Frequency winding modulation identification method and system beyond order limitation

Abstract

The invention belongs to the field of modulation identification, and provides a frequency winding modulation identification method and system beyond order limitation, and the method comprises the steps: obtaining a radar signal, and carrying out the sampling, and obtaining a radar analysis signal; performing frequency winding based on the radar analysis signal to obtain a winding frequency of the radar analysis signal; and performing modulation identification according to the winding frequency of the radar analysis signal. On the basis of the instantaneous autocorrelation algorithm, the concept of frequency winding is provided, the limitation that the order is too small is broken through, the order is directly set to be large, the anti-noise performance of the algorithm is improved, and typical modulation signals have new different digital characteristics and can be effectively distinguished.

Description

Technical Field

[0001] The present invention belongs to the technical field of modulation recognition, and in particular relates to a modulation recognition method and system for frequency warping beyond order limitation. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] The traditional radar signal sorting technology based on five characteristic parameters (i.e., arrival angle, carrier frequency, arrival time, pulse width and pulse amplitude) can no longer meet the current needs. However, the internal characteristics of the pulse have strong stability and separability. Identifying the intra-pulse modulation characteristics can improve the accuracy of signal sorting. Therefore, the recognition of the internal characteristics of the pulse is particularly important. The research and development of related technologies for identifying the intra-pulse modulation type of radar signals has very practical significance. In order to meet the needs of DSP processing, time domain processing methods are generally used. The more widely used methods include multiple phase difference method and instantaneous autocorrelation method.

[0004] The multiple phase difference method estimates the phase of the signal, performs phase reconstruction or unwrapping, and then performs N-fold difference, which can smooth the noise and improve the adaptability of the phase difference method to low signal-to-noise ratio signals.

[0005] The principle of the instantaneous autocorrelation method is to calculate the instantaneous autocorrelation of the signal (the instantaneous autocorrelation function is defined as the product of the signal's own conjugate and the signal delay), obtain its phase, and then obtain the instantaneous frequency of the signal through the phase. The method of extracting the instantaneous frequency is relatively simple and is widely used.

[0006] Under low signal-to-noise ratio conditions, the multiple phase difference method is affected by various noises, including various thermal noises, measurement noise, etc., the signal-to-noise ratio decreases and the number of phase differences increases. The instantaneous frequency obtained during unwrapping will have sudden errors, so the unwrapping algorithm is very demanding. The number or order of the instantaneous autocorrelation algorithm should not be too large, generally 1 or 2. At this moment, the noise correlation causes the performance under low signal-to-noise ratio to drop sharply.

[0007] In other words, the traditional multiple phase difference method has too high requirements for the unwrapping algorithm, and often fails due to noise jitter. The multiplicity or order of the instantaneous autocorrelation algorithm cannot be set too large. The positions of two adjacent sampling points in the correlation calculation are very close. The noise correlation at this moment will cause the performance of the algorithm to drop sharply at low signal-to-noise ratios. Summary of the invention

[0008] In order to solve the above problems, the present invention proposes a modulation recognition method and system for frequency warping that exceeds the order limit. The present invention avoids the calculation of unwarping by the multiple phase difference method and can improve the anti-noise performance under low signal-to-noise ratio conditions.

[0009] According to some embodiments, a first solution of the present invention provides a modulation recognition method for frequency warping beyond the order limitation, using the following technical solution:

[0010] A modulation recognition method for frequency warping beyond order limitation, comprising:

[0011] Acquire radar signals and perform sampling to obtain radar analysis signals;

[0012] Perform frequency warping based on the radar analysis signal to obtain a warping frequency of the radar analysis signal;

[0013] Modulation recognition is performed based on the convolution frequency of the radar analysis signal.

[0014] Furthermore, the radar signal is acquired and sampled to obtain a radar analysis signal, specifically:

[0015] The radar analysis signal obtained after the radar signal is sampled is:

[0016]

[0017] Where A is the amplitude, f(n) is the frequency modulation function of the signal, is the phase modulation function, is the initial phase, f s is the sampling frequency.

