following steps performed in sequence:
1) when the suppressive interference signals coexist with satellite signals and noise signals, forming array signals to be processed by using the M-element uniform linear array;
2) performing discrete sampling on the whole interference signal incoming space to obtain a sparse representation model of the array signal formed in the step 1);
3) carrying out correlation processing on the obtained data of the sparse representation model of the array signal and the guide vectors of all possible angles, and finding out the position of the maximum value of the correlation quantity in a guide vector matrix;
4) estimating a sparse vector corresponding to the maximum value of the correlation quantity by using a least square method;
5) subtracting the estimated sparse vector from the data of the constructed sparse representation model of the array signal to obtain a residual quantity;
6) judging whether the interference component is completely inhibited, and repeating the steps 3) -5) if the condition for stopping iteration is not met until the condition for stopping iteration is met;
7) and finally, taking the first element of the residual vector as data after current snapshot interference suppression, and performing satellite acquisition tracking and positioning.
The method for obtaining the sparse representation model of the array signal in the step 2) comprises the following steps: firstly, all interference signals are subjected to discrete sampling to space, and a discrete angle set psi = { -90 °, -89.9 °, -89.8 °,. and 89.9 ° } is obtained; then, when the corresponding DOA in the discrete angle set has interference, the signal value is made equal to the interference signal value, otherwise, the signal values are all 0; then constructing a guide vector matrix A = [ a (-90 degrees), a (-89.9 degrees), a (-89.8 degrees),.., a (89.9 degrees) ] corresponding to the discrete angle set psi; and finally, establishing a sparse representation model of the array signal.
The specific method for performing the relevant processing in the step 3) is as follows: and carrying out correlation processing on the data of the sparse representation model of the array signal and a steering vector matrix A corresponding to the discrete angle set psi.
The method for judging whether the interference is completely suppressed in the step 6) comprises the following steps: comparing the maximum value of the correlation quantity in the step 3) with the noise level, and when the maximum value of the correlation quantity is smaller than the noise level, indicating that the interference component is completely inhibited, otherwise, continuing iteration until the condition is met; or comparing the residual total energy obtained in the step 5) with the noise energy, and when the residual total energy is less than the noise energy, indicating that the interference component is completely suppressed, otherwise, continuing to iterate until the condition is met.
The method for suppressing the unstable suppressive interference signals in the satellite navigation system combines the sparse characteristic of the interference signal space spectrum and adopts the theory of compressed sensing to respectively suppress the interference of each snapshot, thereby avoiding the estimation of a covariance matrix. The method is similar to a greedy method in the field of compressive sensing, but is different from the existing greedy method in that the number of interferences does not need to be known in advance, the method is insensitive to DOA sampling interval mismatch, and the interference of which the DOA interval is smaller than the resolution can be processed.
Compared with the prior art, the method has the following advantages:
1) the method adopts single snapshot data to process signals, avoids estimation of covariance matrix, can effectively inhibit non-stationary interference signals, and makes the interference inhibition method based on array processing more perfect;
2) the method does not need to accurately estimate the interference direction when inhibiting the interference signal, is different from the conventional interference inhibition method, and can avoid the defect of low resolution of the conventional method even if the two interference directions are very close, thereby well achieving the purpose of inhibiting the interference;
3) the method is different from the existing greedy method, and the number of interferences does not need to be known in advance;
4) the method is insensitive to DOA sampling interval mismatch when interference is suppressed;
5) the method can be used to suppress interference with DOA spacing less than the resolution.
Drawings
FIG. 1 is a schematic diagram of the interference variation used in the simulation experiment of the present invention;
FIG. 2 is a diagram showing comparison between the results captured in simulation experiment 1;
fig. 3 is a diagram showing comparison of the captured results of simulation experiment 2.
Detailed Description
The following describes a method for suppressing non-stationary suppressive interference signals in a satellite navigation system according to the present invention in detail with reference to the accompanying drawings and specific embodiments.
In the embodiment, a GPS system is adopted, but the provided method is also suitable for other satellite navigation systems, such as a Beidou satellite navigation system.
