Implementation method and system of time-varying multi-tone interference resisting system

Abstract

The invention provides an implementation method and system for a time-varying multi-tone interference resistant system, and the method comprises the steps: S1, enabling a receiving end to collect a continuous signal, and carrying out the preprocessing of the continuous signal, and obtaining a preprocessing result; s2, determining the number of multi-tone interference in the preprocessed signal by using a time-varying multi-tone interference detection algorithm; s3, applying a 1 / 2 overlapping window method to an AM algorithm, and removing the existing maximum single-tone interference; and S4, repeating the step S3 until the number of cycles reaches the number of multi-tone interferences, and obtaining a signal from which the multi-tone interferences are removed. The method can be realized on the basis of an AM single-tone interference elimination algorithm, the interference signals are restored and removed by estimating the interference parameters, interference resistance can be realized on the basis of not losing useful signal energy, and the interference elimination capability is relatively high.

Description

Technical Field

[0001] The present invention relates to the field of wireless communications, and in particular to a method and system for implementing a system for resisting time-varying multi-tone interference. Background Art

[0002] In modern military information warfare, the electromagnetic environment is becoming increasingly complex. Military communication interference can be divided into suppression interference and deception interference according to the interference type. Single-tone interference and multi-tone interference are typical suppression interference. Single-tone interference is an interference mode that continuously transmits a single sine wave signal at a fixed frequency. Multi-tone interference (also known as comb interference) is a combined interference mode of multiple single-frequency interferences. It has a relatively obvious interference effect on tactical data links such as Link4A, Link11 and Link16, so it is very important for the communication system to have the ability to resist multi-tone interference.

[0003] In time-varying channels, the interference quantity and parameters such as frequency, phase, and amplitude of multi-tone interference change over time. In current anti-multi-tone interference systems, most of them are aimed at non-time-varying channels, and the anti-interference algorithm cannot respond to the changes in multi-tone interference parameters in a timely manner, resulting in loss of anti-interference performance.

[0004] In actual communication confrontation scenarios, the enemy will try every means to interfere with our normal communications, and the number, frequency, amplitude and other parameters of multi-tone interference may change continuously. In order to ensure the effectiveness and reliability of the communication system, the communication system must have strong anti-interference capabilities. Therefore, there is an urgent need for an anti-multi-tone interference system for time-varying channels, which can detect the changes in interference patterns in the channel in real time and perform corresponding anti-interference processing. It can not only adapt to time-varying interference channels, but also have good anti-interference capabilities.

[0005] In a Chinese patent document with publication number CN101945064A, an iterative anti-multitone interference communication method based on energy expansion is disclosed. The communication method includes a transmission process, a multitone interference and background noise generation process, and a receiving process, and the receiving process includes the steps of: serial-to-parallel conversion; extracting multitone interference signals; reconstructing multitone interference signals; eliminating multitone interference signals; energy expansion inverse conversion; parallel-to-serial conversion; demodulation; modulation; serial-to-parallel conversion; energy expansion conversion; output. This patent document uses the energy expansion conversion principle without coding to obtain feedback gain to reduce computational complexity, which is essentially different from the technology used in the present invention. Summary of the invention

[0006] In view of the defects in the prior art, an object of the present invention is to provide a method and system for implementing a system for resisting time-varying multi-tone interference.

[0007] A method for implementing a system for resisting time-varying multi-tone interference provided by the present invention includes:

[0008] Step S1: enabling the receiving end to collect continuous signals and perform preprocessing to obtain preprocessed results;

[0009] Step S2: using a time-varying multi-tone interference detection algorithm to determine the amount of multi-tone interference in the pre-processed signal;

[0010] Step S3: Apply the 1 / 2 overlapping window method to the AM algorithm to remove the currently existing maximum single-tone interference;

[0011] Step S4: Repeat step S3 until the number of cycles reaches the number of multi-tone interferences, and obtain a signal after removing the multi-tone interferences.

[0012] Preferably, the preprocessing includes intercepting the received signal of the current time slot and performing discrete Fourier transform to obtain the received signal time domain r[n] and the received signal frequency domain R[k] of the current time slot.