[0018] Furthermore, the frequency warping is performed based on the radar analysis signal, specifically:

[0019]

[0020] Where multi is the order and multi>>2, conj[] means taking the conjugate of the signal, and angle() means taking the angle of the complex number, which ranges from (-π,π].

[0021] Furthermore, the modulation identification is performed according to the wrapping frequency of the radar analysis signal, specifically:

[0022] The wrapping frequency of the radar resolution signal is used as the distinguishing feature;

[0023] Distinguish the modulation types of different radar signals;

[0024] Get the modulation type of the radar signal.

[0025] According to some embodiments, a second solution of the present invention provides a modulation recognition system for frequency warping beyond the order limitation, using the following technical solution:

[0026] A modulation recognition system for frequency warping beyond order limitation, comprising:

[0027] A signal sampling module is configured to acquire and sample radar signals to obtain radar analysis signals;

[0028] A frequency warping module is configured to perform frequency warping based on the radar analysis signal to obtain a warping frequency of the radar analysis signal;

[0029] The modulation identification module is configured to perform modulation identification according to the wrapping frequency of the radar analysis signal.

[0030] Furthermore, in the signal sampling module, the radar signal is acquired and sampled to obtain the radar analysis signal, specifically:

[0031] The radar analysis signal obtained after the radar signal is sampled is:

[0032]

[0033] Where A is the amplitude, f(n) is the frequency modulation function of the signal, is the phase modulation function, is the initial phase, f s is the sampling frequency.

[0034] Furthermore, in the frequency warping module, frequency warping is performed based on the radar analysis signal, specifically:

[0035]

[0036] Where multi is the order and multi>>2, conj[] means taking the conjugate of the signal, and angle() means taking the angle of the complex number, which ranges from (-π,π].

[0037] According to some embodiments, a third aspect of the present invention provides a computer-readable storage medium.

[0038] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a modulation identification method for frequency warping beyond order limitation as described in the first aspect above.

[0039] According to some embodiments, a fourth aspect of the present invention provides a computer device.

[0040] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the modulation identification method of frequency warping beyond the order limitation as described in the first aspect above are implemented.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] The present invention aims at the characteristics that the multi-phase difference method unwrapping is particularly sensitive to noise, and the multiplicity or order of the instantaneous autocorrelation algorithm should not be too large. Based on the instantaneous autocorrelation algorithm, the present invention proposes the concept of frequency warping, breaks through the limitation of too small order, directly sets the order to be very large, improves the anti-noise performance of the algorithm, and new and different digital features appear in typical modulated signals, which can be effectively distinguished. The multiplicity setting breaks through the limitation of the traditional instantaneous autocorrelation method; for LFM signals, the order setting can be appropriately increased, and the more orders, the more obvious the broken line features. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0044] Figure 1 It is a flow chart of a modulation identification method of frequency warping beyond order limitation in an embodiment of the present invention;

[0045] Figure 2 is a result diagram of the multiple phase difference method with a multiplicity of 20 in an embodiment of the present invention;

[0046] Figure 3 is a graph of algorithm results proposed in this embodiment of the present invention when the multiplicity multi is 2;

[0047] Figure 4 is a graph of algorithm results proposed in this embodiment of the present invention when the multiplicity multi is 20;

[0048] Figure 5 This is a graph of the algorithm result proposed in this embodiment of the present invention when the multiplicity multi is 80;

[0049] Figure 6 is a QPSK convolution frequency distribution diagram in an embodiment of the present invention;

[0050] Figure 7 is a BPSK convolution frequency distribution diagram in an embodiment of the present invention;

[0051] Figure 8 2FSK convolution frequency distribution diagram in an embodiment of the present invention;

[0052] Fig. 9 is a CW winding frequency distribution diagram in an embodiment of the present invention;