The method for suppressing the unstable suppressive interference signals in the satellite navigation system comprises the following steps in sequence:
1) when the suppressive interference signal coexists with the satellite signal and the noise signal, forming an array signal to be processed by using the M-element uniform linear array:
considering an M-element uniform equidistant linear array, where the array element spacing is equal to half of the wavelength of the incident signal, when the suppressive interference signal coexists with the satellite signal and the noise signal, the nth snapshot data of the antenna array received signal may be expressed as:
wherein s isl(n) denotes the l-th GPS satellite signal, jq(t) denotes the qth suppressive interference signal,
represents a signal steering vector corresponding to the spatial angle theta, and e (n) represents a complex white gaussian noise vector in the received signal.
2) Discrete sampling is carried out on the coming space of the whole interference signal, and a sparse representation model of the array signal formed in the step 1) is obtained:
the number of the suppressing interference signals is limited and is smaller than the array element number, so that the space spectrum of the interference signals meets the sparse characteristic. All interfering signals are first discretely sampled into space, with 0.1 ° spacing and 0.3 ° spacing being used in this embodiment to discretely sample the entire possible space [ -90 °,90 °), with the main objective of verifying that the method is insensitive to DOA sampling interval mismatches. The following analyses were performed at 0.1 ° intervals, and the 0.3 ° intervals were similar.
Ψ { -90 °, -89.9 °, -89.8 °,. 89.9 ° } (2) wherein Ψ is a discrete set of angles.
Then, the following steps are carried out:
equation (3) means that its signal value equals the interfering signal value only if the corresponding DOA has interference, and otherwise equals 0.
And then constructing a steering vector matrix corresponding to the discrete angle set psi:
A=[a(-90°),a(-89.9°),a(-89.8°),...,a(89.9°)](4)
a comprises guide vectors corresponding to all possible angles, and the new guide vector matrix is called an ultra-complete dictionary in the compressed sensing theory, so that a sparse representation model of an array signal conforming to compressed sensing can be expressed as follows:
wherein, of which only a few elements are not equal to zero, is a sparse vector,since the power of the satellite signal is much lower than the noise power, it is possible to reduce the noise powerThe central main component is a noise vector.
3) And carrying out correlation processing on the data of the obtained sparse representation model of the array signal and the steering vectors of all possible angles, and finding the position of the maximum value of the correlation quantity in a steering vector matrix:
firstly, initialization: residual amount r0= x (n), number of iterations h =1, set0Is an empty set.
Sequentially correlating data x (n) of a sparse representation model of the array signal with column vectors in a steering vector matrix A corresponding to the discrete angle set psi, and finding out the position lambda of the maximum value of the correlation quantity in the steering vector matrixhI.e. by
4) And (3) estimating a sparse vector corresponding to the maximum value of the correlation quantity by using a least square method:
the update set is:
h=h-1U{λhthe (7) estimates the sparse vector corresponding to the maximum value of the correlation quantity by a least square method,
5) subtracting the estimated sparse vector from the data of the constructed sparse representation model of the array signal to obtain the residual:
and (4) updating the residual quantity:
6) judging whether the interference component is completely inhibited, if the condition for stopping iteration is not met, repeating the steps 3) -5) until the condition for stopping iteration is met:
the invention provides two methods for judging whether to stop iteration, which are named as a first method and a second method respectively for convenience:
the method comprises the following steps: comparing the total residual energy in the step 5) with the total noise energy, if the total residual energy is less than the total noise energy, indicating that no interference signal component exists in the residual quantity, and stopping iteration; if the total energy of the residual quantity is larger than the total energy of the noise, the residual quantity is still provided with the components of the interference signal, and the steps 3) -5) are repeated until the iteration stop condition is met.
The second method comprises the following steps: comparing the maximum value of the correlation quantity in the step 3) with the noise level, if the maximum value of the correlation quantity is smaller than the noise level, indicating that the components of the interference signal are completely inhibited, and stopping iteration; if the noise level is higher than the noise level, the interference signal component exists, and the steps 3) -5) are required to be repeated for iteration until an iteration stop condition is met.
7) And finally, taking the first element of the residual vector as data after current snapshot interference suppression, and performing satellite acquisition tracking and positioning:
and when the iteration stopping condition is met, taking the first element of the final residual vector as data after current snapshot interference suppression, and utilizing the data to capture, track and position the satellite, wherein the feasibility of the method can be verified through a capture factor.
