CN114268526B - BPSK and QPSK signal modulation identification method based on degree characteristics of graph - Google Patents
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Abstract
Aiming at the recognition problem of two modulation signals, namely BPSK and QPSK, the invention provides a modulation recognition method of the BPSK and QPSK signals based on the degree characteristics of the graph. Firstly, square spectrums of signals to be identified are obtained, and then rectangular windows are added to obtain truncated square spectrums. And then, carrying out domain conversion on the truncated square spectrum, taking the sum of the vertex degrees of the graph as identification statistics, setting a proper threshold, and comparing the identification statistics with the threshold to realize modulation identification of BPSK and QPSK signals. Simulation results show that the invention can more effectively identify BPSK and QPSK modulation signals under the condition of low signal-to-noise ratio, and the algorithm complexity is lower because the number of the input signal points of the graph conversion is less.
Description
Technical Field
The invention belongs to the field of signal identification and processing, and particularly relates to a BPSK and QPSK signal modulation identification method based on the degree characteristics of a graph.
Background
The modulation mode identification of radar and communication signals is widely applied to the military and civil fields. In the military field such as electronic warfare, signal modulation mode identification is an important precondition for acquiring enemy radar performance parameters; in the civil field, on the premise of limited wireless communication channel resources, the receiving end can realize the identification of the modulation mode of the signal, so that the channel can be saved to a greater extent. BPSK and QPSK signals are the two most commonly used phase-coded modulated signals in radar signals.
In recent years, a new graph-based signal processing algorithm has been widely used in signal processing and the like. In particular, kun Yan et al in 2017 proposed a processing algorithm (Yan K, wu H C, xiao H, et al, new robustband-Limited Signal Detection Approach Using Graphs J IEEE Communications Letters, 2017) for converting a time-series signal into a graph topology, the main idea of the algorithm being to change noise into a complete graph and to convert a noisy signal into an incomplete graph to detect the complete connectivity of the graph to realize the detection of the presence or absence of a signal. If it is applied in signal modulation recognition in accordance with this framework, it is necessary to change one of the time domain or other transform domain forms of the BPSK or QPSK signal into a noise form and the other into a non-noise form. One of the possible ideas is: after the BPSK signal and the QPSK signal are subjected to square operation, a plurality of larger values are removed, so that respective square correction spectrums can be obtained, the square correction spectrums are respectively converted into a complete graph and an incomplete graph, and the modulation recognition problem can be converted into a complete graph detection problem. However, since the larger spectral line contains most of the information of the signal component, the processing will lose the important information, which results in poor performance when the signal-to-noise ratio is low. In addition, the elimination of many such large spectral lines is itself a difficult technical problem.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a BPSK and QPSK signal modulation identification method based on the degree characteristics of a graph. The method carries out graph conversion on the truncated square spectrum, selects specific characteristic quantity and threshold, completes identification of BPSK and QPSK modulation signals, has low algorithm calculation complexity and higher identification accuracy at low signal-to-noise ratio.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the BPSK and QPSK signal modulation identification method based on the degree characteristics of the graph is characterized by comprising the following steps:
step 1: calculating the square spectrum of the signal to be identified;
step 2: taking the peak spectrum line of the square spectrum as a central spectrum line, and adding a rectangular window to obtain a truncated square spectrum;
step 3: performing graph conversion on the truncated square spectrum, and extracting the sum of all vertex degrees of the graph as an identification characteristic quantity;
step 4: setting a corresponding threshold;
step 5: and comparing the identification characteristic quantity with a set threshold to further identify the BPSK signal and the QPSK signal.
In order to optimize the technical scheme, the specific measures adopted further comprise:
further, in step 1, let the signal to be identified be x (n), square it and DFT transform, square the spectrum modulo square to obtain a square spectrum, denoted as Y (k) = (|dft [ x ] 2 (n)]|) 2 K=0, 1,..n-1, where N is the number of samples of the signal.
Further, in step 2, for the square spectrum Y (k), the peak spectral line position of the square spectrum is found to be k=k max Where k represents the line position, k max Representing peak line position, the length of the rectangular window is set to be 2d, and k=k max And (3) taking the peak spectrum line as a center and windowing to obtain:
the number of points with 0 in Y '(k) is deleted to obtain a truncated square spectrum with B (m) =Y' (k), and m is more than or equal to 0 and less than or equal to 2d.
Further, when the number of sample points N of the signal is 1024, d takes 50.
