High-precision power measurement method for digital modulation communication signal

Abstract

The invention discloses a high-precision power measurement method for a digital modulation communication signal, and belongs to the technical field of communication reconnaissance, and the method comprises the steps: collecting an intermediate frequency signal, guiding the down-conversion decimation filtering of a single signal according to the frequency bandwidth of the intermediate frequency signal, and obtaining the baseband IQ data of the single signal; identifying the intermediate frequency signal modulation pattern according to the baseband IQ data, and judging the category of the intermediate frequency signal; according to the category of the intermediate frequency signal, multiple square spectrum calculations of the intermediate frequency signal are completed; performing signal energy statistics on multiple square spectrum maximum value points of the intermediate frequency signal to obtain relative signal power; and calculating accurate signal power according to the maximum value of the multiple square spectrums and the relative signal power. According to the invention, high-precision measurement of communication signal power in a large signal-to-noise ratio range can be realized.

Description

Technical Field

[0001] The invention belongs to the technical field of communication reconnaissance, and in particular relates to a high-precision power measurement method for digitally modulated communication signals. Background Art

[0002] The signal power of the communication radiation source is an important one-dimensional descriptive parameter of the target object. In the field of communication reconnaissance, high-precision measurement of the power of the communication radiation source signal can assist the system in deriving various reconnaissance applications and has strong military application value.

[0003] Existing power measurement methods for communication signals are generally based on time domain or frequency domain energy statistics of intercepted signals.

[0004] There are several shortcomings in time-domain based signal power measurement:

[0005] (1) Time domain statistics can only be applied to a single signal after filtering;

[0006] (2) The measurement accuracy is dependent on the in-band fluctuation and out-of-band suppression characteristics of the filter;

[0007] (3) After the signal-to-noise ratio is reduced, the measurement result is the sum of the signal and noise power, which cannot correctly reflect the actual signal power.

[0008] The problems with measuring signal power based on frequency domain are:

[0009] (1) There is a measurement error in the 3dB bandwidth parameter measurement of digital signals, which leads to fluctuations in the in-band power statistics;

[0010] (2) The grid effect of FFT transformation has a great influence on the power measurement of narrowband signals;

[0011] (3) After the signal-to-noise ratio is reduced, the signal power measurement value in the frequency domain is still the sum of the signal and noise power, which cannot correctly reflect the actual signal power.

[0012] In view of the actual engineering application of the existing technology, the accuracy of the communication signal power measurement method based on time domain or frequency domain is 1 to 1.5 dB. At the same time, due to the defects of the measurement principle, the power measurement result has a certain nonlinear phenomenon under the condition of low signal-to-noise ratio. Summary of the invention

[0013] The purpose of the present invention is to overcome the defects of the prior art and provide a high-precision power measurement method for digital modulated communication signals. The method aims to achieve high-precision measurement of communication signal power within a large signal-to-noise ratio range by adopting a low-complexity method for digital modulated (BPSK\QPSK\8PSK\16QAM, etc.) signals in a blind reconnaissance situation.

[0014] The object of the present invention is achieved through the following technical solutions:

[0015] A high-precision power measurement method for a digitally modulated communication signal, the method comprising:

[0016] Collecting an intermediate frequency signal, guiding the down-conversion extraction and filtering of a single signal according to the frequency bandwidth of the intermediate frequency signal, and obtaining baseband IQ data of the single signal;

[0017] Identify the modulation pattern of the intermediate frequency signal according to the baseband IQ data, and determine the category to which the intermediate frequency signal belongs;

[0018] According to the category to which the intermediate frequency signal belongs, a multi-dimensional spectrum calculation of the intermediate frequency signal is completed;

[0019] Performing signal energy statistics on multiple maximum points of the square spectrum of the intermediate frequency signal to obtain relative signal power;

[0020] The accurate signal power is calculated based on the multi-square spectrum maximum value and the relative signal power.

[0021] Further, the determining the category to which the intermediate frequency signal belongs includes:

[0022] Calculate the instantaneous amplitude fluctuation rate of the signal, and determine the coarse category of the intermediate frequency signal according to a first preset threshold, wherein the coarse category includes BPSK\16QAM and QPSK\8PSK;

[0023] The instantaneous phase of the signal is calculated, and the instantaneous phase jump of the signal is obtained. According to the instantaneous phase jump of the signal and the second preset threshold, the sub-category of the intermediate frequency signal is determined, and the sub-category includes BPSK, 16QAM, QPSK and 8PSK.

