Low-interference-to-noise-ratio interference detection method and positioning method based on multi-beam double-satellite system

Abstract

The invention discloses a low-interference-to-noise-ratio interference detection method and positioning method based on a multi-beam double-satellite system, and the method comprises the steps: determining an interference frequency according to the interference of a primary satellite, and building an interference model of the interference of the primary satellite and the interference of a secondary satellite; performing matched filtering on the interference forwarded by the two multi-beam satellites to the ground receiving station, and improving the interference-to-noise ratio between the interference; performing wavelet decomposition on the interference after matched filtering to obtain wavelet coefficients of different scales and frequencies; and determining a threshold value, carrying out threshold value processing on the wavelet coefficient, removing a noise coefficient, and reserving an interference coefficient. And performing wavelet reconstruction by using the reserved interference coefficient to obtain denoised interference. According to the method, the double-satellite positioning limitation condition that double satellites need to cover the interference source together is broken through, the interference source can be positioned in a wide area, and an effective tool is provided for interference source positioning and troubleshooting of a multi-beam satellite communication system.

Description

Technical Field

[0001] The invention belongs to the field of satellite communications, and in particular relates to a low interference-to-noise ratio interference detection method and a positioning method based on a multi-beam dual-satellite system. Background Art

[0002] High Earth Orbit (GEO) communication satellites use multi-beam coverage to improve coverage gain and communication capacity. For example, the fourth-generation Inmarsat satellite uses 19 wide spot beams and 228 narrow spot beams. The onboard multi-beam antenna technology enables satellites to cover a larger area by emitting beams in multiple directions at the same time, while having higher gain and better directivity. However, multi-beam satellites face greater interference threats due to their high beam gain.

[0003] Therefore, it is necessary to find the location of the interference source quickly and accurately. In this regard, the Chinese patent with publication number CN 110045327 A discloses a single-satellite interference source positioning method based on multiple co-frequency multiplexing beams, which describes the positioning method. However, due to factors such as unknown or changing beam characteristics, the positioning accuracy is poor. At present, the dual-satellite time-frequency difference joint positioning method is more commonly used to locate the interference source. It measures the arrival time difference and arrival frequency difference information of the dual satellites to the same interference source to achieve accurate positioning of the interference signal. This method can achieve high-precision positioning under the condition that the number of required satellites is small.

[0004] However, when this method is applied to the interference positioning of multi-beam satellites, there are important technical difficulties, such as TDOA / FDOA joint dual-satellite positioning, which requires the interference source to be located within the dual-satellite area, but the two multi-beam satellites usually cover different areas and have no common coverage area.

[0005] In addition, the same-frequency multi-beams of different satellites are highly isolated from each other. When the interference located in the main satellite spot beam reaches the same-frequency beam of another auxiliary satellite, it is greatly attenuated due to beam isolation, resulting in a negative interference-to-noise ratio when the auxiliary satellite receives the interference. The current mainstream estimation methods for dual-satellite time-frequency difference parameters, including the generalized correlation method, the mutual fuzzy function method, the fourth-order cumulant method, etc., can only have more accurate parameter estimates under high interference-to-noise ratio (at least 5dB). The generalized correlation method and the mutual fuzzy function method will have large errors at low interference-to-noise ratios. Although the fourth-order cumulant method has slightly better noise resistance and can maintain a good time-frequency difference estimation at -5dB, if the interference-to-noise ratio continues to decrease, there will also be large errors. When the interference-to-noise ratio drops to -30dB, the above methods cannot effectively estimate the time-frequency difference parameters, resulting in the inability of multi-beam dual-satellite to use the dual-satellite time-frequency difference joint positioning method to locate the interference source. Summary of the invention

[0006] The present invention aims to solve one of the technical problems existing in the related art at least to a certain extent.

[0007] One object of the present invention is to provide a detection method for low interference-to-noise ratio interference based on multi-beam binary satellites. By taking advantage of the high interference-to-noise ratio of the primary satellite, the interference frequency and bandwidth are determined according to the primary satellite interference, and the interference received by the auxiliary satellite and submerged below the noise spectrum is detected based on this.