[0013] Preferably, step S2 includes the following sub-steps:

[0014] Step S2.1: Calculate the power value P of each frequency point of the received signal in the current time slot i ,i=1,2,...M;

[0015] Step S2.2: Establish an interference set J and an interference-free set W and initialize them. The interference set J is empty, and all frequency points are in the interference-free set W.

[0016] Step S2.3: Calculate the average power P of the interference-free set W mean ;

[0017] Step S2.4: Calculate the power threshold Thr;

[0018] Step S2.5: The frequency points with power greater than the threshold Thr are defined as interference frequencies, removed from the non-interference set W, and included in the interference set J;

[0019] Step S2.6: Repeat steps S2.3 to S2.5 until the collection is no longer updated or the maximum number of iterations is reached;

[0020] Step S2.7: Group and merge the frequency points in the interference set J, and calculate the number K of multi-tone interference.

[0021] Preferably, step S3 includes the following sub-steps:

[0022] Step S3.1: Perform 1 / 2 overlapping windowing on the preprocessed signal and perform discrete Fourier transform to obtain the frequency domain representation of each segment of the signal;

[0023] Step S3.2: using AM algorithm to eliminate single tone interference;

[0024] Step S3.3: Add the overlapping parts in adjacent sequence blocks to obtain an estimated signal after removing single-tone interference.

[0025] Preferably, the step S3.2 includes the following sub-steps:

[0026] Step S3.2.1: Search for the maximum position of the spectrum

[0027] Step S3.2.2: Update the maximum estimated position of the spectrum and calculate the frequency estimation error value

[0028] Step S3.2.3: Repeat step S3.2.2 until the maximum number of iterations I is reached, and the final maximum estimated position of the spectrum is obtained. And estimate the parameters of the single-tone interference signal to obtain the estimated frequency Estimated Phase Estimated Range

[0029] Step S3.2.4: Reconstruct the single-tone interference signal And estimate the received signal without the single tone interference

[0030] According to the present invention, a system for implementing a system for resisting time-varying multi-tone interference includes:

[0031] Module M1: enables the receiving end to collect continuous signals and preprocess them to obtain the preprocessed results;

[0032] Module M2: using a time-varying multi-tone interference detection algorithm to determine the amount of multi-tone interference in the pre-processed signal;

[0033] Module M3: Apply the 1 / 2 overlapping window method to the AM algorithm to remove the largest single-tone interference currently existing;

[0034] Module M4: Repeat module M3 until the number of cycles reaches the number of multi-tone interference, and obtain a signal after removing the multi-tone interference.

[0035] Preferably, the preprocessing includes intercepting the received signal of the current time slot and performing discrete Fourier transform to obtain the received signal time domain r[n] and the received signal frequency domain R[k] of the current time slot.

[0036] Preferably, the module M2 includes the following submodules:

[0037] Module M2.1: Calculate the power value P of each frequency point of the received signal in the current time slot i ,i=1,2,...M;

[0038] Module M2.2: Establish and initialize the interference set J and the non-interference set W. The interference set J is empty and all frequency points are in the non-interference set W.

[0039] Module M2.3: Calculate the average power P of the interference-free set W mean ;

[0040] Module M2.4: Calculate the power threshold Thr;

[0041] Module M2.5: The frequencies with power greater than the threshold Thr are defined as interference frequencies, removed from the non-interference set W, and included in the interference set J;

[0042] Module M2.6: Repeat Module M2.3-Module M2.5 until the collection is no longer updated or the maximum number of iterations is reached;

[0043] Module M2.7: Group and merge the frequency points in the interference collection J, and calculate the number K of multi-tone interference.

[0044] Preferably, the module M3 includes the following submodules:

[0045] Module M3.1: Perform 1 / 2 overlapping windowing on the preprocessed signal and perform discrete Fourier transform to obtain the frequency domain representation of each segment of the signal;

[0046] Module M3.2: Use AM algorithm to eliminate single tone interference;

[0047] Module M3.3: Add the overlapping parts in adjacent sequence blocks to obtain the estimated signal after removing the single-tone interference.