[0024] Furthermore, judging the detailed category of the intermediate frequency signal according to the instantaneous phase jump of the signal and the second preset threshold specifically includes:

[0025] The signal phase jump range distribution is obtained based on a histogram statistical method, and the detailed category of the intermediate frequency signal is determined according to the phase jump range distribution in the histogram.

[0026] Furthermore, the step of completing the multi-dimensional spectrum calculation of the intermediate frequency signal according to the category to which the intermediate frequency signal belongs specifically includes:

[0027] The BPSK signal completes a second spectrum calculation, the QPSK or 16QAM signal completes a fourth spectrum calculation, and the 8PSK signal completes an eighth spectrum calculation.

[0028] Furthermore, the method further includes judging the validity of the multi-power spectrum maximum point:

[0029] The ratio of the multi-power spectrum maximum to the spectrum mean within a preset range is calculated, and when the ratio is greater than a preset first ratio threshold, it is determined to be valid.

[0030] Furthermore, the performing signal energy statistics on the multi-spectrum maximum points of the intermediate frequency signal specifically includes:

[0031] The energy of the maximum point and the points adjacent to the maximum point on both sides is statistically calculated as the relative statistical result of the signal energy.

[0032] The beneficial effects of the present invention are:

[0033] (1) The present invention uses the cyclostationary characteristics of digital modulated signals and the modulation pattern recognition results to find multi-dimensional spectrum features in the signal transformation domain for high-precision power measurement. The estimation accuracy is improved by more than one order of magnitude compared with traditional time domain and frequency domain algorithms.

[0034] (2) The present invention can be adapted to accurately estimate signal power under low signal-to-noise ratio conditions, and completely avoids the nonlinear defects in traditional time-domain and frequency-domain power estimation algorithms. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a flowchart of a high-precision power measurement method for digitally modulated communication signals according to an embodiment of the present application;

[0036] Figure 2 This is a distribution diagram of instantaneous amplitude fluctuation rate of signals of different modulation types in the embodiment of the present application;

[0037] Figure 3 This is a schematic diagram of the fourth spectrum of the QPSK signal in the embodiment of the present application;

[0038] Figure 4 This is a schematic diagram of the secondary spectrum of the BPSK signal in an embodiment of the present application;

[0039] Figure 5 It is a schematic diagram of the secondary spectrum of a 0.5 MHz frequency offset BPSK signal in an embodiment of the present application. DETAILED DESCRIPTION

[0040] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0041] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0042] In view of the actual engineering application of the existing technology, the accuracy of the communication signal power measurement method based on time domain or frequency domain is 1 to 1.5 dB. At the same time, due to the defects of the measurement principle, the power measurement result has a certain nonlinear phenomenon under the condition of low signal-to-noise ratio.

[0043] In order to solve the above technical problems, the following embodiments of a high-precision power measurement method for digitally modulated communication signals are proposed in the present invention.

[0044] Reference Figure 1 ,like Figure 1 The figure is a flowchart of a high-precision power measurement method for a digitally modulated communication signal according to an embodiment of the present application. The method specifically comprises the following steps:

[0045] Step 1: Target signal acquisition and preprocessing to remove the influence of irrelevant signals and noise on this algorithm. The intermediate frequency signal is acquired through AD, the power spectrum is calculated, and the rough distribution of signals within the reconnaissance range is obtained through conventional frequency domain multi-signal search. The down-conversion extraction and filtering of a single signal is guided according to the signal frequency bandwidth to obtain the baseband IQ data of a single signal;

[0046] Step 2: Complete the communication signal modulation type identification to provide guidance information for multi-square spectrum calculation. Based on the baseband IQ data of the signal, calculate the instantaneous amplitude fluctuation rate R of the signal, where R is the normalized variance of the signal envelope. The calculation formula is as follows, where r(t) = abs(s(t)), which is the instantaneous envelope of the signal:

[0047] R=var(r(t)) / mean(r(t))^2

[0048] The difference in amplitude fluctuation rate of each digital modulation signal is shown below Figure 1 By setting the classification threshold reasonably, the signal can be classified into two categories: BPSK\16QAM and QPSK\8PSK; the instantaneous phase of the signal is calculated, and the instantaneous phase jump of the signal is obtained. The phase jump range distribution of the signal is obtained based on the histogram statistics method (the phase jump between BPSK signal symbols is 180°, and the phase jump distribution between 16QAM signal symbols is relatively scattered; the phase jump between QPSK signal symbols is 180° and 90°, while 8PSK is relatively scattered). By setting the classification threshold reasonably, the further identification of BPSK\16QAM and QPSK\8PSK signals can be completed.