[0053] Fig.10 is a LFM winding frequency distribution diagram in an embodiment of the present invention;

[0054] Fig.11 NLFM winding frequency distribution diagram in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0056] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0057] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0058] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0059] Embodiment 1

[0060] like Figure 1 As shown, this embodiment provides a modulation identification method for frequency warping that exceeds the order limit. This embodiment uses the method applied to a server as an example for illustration. It can be understood that the method can also be applied to a terminal, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network servers, cloud communications, middleware services, domain name services, security services CDN, and big data and artificial intelligence platforms. The terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, etc., but is not limited to this. The terminal and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in this application. In this embodiment, the method includes the following steps:

[0061] Acquire radar signals and perform sampling to obtain radar analysis signals;

[0062] Perform frequency warping based on the radar analysis signal to obtain a warping frequency of the radar analysis signal;

[0063] Modulation recognition is performed based on the convolution frequency of the radar analysis signal.

[0064] Specifically, the method described in this embodiment includes:

[0065] Assume that the analytical signal obtained after sampling the radar signal is:

[0066]

[0067] In the formula, A is the amplitude, f(n) is the frequency modulation function of the signal, is the phase modulation function, is the initial phase, f s is the sampling frequency.

[0068] The present invention proposes the concept of warping frequency, and uses the characteristics of frequency warping to perform signal modulation recognition. The formula for calculating the warping frequency is as follows:

[0069]

[0070] In the above formula, multi is the order (or multiplicity) and multi>>2. For pulse coded signals, multi must be less than the minimum code length of the coded signal. For LFM (linear frequency modulation) and NLFM (non-linear frequency modulation) signals, it can be increased appropriately. conj[] means taking the conjugate of the signal.

[0071] In θ(m,multi)=angle{s(m+j)·conj[s(m-(multi-j))]}, angle() represents the complex angle, and its range is (-π,π]. Although frequency warping may occur, increasing multi will further reduce the impact of noise, and after frequency warping, the signal characteristics of various modulation methods are unique. Therefore, the modulation of the signal can be identified based on the characteristics after frequency warping.

[0072] Taking the BPSK signal as an example, assuming that the carrier f0 = 100, f s =1000, multi=6, then the phase difference is:

[0073] The winding result at this time is The final winding frequency is therefore: When a code element jumps from 0 to 1, then

[0074] The modulation identification is performed according to the wrapping frequency of the radar analysis signal, specifically:

[0075] The wrapping frequency of the radar resolution signal is used as the distinguishing feature;

[0076] Distinguish the modulation types of different radar signals;

[0077] Get the modulation type of the radar signal.

[0078] This embodiment proposes a new digital feature of signal frequency warping as a distinguishing feature for radar signal modulation identification, thereby distinguishing the modulation types of different radar signals. The signal modulation type identification step based on the digital feature of signal frequency warping is the same as the traditional signal modulation identification method, so it will not be repeated here.

[0079] Taking LFM signal as an example, the simulation parameters are set as follows: sampling rate f s =1000Hz, carrier f0=300Hz, compression ratio k=40, duration T=5s, signal-to-noise ratio is 8dB. The frequency calculation is performed by using multi=20 multi-phase difference method and the algorithm proposed in the present invention. The results are as follows: Figure 2 , Figure 3 , Figure 4 as well as Figure 5 As shown:

[0080] Figure 2 This is the result obtained by using the multiple phase difference method. Figure 2 It can be seen that the unwrapping method is particularly sensitive to noise, resulting in the LFM phase difference not being able to obtain a straight line and the signal characteristics being extremely fuzzy. Figure 3 Using the method in this paper, multi=2, there is no frequency wrapping. The essence is the instantaneous correlation method. Since the multiplicity multi is too small, the noise has a great influence on the correlation effect. Figure 4 and Figure 5 When multi is increased, the frequency cannot appear in the form of a straight line. Due to frequency wrapping, an obvious equidistant broken line feature appears, that is, the frequency appears to be wrapped. At the same time, the influence of noise is significantly reduced. The larger the multi, the lower the influence of noise on phase difference jitter, and the more obvious the broken line feature.