[0048] Preferably, the module M3.2 includes the following submodules:

[0049] Module M3.2.1: Searching for the maximum position of the spectrum

[0050] Module M3.2.2: Update the maximum estimated position of the spectrum and calculate the frequency estimation error value

[0051] Module M3.2.3: Repeat module M3.2.2 until the maximum number of iterations I is reached, and the final maximum estimated position of the spectrum is obtained. And estimate the parameters of the single-tone interference signal to obtain the estimated frequency Estimated Phase Estimated Range

[0052] Module M3.2.4: Reconstructing a single-tone interference signal And estimate the received signal without the single tone interference

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] 1. The present invention can be implemented based on an AM single-tone interference elimination algorithm. By estimating interference parameters, the interference signal is restored and removed, and anti-interference can be achieved without losing useful signal energy. Therefore, the interference elimination capability is relatively strong.

[0055] 2. The time-varying multi-tone interference detection algorithm used in the present invention can obtain the multi-tone interference quantity with only one detection, the power threshold changes dynamically, the interference judgment is fast and effective, and the error leveling problem can be solved.

[0056] 3. The system of the present invention has strong applicability, can adapt to changes in multi-tone interference (such as changes in interference patterns and parameters), and perform corresponding interference removal processing, and has strong flexibility and practicality.

[0057] Other beneficial effects of the present invention will be explained in the specific implementation manner through the introduction of specific technical features and technical solutions. Through the introduction of these technical features and technical solutions, those skilled in the art should be able to understand the beneficial technical effects brought about by the technical features and technical solutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0059] Figure 1 This is a diagram of the communication interference scenario in the countermeasure environment of the present invention.

[0060] Figure 2 The present invention is a flowchart of the system for resisting time-varying multi-tone interference.

[0061] Figure 3 The present invention is a flow chart for implementing time-varying multi-tone interference detection.

[0062] Figure 4 It is a schematic diagram of overlapping windowing of the present invention.

[0063] Figure 5 The present invention is a flowchart for implementing single-tone interference elimination.

[0064] Figure 6 This is a spectrum diagram of input signals of the anti-multi-tone interference system of the present invention.

[0065] Figure 7 This is a spectrum diagram of the divisor signal of the anti-multi-tone interference system of the present invention.

[0066] Figure 8 The figure is a curve diagram showing the bit error rate of the system according to the present invention changing with the signal-to-noise ratio.

[0067] Fig. 9 The figure is a curve diagram showing the bit error rate of the system according to the present invention changing with the signal-to-interference ratio.

[0068] Fig.10 This is a curve diagram of bit error rate changing with signal-to-interference ratio when only the single-tone interference elimination algorithm of the present invention is used. DETAILED DESCRIPTION

[0069] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0070] Reference Figure 1 and Figure 2 As shown, a method for implementing a system for resisting time-varying multi-tone interference includes:

[0071] Step 1: Sample and receive the continuous signal at the receiving end, intercept the received signal of the current time slot, and perform discrete Fourier transform on it. The time domain and frequency domain received signals of the current time slot are r[n] and R[k] respectively.

[0072] Step 2: Detect the number of multi-tone interferences using the time-varying multi-tone interference detection algorithm. The process of the time-varying multi-tone interference detection algorithm is as follows: Figure 3 As shown, it includes the following 6 steps:

[0073] Step 2.1: Calculate the power value P of each frequency point of the received signal in the current time slot i ,i=1,2,...M.

[0074] Step 2.2: Establish the interference set J and the non-interference set W and initialize them:

[0075] The interference set J is empty, and all frequency points are in the non-interference set W.

[0076] Step 2.3: Calculate the average power P of the interference-free set W mean .

[0077] Step 2.4: Calculate the power threshold Thr.

[0078] Step 2.5: The frequencies with power greater than the threshold Thr are considered as interference frequencies, removed from the non-interference set W, and included in the interference set J.

[0079] Repeat steps 2.3 to 2.4 until the collection is no longer updated or the maximum number of iterations is reached.

[0080] Step 2.6: Group and merge the frequency points in the interference set J and calculate the number of interferences K.

[0081] Step 3: Divide the received signal into two paths, perform 1 / 2 overlapping windowing, and perform discrete Fourier transform to obtain r1[n] and R1[k].