The effect of the method for suppressing the unstable suppressive interference signal in the satellite navigation system provided by the invention can be further illustrated by the following simulation result.
Simulation conditions are as follows: the experiment adopts 10 array element uniform linear arrays, namely M = 10. The array elements are spaced at half the wavelength of the incident signal. All experiments used high fidelity GPS signals generated by GPS high fidelity data simulation software. In simulation, eight GPS satellite signals PRN1, PRN2, PRN3, PRN6, PRN14, PRN20, PRN22 and PRN25 are adopted to align the signals respectively to 65 degrees, 50 degrees, 32 degrees, 15 degrees, 5 degrees, 25 degrees, 32 degrees and 50 degrees, and the power of the GPS satellite signals and the ratio of the power of interference signals to the power of white noise, namely the signal-to-noise ratio (SNR) and the dry-to-noise ratio (INR) are respectively SNR =20dB and INR =20 dB.
In order to include all possible interference forms as much as possible, the simulation uses interference variations as shown in fig. 1, and the non-stationary suppressive interference signals include high dynamic interference signals and impulse interference signals. The interference between adjacent snapshots of a high dynamic interference signal changes by 0.1 DEG, and the attitude change or high-speed movement of the receiver can cause the incoming direction of the interference signal to change dramatically. Interference 1 and interference 2 coincide in the middle region, i.e. the DOA interval is smaller than the DOA resolution, except that interference 3, interference 4, interference 5, interference 6 are pulsed interference signals, which occur only at partial snapshots. Fig. 1 clearly shows the non-stationarity of the interference signal, and the interference change situation shown in fig. 1 is repeatedly adopted every 600 snapshots in the simulation experiment.
In order to verify the performance of the method for inhibiting the non-stationary interference signals, the performance is compared with the capture result of the minimum power method, and the minimum power method adopts 100 snapshots in a simulation experiment.
In order to verify that the method is insensitive to DOA sampling interval mismatch, simulation experiments respectively use 0.1 degrees and 0.3 degrees for dispersing the whole possible space [ -90 degrees and 90 degrees ] at intervals.
Simulation experiment 1:
the entire possible space is discretized by 0.1 ° intervals [ -90 °,90 °), fig. 2 is a comparison of the acquisition results of the present method with the minimum power method, and fig. 2(a), 2(b) compare the correlation peak value and the acquisition factor, respectively, where the acquisition factor refers to the ratio of the correlation peak value to the secondary peak value. From fig. 2, it can be seen that the method can acquire all eight satellites, and both the peak correlation value and the acquisition factor are better than the minimum power method.
Simulation experiment 2:
the whole possible space is dispersed by 0.3 degrees, namely [ -90 degrees and 90 degrees ], the method is compared with the capture result of the minimum power method in fig. 3, and the peak value of the correlation value and the capture factor are respectively compared with the simulation experiment 1, and fig. 3(a) and 3(b), wherein the capture factor refers to the ratio of the peak value of the correlation value to the secondary peak value. From fig. 3 we can also see that eight satellites can be acquired completely using this method, and that both the peak correlation value and the acquisition factor are better than the minimum power method.
According to simulation experiments 1 and 2, for non-stationary interference signals, the performance is reduced due to the fact that a covariance matrix cannot be accurately estimated by a traditional minimum power method, the method can effectively restrain the stationary interference signals, the number of the interference signals does not need to be known in advance, the method is insensitive to DOA sampling interval mismatch, and the interference signals with the DOA intervals smaller than resolution can be processed.