[0008] Another object of the present invention is to provide a low interference-to-noise ratio interference positioning method based on a multi-beam dual-satellite system, which breaks through the dual-satellite positioning restriction that the dual-satellite must jointly cover the interference source, can locate the interference source in a wide area, and provide an effective tool for locating and troubleshooting interference sources in multi-beam satellite communication systems.

[0009] In order to achieve the above-mentioned object, the present invention provides a low interference-to-noise ratio interference detection method based on a multi-beam dual-satellite system, wherein the multi-beam dual-satellite system includes two multi-beam satellites, an interference source and a ground receiving station; of the two multi-beam satellites, one is a primary satellite and the other is an auxiliary satellite, the interference source is located within the range of one beam of the primary satellite and within the sidelobe suppression range of the auxiliary satellite beam, and the interference is forwarded to the ground receiving station via the two multi-beam satellites; The interference detection method comprises: S100, determining an interference frequency according to the main satellite interference, and establishing an interference model of the main satellite interference and the auxiliary satellite interference accordingly; S200, matching filter the interference forwarded by two multi-beam satellites to the ground receiving station to improve the interference-to-noise ratio; S300, performing wavelet decomposition on the interference after matched filtering to obtain wavelet coefficients of different scales and frequencies; then determining a threshold, performing threshold processing on the wavelet coefficients, removing noise coefficients, and retaining interference coefficients.

[0010] S400, performing wavelet reconstruction using the reserved interference coefficient to obtain denoised interference; A further preferred technical solution of the present invention is that in step S100, the interference frequency is determined according to the primary satellite interference, and an interference model of the primary satellite interference and the auxiliary satellite interference is established accordingly. The specific method is: S110, the ground receiving station selects two multi-beam satellites to receive interference sent by the interference source and forwarded by the two multi-beam satellites; S120, determining a primary satellite, and determining an interference frequency according to the interference forwarded by the primary satellite; S130, perform fast Fourier transform on the forwarded interference, perform frequency change according to the determined interference frequency to obtain the original unshifted interference, and establish an interference model, which is expressed as:

[0011] in, and are the interference models of the interference source forwarded to the ground receiving station through two multi-beam satellites, s(t) is the noise-free interference signal emitted by the interference source, t is the time variable, and represents the signal Change over time; and are the arrival time of the interference source interference forwarded to the ground receiving station by two multi-beam satellites, is a natural constant, j is an imaginary unit; and are the frequencies at which the interference source reaches the ground receiving station after being forwarded by two multi-beam satellites; and They respectively represent the Gaussian white noise interference of the interference source forwarded to the ground receiving station through two multi-beam satellites, and the interference and noise are uncorrelated; is the complex gain of the ith beam (including amplitude and phase information), which is calculated as follows:

[0012] and are the excitation amplitude and phase of the unit antenna, is the directivity function of the unit antenna, are multi-beam satellite beams with different numbers, n is the nth unit in the antenna array, is the phase change within the unit length, and Represent the antenna elevation angle and azimuth angle respectively; S140, normalize the interference model, and express the interference forwarded by two multi-beam satellites to the ground receiving station as:

[0013] in, is the relative amplitude of the interference received by the ground receiving station from two multi-beam satellites. ; It indicates the time difference when the ground receiving station receives the interference forwarded by two multi-beam satellites. ; It indicates the frequency difference of interference received by the ground receiving station from two multi-beam satellites. .

[0014] Preferably, in step S200, matched filtering is performed on the interference forwarded by the two multi-beam satellites to the ground receiving station. The specific method is: S210, establish a matched filter, expressed as:

[0015] in, Indicates known emission interference, is the time domain impulse response, The power spectral density is Zero-mean stationary additive Gaussian white noise; represents the power spectral density, is the power spectrum density value of additive Gaussian white noise in the frequency range; S220, the interference model , Substituting into the matched filter, it is expressed as:

[0016] in, , Signal and The output signal after the impulse response is is the time offset, is the impulse response of the system.