[0082] Step 4: AM (Aboutanios-Mulgrew) algorithm is used in the present invention to remove the maximum single-tone interference. The algorithm improves the anti-interference capability of the system by adaptively estimating and eliminating single-tone interference signals.

[0083] It includes the following 4 steps:

[0084] Step 4.1: Search for the maximum position of the spectrum

[0085] Step 4.2: Update the maximum estimated position of the spectrum and calculate the frequency estimation error value

[0086] Step 4.3: Repeat step 4.2 until the maximum number of iterations I is reached, and the final maximum estimated position of the spectrum is obtained. And estimate the parameters of the single-tone interference signal to obtain the estimated frequency Estimated Phase Estimated Range

[0087] Step 4.4: Reconstruct the single-tone interference signal And estimate the received signal without the single tone interference

[0088] Step 5: Received signal reconstruction: Add the overlapping parts in adjacent sequence blocks to obtain the estimated signal after removing the single-tone interference in this round

[0089] Step 6: Repeat steps 3 to 5 until the number of cycles reaches the number of multi-tone interference K, and finally obtain the signal after multi-tone interference is removed.

[0090] The above is a basic embodiment of the present invention. The technical solution of the present invention is further described below through a preferred embodiment.

[0091] Example 1

[0092] The present invention proposes a design and implementation method flow chart of a system for resisting time-varying multi-tone interference, as shown in FIG. Figure 2 As shown in the figure. Among them, the time-varying multi-tone interference detection implementation flow chart is as follows Figure 3 As shown, the single-tone interference elimination implementation flow chart is as follows Figure 5As shown. The received signal of the system is r[n], and the output signal after interference removal is

[0093] Step 1: Sample the continuous signal at the receiving end with a sampling rate of f s . Intercept the received signal of the current time slot and perform discrete Fourier transform on it. In a time-varying multi-tone interference channel, the amount, amplitude, frequency, and phase of interference in the channel change over time, but in each time slot, it can be considered that the channel state is stable and the interference pattern does not change. When the number of sampling points per time slot is N s When the sampled signal is padded with zeros, a discrete Fourier transform of M points is performed. Then the time domain and frequency domain expressions of the received signal in the current time slot are:

[0094]

[0095]

[0096] Where x[n] represents the sampled transmitted signal (useful data), I represents the number of multi-tone interference, and A i is the interference amplitude of the ith single-tone interference, f i is the i-th single-tone interference frequency, is the initial phase of the i-th single tone interference.

[0097] Step 2: Detect the number of multi-tone interferences using a time-varying multi-tone interference detection algorithm.

[0098] The process of the time-varying multi-tone interference detection algorithm is as follows Figure 3 As shown, it includes the following 6 steps:

[0099] Step 2.1: Calculate the power value P of each frequency point of the received signal in the current time slot i ,i=1,2,...M. The calculation formula is:

[0100]

[0101] Step 2.2: Establish the interference set J and the non-interference set W and initialize them:

[0102] The interference set J is empty, and all frequency points are in the non-interference set W, see formula (4);

[0103]

[0104] Step 2.3: Calculate the average power P of the interference-free set W mean In order to reduce the amount of calculation in the averaging process, an incremental calculation method can be used. Formula (5) is used only when the average power is calculated initially, and the power average is updated using formula (6) in the subsequent iterations.

[0105] During initialization, the average power of the interference-free set can be calculated according to formula (5):

[0106]

[0107] In subsequent iterations, the average power of the interference-free set can be calculated according to formula (6). The incremental calculation method greatly reduces the computational complexity of the multi-tone interference detection algorithm:

[0108]

[0109] Among them, ΔW represents the reduction of the interference-free set W, that is, the set of points considered as interference points in the previous iteration.

[0110] Step 2.4: Calculate the power threshold Thr by using equation (7). cme is a preset interference detection threshold;

[0111] Thr=P mean ·T cme (7)

[0112] Among them, the preset interference detection threshold value T cme If the value is too large, interference may be missed, affecting the performance of the anti-interference system; if the value is too small, it may lead to misjudgment of the estimated number of interferences, ultimately resulting in incomplete interference removal or affecting the quality of the output signal. In this embodiment, the value is set to 2.9.