[0081] Frequency warping calculations are performed for the following six typical modulation methods. The signal types include LFM (linear frequency modulation), NLFM (non-linear frequency modulation, cubic polynomial frequency modulation is used here), 2FSK (binary frequency shift keying), BPSK (binary phase shift keying), QPSK (quadrature phase shift keying), and CW (single carrier). The parameter settings are as follows:

[0082] CW: carrier frequency f0 = 10M, sampling rate fs =120M, signal duration T=10us;

[0083] LFM: carrier frequency f0 = 10M, sampling rate f s =120M, signal bandwidth B=10M, starting frequency f1=10M, signal duration T=10us;

[0084] NLFM: carrier frequency f0 = 10M, f s =120M, signal bandwidth B = 10M, starting frequency f1 = 10M, signal duration T = 10us, and cubic polynomial parameter k1 = 0.4*10 12 , k2=0.6*10 17 ;

[0085] 2FSK: carrier frequency f0 = 10M, frequency offset 5M, f s =120M, 13-bit Barker code, code element T b =1us;

[0086] BPSK: carrier frequency f0 = 10M, f s =120M, 13-bit Barker code, code element T b =1us;

[0087] QPSK: carrier frequency f0 = 10M, f s =120M, 16-bit FRANK code, T b =1us;

[0088] When the signal-to-noise ratio is 10dB, the frequency winding distribution diagram is as follows:

[0089] like Figure 6 , Figure 7 , Figure 8 , Fig. 9 , Fig.10 as well as Fig.11 As shown in the figure above, it can be seen that in the case of frequency warping, the warping frequency characteristics of each modulation method are very obvious, and various modulation methods can be easily distinguished. Among them, the QPSK signal has two typical peaks with very different sizes; the BPSK signal has a peak with little difference; 2FSK has a rectangular feature, and peaks appear at both ends of the rectangle; the warping frequency of the CW signal fluctuates around a constant value; the LFM signal has a typical equidistant broken line; the broken line spacing of NLFM (cubic polynomial frequency modulation) is getting smaller and smaller.

[0090] In view of the fact that the unwarping of the multiple phase difference method is particularly sensitive to noise and the multiplicity or order of the instantaneous autocorrelation algorithm should not be too large, this embodiment proposes the concept of frequency warping on the basis of the instantaneous autocorrelation algorithm, breaking through the limitation of too small order and directly setting the order to be very large, thereby improving the anti-noise performance of the algorithm, and new and different digital features appear in typical modulated signals, which can be effectively distinguished. The multiplicity setting breaks through the limitation of the traditional instantaneous autocorrelation method; for LFM signals, the order setting can be appropriately increased, and the more the order, the more obvious the broken line feature. This algorithm breaks through the limitation of the traditional multiplicity setting being too small and uses the frequency warping that occurs for modulation identification. For LFM signals, the multiplicity setting can be appropriately increased so that the typical equidistant frequency broken line features appear for identification.

[0091] Embodiment 2

[0092] This embodiment provides a modulation recognition system for frequency warping beyond order limitation, including:

[0093] A signal sampling module is configured to acquire and sample radar signals to obtain radar analysis signals;

[0094] A frequency warping module is configured to perform frequency warping based on the radar analysis signal to obtain a warping frequency of the radar analysis signal;

[0095] The modulation identification module is configured to perform modulation identification according to the wrapping frequency of the radar analysis signal.

[0096] Furthermore, in the signal sampling module, the radar signal is acquired and sampled to obtain the radar analysis signal, specifically:

[0097] The radar analysis signal obtained after the radar signal is sampled is:

[0098]

[0099] Where A is the amplitude, f(n) is the frequency modulation function of the signal, is the phase modulation function, is the initial phase, f s is the sampling frequency.