[0017] Preferably, the specific method of step S300 is: S310, decomposing the interference to be processed into sub-band interferences of different scales and frequencies through wavelet transform, expressed as:

[0018] in, Noise interference , Wavelet coefficients of each layer after wavelet transformation; is the approximate coefficient, which is the wavelet transform coefficient of the effective interference part. is the detail coefficient, is the wavelet transform coefficient containing the interference noise part; is the scale parameter, representing the number of wavelet decomposition layers, It is the position offset of the wavelet function on the time axis, which is used to locate the local features of the signal; S320, determining a threshold value, the threshold value calculation formula is:

[0019] in, is the original signal length, For the The number of wavelet coefficients of the layer; S330 , threshold processing is performed on the interference detail coefficients, and detail coefficients less than a certain threshold are set to zero to remove the influence of noise.

[0020] Preferably, in step S400, the approximate coefficients and detail coefficients after threshold processing are reconstructed by inverse wavelet transform to obtain denoised interference.

[0021] Another aspect of the present invention provides a low interference-to-noise ratio positioning method based on a multi-beam dual-satellite system, comprising: S500, substituting the reconstructed interference obtained by the above interference detection method into the mutual ambiguity function to estimate the time-frequency difference parameters; S600: Using the estimated value of the time-frequency difference parameter and selecting the positions and velocities of the two corresponding satellites, the interference source is located through a positioning settlement equation group.

[0022] Furthermore, the mutual fuzzy function in step S500 is expressed as:

[0023] in, and Forward interference received from primary and secondary satellites, Expressed as complex conjugate, is the Doppler frequency shift variable, is the total detection time.

[0024] Furthermore, the method for estimating the time-frequency difference parameters in step S500 is: for Take the absolute value , the absolute value of the real delay Doppler shift reaches its peak value, according to The peak position of and Doppler shift The estimated value is:

[0025] In the formula, express The delay and Doppler shift estimates corresponding to the maximum value are obtained.

[0026] Furthermore, the positioning settlement equation group in step S600 is expressed as:

[0027] in, represents the location of the unknown interference source, c is the speed of electromagnetic wave propagation in vacuum, It is the arrival time difference of the interference source interference reaching the two satellites measured by the two satellites, which includes the delay error caused by various errors; is the arrival frequency difference of the interference source reaching the two satellites measured by the two satellites, is the frequency of interference from the interference source, is the Earth's semi-major axis, is the Earth's semi-minor axis, is the satellite position, is the distance from the two satellites to the interference source, is the speed of the satellite.

[0028] Another aspect of the present invention provides a non-transitory computer-readable storage medium having computer instructions stored thereon, wherein the computer instructions enable a computer to execute the above-mentioned low interference-to-noise ratio interference positioning method based on a multi-beam dual-satellite system.

[0029] Yet another aspect of the present invention provides an electronic device, comprising: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus, and the processor calls the logic instructions in the memory to execute the above-mentioned low interference-to-noise ratio interference positioning method based on the multi-beam dual-star system.

[0030] On the other hand, the present invention provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer executes the above-mentioned low interference-to-noise ratio interference positioning method based on a multi-beam dual-star system.

[0031] Beneficial effects: The present invention aims at the problem that in a multi-beam satellite system, the interference source of the main satellite is outside the coverage area of ​​the auxiliary satellite, and the interference entering the auxiliary satellite from the side lobe outside the coverage area is lower than the noise power and is difficult to detect. The present invention adopts matched filtering to improve the interference-to-noise ratio between the interferences, and obtains the wavelet coefficients of each level and the approximate coefficients of the lowest level through the wavelet coefficient decomposition method. Then, the threshold is determined, the non-significant coefficients are discarded, and the modified detail coefficient set is output to reconstruct the interference and restore the interference.