[0113] Step 2.5: The frequency points with power greater than the threshold Thr are considered as interference frequencies, removed from the non-interference set W, and included in the interference set J. The set update formula is expressed as:

[0114]

[0115] Repeat steps 2.3 to 2.4 until the collection is no longer updated or the maximum number of iterations is reached. At this point, the power of all frequency points in the interference-free collection W is less than the power threshold Thr, and the following conditions are met:

[0116] P i ≤Thr,i∈W (9)

[0117] Step 2.6: Group and merge the frequency points in the interference set J, and calculate the interference number K. If there is a group of continuous frequency points that are all in the interference set, only the central frequency point of the group is retained, and the other frequency points are removed from the set J. The number of retained frequency points in the interference set J is the estimated interference number K.

[0118] In this step, it is necessary to group and merge adjacent interference frequency points. Since the detection of interference is based on the frequency domain power spectrum of the current time slot signal, no windowing is performed when intercepting the current time slot signal, which can reduce the complexity of the algorithm. However, correspondingly, direct truncation will cause spectrum leakage. In order to reduce the misjudgment of multi-tone interference caused by spectrum leakage, the adjacent interference frequency points obtained after iteration are grouped and merged to ensure the accuracy of interference detection. The final set J is the estimated interference collection, and the number of frequency points in the interference collection J is the estimated interference number K.

[0119] Step 3: Divide the received signal into two paths and perform 1 / 2 overlapping windowing. The overlapping windowing diagram is as follows: Figure 4 As shown. r Represents the overlapping windowing length. The specific windowing method of 1 / 2 overlapping windowing is: divide the received signal into two paths, the relative delay length of the two paths is 1 / 2N, and the sequence of truncation length N is multiplied by the window function w[n] of equal length. For each path, the overlapping windowed signal is represented by r1[n], and its frequency domain after discrete Fourier transform is represented by R1[k]:

[0120] r1[n]=r[n]·w[n],n=0,1,...N-1 (10)

[0121]

[0122] For 1 / 2 overlap windows, There is a 50% overlap between two adjacent windowed sequences. At this time, the signal-to-noise ratio loss caused by the use of the Hamming window and the Hanning window is zero, and the signal-to-noise ratio loss is only caused by interference suppression and spectrum leakage. At the same time, when the overlap ratio is 50%, the amount of calculation is twice that of no windowing, and it will not introduce too much computational complexity. In this embodiment, the system uses the Hamming window as the 1 / 2 overlapping data window, and the length is N=2048.

[0123] Step 4: Single tone interference elimination. Figure 5 As shown, the AM single-tone interference elimination algorithm is used to estimate the parameters of the single-tone interference signal to achieve the purpose of reconstruction and interference removal, and single-tone interference removal is achieved without losing signal energy. Step 4 includes the following 4 sub-steps:

[0124] Step 4.1: Search for the maximum position of the R1[k] spectrum The formula is:

[0125]

[0126] Step 4.2: Update the maximum estimated position of the spectrum.

[0127] Calculate the frequency estimate error value And update the maximum estimated position of the spectrum according to formula (14).

[0128]

[0129]

[0130] Step 4.3: Repeat step 4.2 until the maximum number of iterations I is reached, and the final maximum estimated position of the spectrum can be obtained. Combined sampling rate f s , the parameters of the single-tone interference signal can be estimated to obtain the estimated frequency Estimated Phase Estimated Range

[0131]

[0132]

[0133]

[0134] Where ∠ is the phase extraction operation, To calculate the real part.

[0135] Step 4.4: Reconstruct the single-tone interference signal And estimate the received signal without the single tone interference

[0136]

[0137]

[0138] Step 5: Received signal reconstruction: Add the overlapping parts in adjacent sequence blocks to obtain the estimated signal after single-tone interference removal in this round.

[0139] Step 6: Repeat steps 3 to 5 until the number of cycles reaches the number of multi-tone interference K. The final signal This is the result of removing multi-tone interference.

[0140] The effect of the present invention can be illustrated by MATLAB simulation. Specifically, the MATLAB simulation condition of the present invention is MATLAB R2014a simulation software, and the system simulation parameters are shown in Table 1.