[0100] Furthermore, in the frequency warping module, frequency warping is performed based on the radar analysis signal, specifically:

[0101]

[0102] Where multi is the order and multi>>2, conj[] means taking the conjugate of the signal, and angle() means taking the angle of the complex number, which ranges from (-π,π].

[0103] The examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the contents disclosed in the above embodiment 1. It should be noted that the above modules as part of the system can be executed in a computer system such as a set of computer executable instructions.

[0104] The description of each embodiment in the above embodiments has different emphases. For parts not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0105] The proposed system can be implemented in other ways. For example, the system embodiment described above is only illustrative, and the division of the modules is only a logical function division. In actual implementation, there may be other division methods, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed.

[0106] Embodiment 3

[0107] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the modulation identification method for frequency warping beyond the order limitation described in the first embodiment are implemented.

[0108] Embodiment 4

[0109] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of a modulation identification method for frequency warping beyond order limitation as described in the first embodiment above are implemented.

[0110] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0111] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0112] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0113] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0114] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0115] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A modulation recognition method for frequency warping beyond order limitation, characterized in that: include: Acquire radar signals and perform sampling to obtain radar analysis signals; Perform frequency warping based on the radar analysis signal to obtain a warping frequency of the radar analysis signal; Modulation recognition is performed based on the convolution frequency of the radar analysis signal.

2. A modulation identification method for frequency warping beyond order limitation as claimed in claim 1, characterized in that: The radar signal is acquired and sampled to obtain a radar analysis signal, specifically: The radar analysis signal obtained after the radar signal is sampled is: Where A is the amplitude, f(n) is the frequency modulation function of the signal, is the phase modulation function, is the initial phase, f s is the sampling frequency.

3. A modulation identification method for frequency warping beyond order limitation as claimed in claim 1, characterized in that: The frequency warping based on the radar analysis signal is specifically as follows: Where multi is the order and multi>>2, conj[] means taking the conjugate of the signal, and angle() means taking the angle of the complex number, which ranges from (-π,π].

4. A modulation identification method for frequency warping beyond order limitation as claimed in claim 1, characterized in that: The modulation identification is performed according to the wrapping frequency of the radar analysis signal, specifically: The wrapping frequency of the radar resolution signal is used as the distinguishing feature; Distinguish the modulation types of different radar signals; Get the modulation type of the radar signal.

5. A modulation recognition system for frequency warping beyond order limitation, characterized in that: include: A signal sampling module is configured to acquire and sample radar signals to obtain radar analysis signals; A frequency warping module is configured to perform frequency warping based on the radar analysis signal to obtain a warping frequency of the radar analysis signal; The modulation identification module is configured to perform modulation identification according to the wrapping frequency of the radar analysis signal.

6. A modulation recognition system for frequency warping beyond order limitation as claimed in claim 5, characterized in that: In the signal sampling module, the radar signal is acquired and sampled to obtain the radar analysis signal, specifically: The radar analysis signal obtained after the radar signal is sampled is: Where A is the amplitude, f(n) is the frequency modulation function of the signal, is the phase modulation function, is the initial phase, f s is the sampling frequency.

7. A modulation recognition system for frequency warping beyond order limitation as claimed in claim 5, characterized in that: In the frequency warping module, frequency warping is performed based on the radar analysis signal, specifically: Where multi is the order and multi>>2, conj[] means taking the conjugate of the signal, and angle() means taking the angle of the complex number, which ranges from (-π,π].

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of a modulation identification method for frequency warping beyond order limitation as claimed in any one of claims 1 to 4 are implemented.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the modulation identification method of frequency warping beyond order limitation as described in any one of claims 1 to 4 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of a modulation identification method for frequency warping beyond order limitation as claimed in any one of claims 1 to 4 are implemented.

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