Further, the step 3 specifically includes the following steps:
step 3.1: normalizing the truncated square spectrum B (m) to obtain a normalized spectrum thereof:
setting a quantization level q, and uniformly quantizing the normalized frequency spectrum, namely when i/q is less than B' (m) and less than i+1/q, i is more than or equal to 0 and less than or equal to q-1, wherein the quantized frequency spectrum is U (m) =i+1;
converting U (m) to the graph domain, constructing graph G (V, E), wherein the set of vertices V of the graph represent a mapping of quantization levels {1,2,..q } v= { V 1 ，v 2 ，...v q -a }; edge set e= { E of graph α，β |ν α ∈V，ν β ∈V}，e α，β Representing an edge between two vertices of the graph; the specific practice of constructing the graph G (V, E) is: for each quantized sample U (m), traversing the level relation of the quantized sample U (m) and U (m+1) one by one, when v exists α To v β When the level of (a) jumps, two vertexes are connected, e α，β =1; otherwise, there is no connection between two vertices, e α，β ＝0；
Step 3.2: calculating a degree matrix D of G (V, E), and extracting a degree vector d= (D) of a diagonal element constituting a graph thereof 1 ，d 2 ，...，d j ，...，d q ) Wherein d is j The sum (d) of the degree is calculated as the sum of the numbers of edges connected to the jth vertex.
Further, in step 4, a recognition threshold λ of BPSK and QPSK signals is set evt When the number of sample points N of the signal is 1024 and the number of the graph vertexes is 10, lambda evt Taking 10.
Further, in step 5, if the identification feature is smaller than the set threshold, the signal is a BPSK modulated signal; otherwise, the signal is QPSK modulated.
The beneficial effects of the invention are as follows: the invention performs graph conversion after properly windowing the square spectrum of the observed signal, and completes the identification of the BPSK signal and the QPSK signal according to the degree matrix of the graph and the identification characteristic quantity, wherein the square spectrum is directly utilized, the correction process of removing the large value is not needed, and the information of the signal component can be well reserved. Compared with the traditional correction spectrum-based recognition algorithm, the method directly carries out domain transformation on the power spectrums of the squares of the two types of signals, effectively saves the main information of the signals, can effectively recognize BPSK and QPSK signals under the condition of low signal-to-noise ratio, is less influenced by parameter variation, has certain robustness and has higher algorithm efficiency. In addition, the method is different from the existing recognition processing algorithm based on complete graph detection, analyzes the difference of signals from the angle of random graph theory, defines the graph domain characteristics, further expands the application field of the existing graph domain processing method, and enriches the processing means of the method.
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FIG. 1 is a flow chart of an identification method of the present invention.
Fig. 2 shows the average of the sum of the degrees of the truncated square spectrum generation map of BPSK and QPSK signals at different signal-to-noise ratios.
Detailed Description
The invention will now be described in further detail with reference to the accompanying drawings.
Fig. 1 is a flowchart of a BPSK and QPSK signal modulation identification method based on the degree characteristics of the graph. Firstly, square spectrums of signals to be identified are obtained, and then the square spectrums are windowed to obtain truncated square spectrums. Then, the modulation identification is converted into a graph domain, the sum of the graph degree is used as an identification statistic, an appropriate threshold is set, and the identification statistic is compared with the threshold to realize modulation identification of BPSK and QPSK signals. Simulation results show that under the condition of no signal priori information, the invention can identify two modulation signals of BPSK and QPSK. The BPSK and QPSK signal modulation identification method based on the degree characteristics of the graph specifically comprises the following steps:
the number of points with 0 in Y '(k) is deleted to obtain a truncated square spectrum with B (m) =Y' (k), and m is more than or equal to 0 and less than or equal to 2d.
And 3, carrying out graph conversion on the truncated square spectrum, and extracting the sum of all vertex degrees of the graph as an identification characteristic quantity, wherein the method comprises the following specific steps of:
step 3.1, graph conversion: normalizing the truncated square spectrum B (m) to obtain a normalized spectrum thereof:
setting a quantization level q, and uniformly quantizing the quantization level q, wherein when i/q is less than B (m) < i+1/q, i is more than or equal to 0 and less than or equal to q-1, the quantized frequency spectrum is U (m) =i+1;
finally, U (m) is converted to the graph domain, constituting a graph G (V, E), where the set of vertices V of the graph is a mapping of the quantization levels {1, 2..q }, i.e. v= { V 1 ，ν 2 ，...v q -a }; edge set e= { E of graph α，β |v α ∈V，ν β E V }. The specific practice of constructing the graph G (V, E) is: for each quantized sample U (m), traversing the level relation of the quantized sample U (m) and U (m+1) one by one, when v exists α To v β When the level of (a) jumps, then the two vertices are connected, i.e α，β =1; otherwise, there is no connection between the two vertices, i.e. e α，β ＝0；
Step 3.2, extracting identification feature quantity: calculating a degree matrix D of G (V, E), and extracting a degree vector d= (D) of a diagonal element constituting a graph thereof 1 ，d 2 ，...，d j ，...，d q ) Wherein d is j The sum (d) of the degree is calculated as the sum of the numbers of edges connected to the jth vertex.
And step 5, comparing the identification characteristic quantity with a threshold to identify BPSK and QPSK signals. When sum (d) < lambda evt And when the signal is a BPSK modulation signal; otherwise, the signal is QPSK modulated.