Claims (4)
1. A method for suppressing non-stationary suppressive interference signals in a satellite navigation system is characterized in that: which comprises the following steps carried out in sequence:
1) when the suppressive interference signals coexist with satellite signals and noise signals, forming array signals to be processed by using the M-element uniform linear array;
2) performing discrete sampling on the whole interference signal incoming space to obtain a sparse representation model of the array signal formed in the step 1);
3) carrying out correlation processing on the obtained data of the sparse representation model of the array signal and the guide vectors of all possible angles, and finding out the position of the maximum value of the correlation quantity in a guide vector matrix;
4) estimating a sparse vector corresponding to the maximum value of the correlation quantity by using a least square method;
5) subtracting the estimated sparse vector from the data of the constructed sparse representation model of the array signal to obtain a residual quantity;
6) judging whether the interference component is completely inhibited, and repeating the steps 3) -5) if the condition for stopping iteration is not met until the condition for stopping iteration is met;
7) and finally, taking the first element of the residual vector as data after current snapshot interference suppression, and performing satellite acquisition tracking and positioning.
2. The method of claim 1, wherein the suppression of non-stationary jamming signals is performed by: the method for obtaining the sparse representation model of the array signal in the step 2) comprises the following steps: firstly, all interference signals are subjected to discrete sampling to space, and a discrete angle set psi { -90 °, -89.9 °, -89.8 °,. and.89.9 ° } is obtained; then, when the corresponding DOA in the discrete angle set has interference, the signal value is made equal to the interference signal value, otherwise, the signal values are all 0; then constructing a guide vector matrix A corresponding to the discrete angle set psi ═ a (-90 °), a (-89.9 °), a (-89.8 °), a.., a (89.9 °); and finally, establishing a sparse representation model of the array signal.
3. The method of claim 1, wherein the suppression of non-stationary jamming signals is performed by: the specific method for performing the relevant processing in the step 3) is as follows: and carrying out correlation processing on the data of the sparse representation model of the array signal and a steering vector matrix A corresponding to the discrete angle set psi.
4. The method of claim 1, wherein the suppression of non-stationary jamming signals is performed by: the method for judging whether the interference is completely suppressed in the step 6) comprises the following steps: comparing the maximum value of the correlation quantity in the step 3) with the noise level, and when the maximum value of the correlation quantity is smaller than the noise level, indicating that the interference component is completely inhibited, otherwise, continuing iteration until the condition is met; or comparing the residual total energy obtained in the step 5) with the noise energy, and when the residual total energy is less than the noise energy, indicating that the interference component is completely suppressed, otherwise, continuing to iterate until the condition is met.
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| CN104345321A (en) * | 2014-11-03 | 2015-02-11 | 西安烽火电子科技有限责任公司 | Space-time adaptive anti-interference method for satellite navigation receiver |
| CN107103727B (en) * | 2017-06-12 | 2020-10-02 | 广东小天才科技有限公司 | Bluetooth alarm method and device |
| CN108037481B (en) * | 2017-12-01 | 2022-02-08 | 天津大学 | Robustness gradable sparse array frequency and DOA estimation method and device |
| CN108205127B (en) * | 2017-12-25 | 2021-11-09 | 电子科技大学 | Underwater acoustic signal processing method based on sparse representation |
| CN110320537A (en) * | 2019-07-24 | 2019-10-11 | 哈尔滨工程大学 | A kind of satellite navigation receiver blind adaptive beamforming method |
| CN111551902B (en) * | 2020-06-02 | 2022-11-01 | 电子科技大学 | Method for recovering acquired signals when FMCW radar antenna is defective based on compressed sensing technology |
| CN112946695B (en) * | 2021-03-01 | 2023-10-13 | 北京交通大学 | Satellite positioning suppression interference identification method based on singular value decomposition |
| CN113359157B (en) * | 2021-06-02 | 2023-04-28 | 西安交通大学 | Method, system, medium and equipment for suppressing continuous wave interference in Roland signal |
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| CN102393525A (en) * | 2011-10-28 | 2012-03-28 | 西安电子科技大学 | Navigation interference suppression and signal amplification method for subspace projection |
| CN102495414A (en) * | 2011-11-28 | 2012-06-13 | 哈尔滨功成科技创业投资有限公司 | Capturing technology of GPS (global positioning system) weak signal |
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| CN102393525A (en) * | 2011-10-28 | 2012-03-28 | 西安电子科技大学 | Navigation interference suppression and signal amplification method for subspace projection |
| CN102495414A (en) * | 2011-11-28 | 2012-06-13 | 哈尔滨功成科技创业投资有限公司 | Capturing technology of GPS (global positioning system) weak signal |
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