[0032] The present invention restores the interference of the auxiliary satellite with extremely low interference-to-noise ratio to the greatest extent, and calculates the mutual fuzzy function with the interference of the main satellite to obtain the time-frequency difference positioning parameters, effectively improving the estimation accuracy of the positioning parameters. Finally, the accurate positioning of the interference is obtained through the dual-satellite time-frequency difference positioning algorithm. The present invention breaks through the dual-satellite positioning restriction that the dual satellites need to jointly cover the interference source, and can realize the positioning of the interference source in a wide area, providing an effective tool for the positioning and troubleshooting of interference sources in multi-beam satellite communication systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a model diagram based on the multi-beam binary star system in the present invention.

[0034] Figure 2 It is a flow chart of a low interference-to-noise ratio interference detection method and a positioning method based on a multi-beam dual-satellite system of the present invention; Figure 3is a diagram of the mutual fuzzy function estimation result when the interference is not processed in the simulation experiment of Example 1; Figure 4 is a diagram of the mutual fuzzy function estimation result after processing interference in a simulation experiment of Example 1; Figure 5 is a comparison diagram of the time difference parameters of various algorithms under different interference-to-noise ratios in the simulation experiment of Example 1; Figure 6 is a comparison diagram of frequency difference parameters of various algorithms under different interference-to-noise ratios in the simulation experiment of Example 1; Figure 7 is a GDOP simulation diagram of Example 1; Figure 7 (a) is a simulation diagram of GDOP simulation using the time-frequency difference parameters obtained without the above method. Figure 7 (b) is a simulation diagram of GDOP simulation using the time-frequency difference parameters obtained after processing using the matched filter-hard threshold method in the method of Example 1. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments, and they should not be understood as limitations on the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. In the description of the present invention, it should be understood that the terms used are only for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0036] Combine the following Figure 1-Figure 7 The invention describes a low interference-to-noise ratio interference detection method and a positioning method based on a multi-beam dual-satellite system.

[0037] Embodiment 1: This embodiment provides a low interference-to-noise ratio interference detection method and a positioning method based on a multi-beam dual-satellite system.

[0038] The multi-beam dual-satellite system Figure 1 As shown, it includes two multi-beam satellites, interference sources and ground receiving stations; one of the two multi-beam satellites is a main satellite and the other is an auxiliary satellite. The interference source is located within the range of one of the beams of the main satellite and within the sidelobe suppression range of the auxiliary satellite beam. The interference is forwarded to the interference detection and positioning server through the two multi-beam satellites. In this embodiment, the ground receiving station at the gateway station is taken as an example, and a feed interference reception and interference positioning server are set. The interference is forwarded to the gateway station through the multi-beam satellite for subsequent interference processing and satellite positioning processes.

[0039] Specific steps, such as Figure 2 As shown, including: S100, determining an interference frequency according to the main satellite interference, and establishing an interference model of the main satellite interference and the auxiliary satellite interference accordingly.

[0040] S110, the interference source is transmitted to the multi-beam satellite, and the interference model is expressed as:

[0041] S120, the ground receiving station selects two multi-beam satellites, determines the primary satellite, and determines the interference frequency according to the interference forwarded by the primary satellite; S130, perform fast Fourier transform on the forwarded interference, perform frequency change according to the determined interference frequency to obtain the original unshifted interference, and establish an interference model, which is expressed as:

[0042] in, and are the interference models of the interference source forwarded to the ground receiving station through two multi-beam satellites, s(t) is the noise-free interference signal emitted by the interference source, t is the time variable, and represents the signal Change over time; and are the arrival time of the interference source interference forwarded to the ground receiving station by two multi-beam satellites, is a natural constant and j is an imaginary unit. and are the frequencies at which the interference source reaches the ground receiving station after being forwarded by two multi-beam satellites; and They respectively represent the Gaussian white noise interference of the interference source forwarded to the ground receiving station through two multi-beam satellites, and the interference and noise are uncorrelated; is the complex gain of the ith beam (including amplitude and phase information), which is calculated as follows:

[0043] and are the excitation amplitude and phase of the unit antenna, is the directivity function of the unit antenna, are multi-beam satellite beams with different numbers, n is the nth unit in the antenna array, is the phase change within the unit length, and Represent the antenna elevation angle and azimuth angle respectively.