[0141] Table 1 Simulation parameters

[0142]

[0143] In the simulation, the channel is set to have three modes: single-tone interference, dual-tone interference, and triple-tone interference. In different time slots, the number of multi-tone interference will change, and the frequency, amplitude, and phase of the interference will also change accordingly. In time slot t, the state probability matrix P of the time-varying channel t Set to:

[0144]

[0145] Among them, p1 represents the probability of a single-tone interference channel, p2 represents the probability of a two-tone interference channel, and p3 represents the probability of a three-tone interference channel.

[0146] The simulation content and results are as follows:

[0147] 1) Taking the case of a fixed three-tone interference in the channel as an example, the signal spectrum before and after being processed by the anti-multi-tone interference system under the time-varying channel is as follows: Figure 6 , Figure 7 As shown. Figure 6 It can be seen that there are three single-tone interferences in the input signal of the anti-multi-tone interference system (i.e. the original received signal), with frequencies of 80kHz, 18.4kHz, and 488kHz, and the spectrum is higher than the noisy signal. After being processed by the time-varying channel anti-multi-tone interference system, Figure 7 It can be seen that the interference has been removed, indicating that the system can effectively remove fixed multi-tone interference. On this basis, the system's ability to resist multi-tone interference in time-varying channels is studied.

[0148] 2) In order to study the system's ability to resist multi-tone interference in a time-varying channel, the ratio of useful signal power to maximum interference power (hereinafter referred to as signal-to-interference ratio) is set to 11, and the interference pattern is constantly changing. The difference in the system's anti-time-varying multi-tone interference performance is studied in systems using different anti-interference algorithms. The simulation results are shown in Figure 2. Figure 8 As shown. The CME anti-interference system is selected as a comparison. This system uses the frequency domain CME anti-interference algorithm and has no independent interference detection module. From the simulation results, it can be seen that the system algorithm can effectively eliminate time-varying multi-tone interference. -3 When the signal-to-noise ratio of the algorithm is 5dB lower than that of the CME algorithm, and only 0.8dB higher than that without interference, it shows that the system has strong ability to resist time-varying multi-tone interference.

[0149] 3) Fig. 9 The simulation results of the system bit error rate changing with the signal-to-interference ratio SJR using different anti-interference systems in a time-varying multi-tone interference channel with a signal-to-noise ratio of 10. Fig.10 This is the simulation result when only the AM single-tone anti-interference algorithm is used. Fig. 9 It can be seen that when SJR is between -20dB and 10dB, the interference is relatively large. After the anti-interference processing of this system, the bit error rate can be reduced to 10 -4When SJR is greater than 10, the bit error rate decreases with the increase of signal-to-interference ratio. At this time, the interference power is small and its spectrum is buried under the noise spectrum. Multi-tone interference detection cannot detect the interference and does not perform interference elimination, thus avoiding the signal-to-noise ratio loss caused by the interference elimination algorithm. Fig.10 It can be seen that this system solves the error floor problem of the AM single-tone elimination algorithm.

[0150] It can be seen from the above MATLAB simulation results that the design and implementation method of a time-varying multi-tone interference resistance system proposed by the present invention can effectively remove time-varying multi-tone interference. The system has strong applicability, can adapt to the changes of multi-tone interference (three multi-tone modes, different interference parameter changes), and perform corresponding processing; when the signal-to-interference ratio is fixed, after being processed by the anti-time-varying multi-tone interference system, only 0.8dB signal-to-noise ratio is lost compared to when there is no interference; when the signal-to-noise ratio is fixed, after being processed by the anti-time-varying multi-tone interference system, when the signal-to-noise ratio is relatively small, the system bit error rate is improved by an order of magnitude relative to the comparison system, and when the signal-to-noise ratio is relatively large, there is no error leveling. Therefore, the system has the advantages of adapting to time-varying interference channels, good anti-multi-tone interference performance, and no error leveling, and has certain advantages.

[0151] The present invention also provides an implementation system of a system for resisting time-varying multi-tone interference. The implementation system of the system for resisting time-varying multi-tone interference can be implemented by executing the process steps of the implementation method of the system for resisting time-varying multi-tone interference, that is, those skilled in the art can understand the implementation method of the system for resisting time-varying multi-tone interference as a preferred implementation mode of the implementation system of the system for resisting time-varying multi-tone interference.