Table 1 shows the identification performance of BPSK/QPSK signals under different signal-to-noise ratios, and the simulation conditions are: the signal-to-noise ratio is [ -6, -4, -2,0,2,4,6,8], the sampling frequency is 100MHz, the carrier frequency is 20.76MHz, the code element width is 640ns, the number of sample points is 1024, the initial phase is pi/4, the length of a rectangular window is 100, the number of peaks of the graph is 10, and the simulation is 1000 times under each condition. As can be seen from Table 1, when the signal-to-noise ratio is greater than-4 dB, the average recognition accuracy can reach more than 95%.
TABLE 1 identification performance of BPSK/QPSK signals under different signal-to-noise ratios
The graph generated by graph conversion of the truncated square spectrum extracted from the BPSK signal has no connected component of a certain scale (total number of vertices is greater than 10), and the graph generated by graph conversion of the truncated square spectrum extracted from the QPSK signal has a connected component of a certain scale. The magnitude of the sum of the degrees of the generated graph may characterize whether the graph has connected components of a certain scale. Fig. 2 is a mean value of the sum of the degrees of the truncated square spectrum generation graphs of BPSK and QPSK signals under different signal-to-noise ratios, and can be used to realize modulation identification of BPSK/QPSK signals.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to the invention without departing from the principles thereof are intended to be within the scope of the invention as set forth in the following claims.
Claims (6)
1. The BPSK and QPSK signal modulation identification method based on the degree characteristics of the graph is characterized by comprising the following steps:
step 1: calculating the square spectrum of the signal to be identified;
step 2: taking the peak spectrum line of the square spectrum as a central spectrum line, and adding a rectangular window to obtain a truncated square spectrum; in step 2, for the square spectrum Y (k), the peak line position of the square spectrum is found to be k=k max Where k represents the line position, k max Representing peak line position, the length of the rectangular window is set to be 2d, and k=k max And (3) taking the peak spectrum line as a center and windowing to obtain:
the point number with 0 in Y '(k) is deleted to obtain a truncated square spectrum of B (m) =Y' (k), wherein m is more than or equal to 0 and less than or equal to 2d;
step 3: performing graph conversion on the truncated square spectrum, and extracting the sum of all vertex degrees of the graph as an identification characteristic quantity;
step 4: setting a corresponding threshold;
step 5: and comparing the identification characteristic quantity with a set threshold to further identify the BPSK signal and the QPSK signal.
2. The BPSK and QPSK signal modulation identification method based on the degree characteristics of the map as set forth in claim 1, wherein: in step 1, let the signal to be identified be x (n), square it and DFT transform, square the spectrum modulus to obtain square spectrum, and record as Y (k) = (|dft [ x ] 2 (n)]|) 2 K=0, 1,..n-1, where N is the number of samples of the signal.
3. The BPSK and QPSK signal modulation identification method based on the degree characteristics of the map as set forth in claim 1, wherein: when the number of sample points N of the signal is 1024, d takes 50.
4. The BPSK and QPSK signal modulation identification method based on the degree characteristics of the map as set forth in claim 1, wherein: the step 3 specifically comprises the following steps:
step 3.1: normalizing the truncated square spectrum B (m) to obtain a normalized spectrum thereof:
setting a quantization level q, and uniformly quantizing the normalized frequency spectrum, wherein when iq is less than B' (m) and less than i+1q, i is more than or equal to 0 and less than or equal to q-1, the quantized frequency spectrum is U (m) =i+1;
converting U (m) to the graph domain, constructing graph G (V, E), wherein the set of vertices V of the graph represent a mapping of quantization levels {1,2,..q } v= { V 1 ,v 2 ,...v q -a }; edge set e= { E of graph α,β |ν α ∈V,ν β ∈V}，e α,β Representing an edge between two vertices of the graph; the specific practice of constructing the graph G (V, E) is: for each quantized sample U (m), traversing the level relation of the quantized sample U (m) and U (m+1) one by one, when v exists α To v β When the level of (a) jumps, two vertexes are connected, e α,β =1; otherwise, there is no connection between two vertices, e α,β ＝0；
Step 3.2: calculating a degree matrix D of G (V, E), and extracting a degree vector d= (D) of a diagonal element constituting a graph thereof 1 ,d 2 ,...,d j ,...,d q ) Wherein d is j The sum (d) of the degree is calculated as the sum of the numbers of edges connected to the jth vertex.
5. The BPSK and QPSK signal modulation identification method based on the graph degree feature according to claim 2, wherein: in step 4, a recognition threshold lambda of BPSK and QPSK signals is set evt When the number of sample points N of the signal is 1024 and the number of the graph vertexes is 10, lambda evt Taking 10.
6. The BPSK and QPSK signal modulation identification method based on the degree characteristics of the map as set forth in claim 1, wherein: in step 5, if the identification feature is smaller than the set threshold, the signal is a BPSK modulated signal; otherwise, the signal is QPSK modulated.
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