[0044] S140, normalize the interference model, and express the interference forwarded by two multi-beam satellites to the ground receiving station as:

[0045] in, is the relative amplitude of the interference received by the ground receiving station from two multi-beam satellites. ; It indicates the time difference when the ground receiving station receives the interference forwarded by two multi-beam satellites. ; It indicates the frequency difference of interference received by the ground receiving station from two multi-beam satellites. .

[0046] S200, match filter the interference forwarded by two multi-beam satellites to the ground receiving station to improve the interference-to-noise ratio.

[0047] Matched filter (MF) is an "optimal" linear filter based on the maximum output interference-to-noise ratio criterion. Its transfer function when the output interference-to-noise ratio reaches the maximum is: , the time domain impulse response is The filter input is the transmitted interference Interference with noise of superposition.

[0048] S210, establish a matched filter, expressed as:

[0049] in, Indicates known emission interference, is the time domain impulse response, The power spectral density is Zero-mean stationary additive Gaussian white noise; represents the power spectral density, is the power spectral density value of additive Gaussian white noise in the frequency range.

[0050] S220, according to the above interference model, the interference , Substituting into the matched filter we get:

[0051] S230, further changing the above formula to obtain:

[0052] S240, the interference model , Substituting into the matched filter, it is expressed as:

[0053] in, , Signal and The output signal after the impulse response is is the time offset, is the impulse response of the system.

[0054] S300, perform wavelet decomposition on the interference after matched filtering to obtain wavelet coefficients of different scales and frequencies; then determine the threshold, perform threshold processing on the wavelet coefficients, remove the noise coefficient, and retain the interference coefficient. Use wavelet denoising to eliminate noise interference as much as possible The impact of retaining effective interference .

[0055] S310, decomposing the interference to be processed into sub-band interferences of different scales and frequencies through wavelet transform, expressed as:

[0056] in, Noise interference , Wavelet coefficients of each layer after wavelet transformation; is the approximate coefficient, which is the wavelet transform coefficient of the effective interference part. is the detail coefficient, is the wavelet transform coefficient containing the interference noise part; is the scale parameter, representing the number of wavelet decomposition layers, It is the position offset of the wavelet function on the time axis, which is used to locate the local features of the signal; S320, determining a threshold value, the threshold value calculation formula is:

[0057] in, is the original signal length, For the The number of wavelet coefficients of the layer; S330, threshold processing is performed on the interference detail coefficients, and detail coefficients less than a certain threshold are set to zero to remove the influence of noise. There are different processing methods for detail coefficients greater than the threshold, which are divided into hard threshold processing and soft threshold processing, which are as follows:

[0058]

[0059] Where sgn is the sign function.

[0060] S400, reconstructing the approximate coefficients and detail coefficients after the threshold processing through inverse wavelet transform to obtain the interference after denoising.

[0061] S500, substituting the denoised interference into the mutual fuzzy function to estimate the time-frequency difference parameters; The mutual fuzzy function is expressed as:

[0062] in, and Forward interference received from primary and secondary satellites, Expressed as complex conjugate, is the Doppler frequency shift variable, is the total detection time.

[0063] for Take the absolute value , the absolute value of the real delay Doppler shift reaches its peak value, according to The peak position of and Doppler shift The estimated value is:

[0064] In the formula, express The delay and Doppler shift estimates corresponding to the maximum value are obtained.

[0065] In order to test the improvement of the time-frequency difference estimation scheme of the algorithm proposed in this paper on the time-frequency difference performance of the burst radiation source signal, the estimated value of the time-frequency difference The actual time-frequency difference information The error can be measured using the root mean square error (RMSE), which is defined as follows:

[0066] in is the Monte Carlo number of the simulation experiment, here we take .

[0067] S600: Using the estimated value of the time-frequency difference parameter and selecting the positions and velocities of the two corresponding satellites, the interference source is located through a positioning settlement equation group.