[0152] Specifically, a system for implementing a system for resisting time-varying multi-tone interference includes:

[0153] Module M1: enables the receiving end to collect continuous signals and preprocess them to obtain the preprocessed results;

[0154] Module M2: using a time-varying multi-tone interference detection algorithm to determine the amount of multi-tone interference in the pre-processed signal;

[0155] Module M3: Apply the 1 / 2 overlapping window method to the AM algorithm to remove the largest single-tone interference currently existing;

[0156] Module M4: Repeat module M3 until the number of cycles reaches the number of multi-tone interference, and obtain a signal after removing the multi-tone interference.

[0157] The preprocessing includes intercepting the received signal of the current time slot and performing discrete Fourier transform to obtain the received signal time domain r[n] and the received signal frequency domain R[k] of the current time slot.

[0158] The module M2 includes the following submodules:

[0159] Module M2.1: Calculate the power value P of each frequency point of the received signal in the current time slot i ,i=1,2,...M;

[0160] Module M2.2: Establish and initialize the interference set J and the non-interference set W. The interference set J is empty and all frequency points are in the non-interference set W.

[0161] Module M2.3: Calculate the average power P of the interference-free set W mean ;

[0162] Module M2.4: Calculate the power threshold Thr;

[0163] Module M2.5: The frequencies with power greater than the threshold Thr are defined as interference frequencies, removed from the non-interference set W, and included in the interference set J;

[0164] Module M2.6: Repeat Module M2.3-Module M2.5 until the collection is no longer updated or the maximum number of iterations is reached;

[0165] Module M2.7: Group and merge the frequency points in the interference collection J, and calculate the number K of multi-tone interference.

[0166] The module M3 includes the following submodules:

[0167] Module M3.1: Perform 1 / 2 overlapping windowing on the preprocessed signal and perform discrete Fourier transform to obtain the frequency domain representation of each segment of the signal;

[0168] Module M3.2: Use AM algorithm to eliminate single tone interference;

[0169] Module M3.3: Add the overlapping parts in adjacent sequence blocks to obtain the estimated signal after removing the single-tone interference.

[0170] The module M3.2 includes the following submodules:

[0171] Module M3.2.1: Searching for the maximum position of the spectrum

[0172] Module M3.2.2: Update the maximum estimated position of the spectrum and calculate the frequency estimation error value

[0173] Module M3.2.3: Repeat module M3.2.2 until the maximum number of iterations I is reached, and the final maximum estimated position of the spectrum is obtained. And estimate the parameters of the single-tone interference signal to obtain the estimated frequency Estimated Phase Estimated Range

[0174] Module M3.2.4: Reconstructing a single-tone interference signal And estimate the received signal without the single tone interference

[0175] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0176] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for implementing a system for resisting time-varying multi-tone interference, characterized in that: include: Step S1: enabling the receiving end to collect continuous signals and perform preprocessing to obtain preprocessed results; Step S2: using a time-varying multi-tone interference detection algorithm to determine the amount of multi-tone interference in the pre-processed signal; Step S3: Apply the 1 / 2 overlapping window method to the AM algorithm to remove the currently existing maximum single-tone interference; Step S4: Repeat step S3 until the number of cycles reaches the number of multi-tone interferences, and obtain a signal after removing the multi-tone interferences.

2. The method for implementing the anti-time-varying multi-tone interference system according to claim 1, characterized in that: The preprocessing includes intercepting the received signal of the current time slot and performing discrete Fourier transform to obtain the received signal time domain r[n] and the received signal frequency domain R[k] of the current time slot.

3. The method for implementing the anti-time-varying multi-tone interference system according to claim 2, characterized in that: The step S2 comprises the following sub-steps: Step S2.1: Calculate the power value P of each frequency point of the received signal in the current time slot i ,i=1,2,...M; Step S2.2: Establish an interference set J and an interference-free set W and initialize them. The interference set J is empty, and all frequency points are in the interference-free set W. Step S2.3: Calculate the average power P of the interference-free set W mean ; Step S2.4: Calculate the power threshold Thr; Step S2.5: The frequency points with power greater than the threshold Thr are defined as interference frequencies, removed from the non-interference set W, and included in the interference set J; Step S2.6: Repeat steps S2.3 to S2.5 until the collection is no longer updated or the maximum number of iterations is reached; Step S2.7: Group and merge the frequency points in the interference set J, and calculate the number K of multi-tone interference.