[0068] The positioning settlement equation group is expressed as:

[0069] in, represents the location of the unknown interference source, c is the speed of electromagnetic wave propagation in vacuum, It is the arrival time difference of the interference source interference reaching the two satellites measured by the two satellites, which includes the delay error caused by various errors; is the arrival frequency difference of the interference source reaching the two satellites measured by the two satellites, is the frequency of interference from the interference source, is the Earth's semi-major axis, is the Earth's semi-minor axis, is the satellite position, is the distance from the two satellites to the interference source, is the speed of the satellite.

[0070] The method of this embodiment is simulated and verified as follows: Through the Matlab program, the interference that meets the above multi-beam binary satellite system is generated. The sampling rate is 10MHz, the time difference is set to 4.6us, the frequency difference is set to 10.2Hz, the interference-to-noise ratio of the primary satellite is 5dB, and the signal-to-noise ratio of the auxiliary satellite is -30dB.

[0071] Figure 3 is the result diagram of the mutual fuzzy function estimation without the above method. Figure 4 This is a diagram of the mutual fuzzy function estimation result after being processed by the matched filter-hard threshold method in the above method. After the improvement of the method of the present invention, the estimation of the interference time-frequency difference parameters is greatly improved, and the interference submerged in the noise can be processed to extract the time-frequency difference parameters. Therefore, this method has good practical value.

[0072] Figure 5 and Figure 6 This is a comparison of the RMS errors of the time difference and frequency difference estimated by the mutual fuzzy function method after the interference interference noise ratio of the primary satellite is set to 5dB and the signal-to-noise ratio of the auxiliary satellite interference is set to -30dB to 0dB, using the hard threshold function, soft threshold function, matched filter-hard threshold and matched filter-soft threshold to process the interference. It can be seen that the RMS errors of the estimated time difference and frequency difference after matched filter processing are significantly lower than those without processing.

[0073] Figure 7 This is a GDOP simulation diagram of two algorithms after the time-frequency difference parameters are estimated and the satellite positioning position and speed are substituted. Figure 7 (a) is a simulation diagram of GDOP simulation using the time-frequency difference parameters obtained without the above method. Figure 7 (b) is a simulation diagram of GDOP simulation using the time-frequency difference parameters obtained after processing with the matched filter-hard threshold method in the above method. The satellite position and speed are: S1=[101.43, 0.0, 35786000], S2=[125.0, 0.0, 35786000], V1=[0.0, -3070.0, 0.0], V2=[0.0, -3070.0, 0.0].

[0074] Embodiment 2: This embodiment provides a non-transitory computer-readable storage medium, on which computer instructions are stored, the computer instructions causing the computer to execute a low interference-to-noise ratio positioning method based on a multi-beam dual-satellite system, the method comprising the following steps: S100, determining an interference frequency according to the main satellite interference, and establishing an interference model of the main satellite interference and the auxiliary satellite interference accordingly; S200, matching filter the interference forwarded by two multi-beam satellites to the ground receiving station to improve the interference-to-noise ratio; S300, performing wavelet decomposition on the interference after matched filtering to obtain wavelet coefficients of different scales and frequencies; then determining a threshold, performing threshold processing on the wavelet coefficients, removing noise coefficients, and retaining interference coefficients.

[0075] S400, performing wavelet reconstruction using the retained interference coefficient to obtain denoised interference.

[0076] S500, substituting the obtained reconstructed interference into the mutual ambiguity function to estimate the time-frequency difference parameters; S600: Using the estimated value of the time-frequency difference parameter and selecting the positions and velocities of the two corresponding satellites, the interference source is located through a positioning settlement equation group.

[0077] Embodiment 3: This embodiment provides an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus. The processor may call the logic instructions in the memory to execute a low interference-to-noise ratio positioning method based on a multi-beam dual-satellite system, the method comprising the following steps: S100, determining an interference frequency according to the main satellite interference, and establishing an interference model of the main satellite interference and the auxiliary satellite interference accordingly; S200, matching filter the interference forwarded by two multi-beam satellites to the ground receiving station to improve the interference-to-noise ratio; S300, performing wavelet decomposition on the interference after matched filtering to obtain wavelet coefficients of different scales and frequencies; then determining a threshold, performing threshold processing on the wavelet coefficients, removing noise coefficients, and retaining interference coefficients.

[0078] S400, performing wavelet reconstruction using the retained interference coefficient to obtain denoised interference.

[0079] S500, substituting the obtained reconstructed interference into the mutual ambiguity function to estimate the time-frequency difference parameters; S600: Using the estimated value of the time-frequency difference parameter and selecting the positions and velocities of the two corresponding satellites, the interference source is located through a positioning settlement equation group.

[0080] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program code.

[0081] Embodiment 4: This embodiment provides a computer program product, which includes a computer program. The computer program can be stored in a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute a low interference-to-noise ratio positioning method based on a multi-beam dual-satellite system. The method includes the following steps: S100, determining an interference frequency according to the main satellite interference, and establishing an interference model of the main satellite interference and the auxiliary satellite interference accordingly; S200, matching filter the interference forwarded by two multi-beam satellites to the ground receiving station to improve the interference-to-noise ratio; S300, performing wavelet decomposition on the interference after matched filtering to obtain wavelet coefficients of different scales and frequencies; then determining a threshold, performing threshold processing on the wavelet coefficients, removing noise coefficients, and retaining interference coefficients.

[0082] S400, performing wavelet reconstruction using the retained interference coefficient to obtain denoised interference.

[0083] S500, substituting the obtained reconstructed interference into the mutual ambiguity function to estimate the time-frequency difference parameters; S600: Using the estimated value of the time-frequency difference parameter and selecting the positions and velocities of the two corresponding satellites, the interference source is located through a positioning settlement equation group.

[0084] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0085] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A low interference-to-noise ratio interference detection method based on a multi-beam dual-satellite system, the multi-beam dual-satellite system comprising two multi-beam satellites, an interference source and a ground receiving station; one of the two multi-beam satellites is a primary satellite and the other is an auxiliary satellite, the interference source is located within the range of one beam of the primary satellite and within the sidelobe suppression range of the auxiliary satellite beam, and the interference is forwarded to the ground receiving station via the two multi-beam satellites; characterized in that: The interference detection method comprises: S100, determining an interference frequency according to the main satellite interference, and establishing an interference model of the main satellite interference and the auxiliary satellite interference accordingly; S200, matching filter the interference forwarded by two multi-beam satellites to the ground receiving station to improve the interference-to-noise ratio; S300, performing wavelet decomposition on the interference after matched filtering to obtain wavelet coefficients of different scales and frequencies; then determining a threshold, performing threshold processing on the wavelet coefficients, removing noise coefficients, and retaining interference coefficients; S400, performing wavelet reconstruction using the retained interference coefficient to obtain denoised interference.

2. The low interference-to-noise ratio interference detection method based on a multi-beam binary satellite system according to claim 1, characterized in that: In step S100, the interference frequency is determined according to the primary satellite interference, and an interference model of the primary satellite interference and the auxiliary satellite interference is established accordingly. The specific method is as follows: S110, the ground receiving station selects two multi-beam satellites to receive interference sent by the interference source and forwarded by the two multi-beam satellites; S120, determining a primary satellite, and determining an interference frequency according to the interference forwarded by the primary satellite; S130, perform fast Fourier transform on the forwarded interference, perform frequency change according to the determined interference frequency to obtain the original unshifted interference, and establish an interference model, which is expressed as: ； in, and are the interference models of the interference source forwarded to the ground receiving station through two multi-beam satellites, s(t) is the noise-free interference signal emitted by the interference source, and t is the time variable; and are the arrival time of the interference source interference forwarded to the ground receiving station by two multi-beam satellites, is a natural constant, j is an imaginary unit; and are the frequencies at which the interference source reaches the ground receiving station after being forwarded by two multi-beam satellites; and They respectively represent the Gaussian white noise interference of the interference source forwarded to the ground receiving station through two multi-beam satellites, and the interference and noise are uncorrelated; is the complex gain of the i-th beam containing amplitude and phase information, and its calculation formula is: ； and are the excitation amplitude and phase of the unit antenna, is the radiation pattern function of the unit antenna, are multi-beam satellite beams with different numbers. The first units, is the phase change within the unit length, and Represent the antenna elevation angle and azimuth angle respectively; S140, normalize the interference model, and express the interference forwarded by two multi-beam satellites to the ground receiving station as: ； in, is the relative amplitude of the interference received by the ground receiving station from two multi-beam satellites. ; It indicates the time difference when the ground receiving station receives the interference forwarded by two multi-beam satellites. ; It indicates the frequency difference of interference received by the ground receiving station from two multi-beam satellites. .