4. The method for implementing the anti-time-varying multi-tone interference system according to claim 3 is characterized in that: The step S3 comprises the following sub-steps: Step S3.1: Perform 1 / 2 overlapping windowing on the preprocessed signal and perform discrete Fourier transform to obtain the frequency domain representation of each segment of the signal; Step S3.2: using AM algorithm to eliminate single tone interference; Step S3.3: Add the overlapping parts in adjacent sequence blocks to obtain an estimated signal after removing single-tone interference.

5. The method for implementing the anti-time-varying multi-tone interference system according to claim 4, characterized in that: The step S3.2 includes the following sub-steps: Step S3.2.1: Search for the maximum position of the spectrum Step S3.2.2: Update the maximum estimated position of the spectrum and calculate the frequency estimation error value Step S3.2.3: Repeat step S3.2.2 until the maximum number of iterations I is reached, and the final maximum estimated position of the spectrum is obtained. And estimate the parameters of the single-tone interference signal to obtain the estimated frequency Estimated Phase Estimated Range Step S3.2.4: Reconstruct the single-tone interference signal And estimate the received signal without the single tone interference 6. A system for implementing a time-varying multi-tone interference resistance system, characterized in that: include: Module M1: enables the receiving end to collect continuous signals and preprocess them to obtain the preprocessed results; Module M2: using a time-varying multi-tone interference detection algorithm to determine the amount of multi-tone interference in the pre-processed signal; Module M3: Apply the 1 / 2 overlapping window method to the AM algorithm to remove the largest single-tone interference currently existing; Module M4: Repeat module M3 until the number of cycles reaches the number of multi-tone interference, and obtain a signal after removing the multi-tone interference.

7. The implementation system of the anti-time-varying multi-tone interference system according to claim 6, characterized in that: The preprocessing includes intercepting the received signal of the current time slot and performing discrete Fourier transform to obtain the received signal time domain r[n] and the received signal frequency domain R[k] of the current time slot.

8. The implementation system of the anti-time-varying multi-tone interference system according to claim 7, characterized in that: The module M2 includes the following submodules: Module M2.1: Calculate the power value P of each frequency point of the received signal in the current time slot i ,i=1,2,...M; Module M2.2: Establish and initialize the interference set J and the non-interference set W. The interference set J is empty and all frequency points are in the non-interference set W. Module M2.3: Calculate the average power P of the interference-free set W mean ; Module M2.4: Calculate the power threshold Thr; Module M2.5: The frequencies with power greater than the threshold Thr are defined as interference frequencies, removed from the non-interference set W, and included in the interference set J; Module M2.6: Repeat Module M2.3-Module M2.5 until the collection is no longer updated or the maximum number of iterations is reached; Module M2.7: Group and merge the frequency points in the interference collection J, and calculate the number K of multi-tone interference.

9. The implementation system of the anti-time-varying multi-tone interference system according to claim 8, characterized in that: The module M3 includes the following submodules: Module M3.1: Perform 1 / 2 overlapping windowing on the preprocessed signal and perform discrete Fourier transform to obtain the frequency domain representation of each segment of the signal; Module M3.2: Use AM algorithm to eliminate single tone interference; Module M3.3: Add the overlapping parts in adjacent sequence blocks to obtain the estimated signal after removing the single-tone interference.

10. The implementation system of the anti-time-varying multi-tone interference system according to claim 9, characterized in that: The module M3.2 includes the following submodules: Module M3.2.1: Searching for the maximum position of the spectrum Module M3.2.2: Update the maximum estimated position of the spectrum and calculate the frequency estimation error value Module M3.2.3: Repeat module M3.2.2 until the maximum number of iterations I is reached, and the final maximum estimated position of the spectrum is obtained. And estimate the parameters of the single-tone interference signal to obtain the estimated frequency Estimated Phase Estimated Range Module M3.2.4: Reconstructing a single-tone interference signal And estimate the received signal without the single tone interference

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