3. The low interference-to-noise ratio interference detection method based on a multi-beam binary satellite system according to claim 2, characterized in that: In step S200, the interference forwarded by the two multi-beam satellites to the ground receiving station is subjected to matched filtering. The specific method is as follows: S210, establish a matched filter, expressed as: ； in, Indicates known emission interference, is the time domain impulse response, The power spectral density is Zero-mean stationary additive Gaussian white noise; represents the power spectral density, is the power spectrum density value of additive Gaussian white noise in the frequency range; S220, the interference model , Substituting into the matched filter, it is expressed as: ； in, and Signal and The output signal after the impulse response is is the time offset, is the impulse response of the system.

4. The low interference-to-noise ratio interference detection method based on a multi-beam dual-satellite system according to claim 3 is characterized in that: The specific method of step S300 is: S310, decomposing the interference to be processed into sub-band interferences of different scales and frequencies through wavelet transform, expressed as: ； in, Noise interference , Wavelet coefficients of each layer after wavelet transformation; is the approximate coefficient, which is the wavelet transform coefficient of the effective interference part. is the detail coefficient, is the wavelet transform coefficient containing the interference noise part; is the scale parameter, representing the number of wavelet decomposition layers, It is the position offset of the wavelet function on the time axis, which is used to locate the local features of the signal; S320, determining a threshold value, the threshold value calculation formula is: ； in, is the original signal length, For the The number of wavelet coefficients of the layer; S330 , threshold processing is performed on the interference detail coefficients, and detail coefficients less than a certain threshold are set to zero to remove the influence of noise.

5. The low interference-to-noise ratio interference detection method based on a multi-beam dual-satellite system according to claim 4, characterized in that: In step S400, the approximate coefficients and detail coefficients after threshold processing are reconstructed through inverse wavelet transform to obtain the denoised interference.

6. A low interference-to-noise ratio positioning method based on a multi-beam dual-satellite system, characterized in that: include: S500, substituting the reconstructed interference obtained by the interference detection method according to any one of claims 1 to 5 into the mutual ambiguity function to estimate the time-frequency difference parameters; S600: Using the estimated value of the time-frequency difference parameter and selecting the positions and velocities of the two corresponding satellites, the interference source is located through a positioning settlement equation group.

7. The low interference-to-noise ratio positioning method based on a multi-beam dual-satellite system according to claim 6, characterized in that: The mutual fuzzy function in step S500 is expressed as: ； in, and Forward interference received from primary and secondary satellites, Expressed as complex conjugate, is the Doppler frequency shift variable, is the total detection time.

8. The low interference-to-noise ratio positioning method based on a multi-beam dual-satellite system according to claim 7, characterized in that: The method for estimating the time-frequency difference parameters in step S500 is: for Take the absolute value , the absolute value of the real delay Doppler shift reaches its peak value, according to The peak position of and Doppler shift The estimated value is: ； In the formula, express The delay and Doppler shift estimates corresponding to the maximum value are obtained.

9. The low interference-to-noise ratio positioning method based on a multi-beam dual-satellite system according to claim 7, characterized in that: The positioning settlement equation group in step S600 is expressed as: ； in, represents the location of the unknown interference source, c is the speed of electromagnetic wave propagation in vacuum, It is the arrival time difference of the interference source interference reaching the two satellites measured by the two satellites, which includes the delay error caused by various errors; is the arrival frequency difference of the interference source reaching the two satellites measured by the two satellites, is the frequency of interference from the interference source, is the Earth's semi-major axis, is the Earth's semi-minor axis, is the satellite position, is the distance from the two satellites to the interference source, is the speed of the satellite.

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