[0049] The common digital modulation baseband model can generally be expressed as

[0050]

[0051] Where (a n +jb n ) represents the information symbol sequence, T is the symbol period, g(t) represents the shaped pulse, the most common of which is the raised cosine pulse.

[0052] Taking the commonly used QPSK modulation signal as an example, its information sequence (a n +jb n ) value set is The statistical expectation of the quartic form of the QPSK signal is

[0053] The expected value is a function with a period of T. Calculating its fourth power spectrum gives

[0054]

[0055] Where A(f) is the result of the fourth convolution of the Fourier transform of g(t).

[0056] It can be seen from V(f) that the maximum value can be obtained at the frequency {0, ±1 / T, ±2 / T}, and this value is related to the signal power. At the same time, the maximum value is linearly related to the fourth power energy of g(t), which greatly improves the signal energy at this point and suppresses the noise energy.

[0057] Reference Figure 2-Figure 4 ,like Figure 2 The figure shows the distribution diagram of instantaneous amplitude fluctuation rate of signals of different modulation types in the embodiment of the present application. Figure 3 The figure shows a schematic diagram of the fourth spectrum of the QPSK signal in the embodiment of the present application. Figure 4 The figure shows a schematic diagram of the secondary spectrum of the BPSK signal in the embodiment of the present application. As can be seen from the figure,

[0058] The frequency value of {0, ±1 / T, ±2 / T} is at least 10dB higher than the other frequency components of the original signal, and the frequency value is easy to detect; secondly, the frequency value is a single-frequency signal, and the statistical signal energy does not need to consider the 3dB bandwidth problem, and the energy statistics are accurate. Considering that the general non-cooperative reconnaissance baseband signal has a residual frequency offset Δf, the frequency maximum value appears at {2Δf, 2Δf±1 / T, 2Δf±2 / T}, refer to Figure 5 ,like Figure 5 Shown is a schematic diagram of the secondary spectrum of a 0.5 MHz frequency offset BPSK signal in an embodiment of the present application, with a residual frequency of 0.5 MHz and a sampling rate of 5 MHz.

[0059] Step 3: Calculate different types of multi-dimensional spectra of baseband IQ data based on the signal modulation type information. The BPSK signal completes the quadratic spectrum calculation, the QPSK\16QAM signal completes the quadratic spectrum calculation, and the 8PSK signal completes the octa-spectrum calculation.

[0060] Step 4: Utilize the accumulation effect of the signal at positions {0, ±1 / T, ±2 / T} in the frequency domain after multiple power transformations to complete the energy statistics of the spectrum maximum points and obtain high-precision relative statistical results of the signal power.

[0061] Due to the large error in the signal frequency measurement in step 1, the maximum spectrum peak of the multi-order spectrum data does not necessarily appear at zero frequency. For the N-order spectrum, the spectrum peak appears at {NΔf, NΔf±1 / T, NΔf±2 / T}, so for the multi-order spectrum data, it is necessary to complete the search for the maximum spectrum value. In order to improve the reliability of peak judgment, the ratio of the peak value to the nearby spectrum mean can be calculated. The ratio greater than 8dB is considered to be a valid peak.

[0062] Signal multi-power calculation is equivalent to transforming the signal into a single-tone signal. In order to avoid the energy dispersion caused by the grid effect of FFT in the spectrum calculation of single-tone signal, this method needs to count the energy sum of the peak point and the adjacent points on the left and right as the relative statistical result of the signal energy.

[0063] Step 5: Based on the maximum energy and signal power of the signal multi-power spectrum The relationship is linear, the fixed power deviation is removed, and the accurate power of the signal is calculated.

[0064] Since the statistical value of signal energy in the digital processing result is related to many factors such as the shaping filter g(t) at the transmitting end, the number of AD quantization bits at the receiving end, and the down-conversion DDC processing gain, it is difficult to obtain it through theoretical deduction. In engineering implementation, it is recommended to obtain it through multiple measurement statistics as a fixed deviation, and correct the signal energy measurement value in the final result to deduce the absolute power of the signal.

[0065] This embodiment uses the cyclostationary characteristics of digital modulation signals and the modulation pattern recognition results to find multi-square spectrum features in the signal transformation domain for high-precision power measurement, and the estimation accuracy is improved by more than one order of magnitude compared with the traditional time domain and frequency domain algorithms. This method can adapt to the accurate estimation of signal power under low signal-to-noise ratio conditions and completely avoid the nonlinear defects in traditional time domain and frequency domain power estimation algorithms.

[0066] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A high-precision power measurement method for digitally modulated communication signals, characterized in that: The method comprises: Collecting an intermediate frequency signal, guiding the down-conversion extraction and filtering of a single signal according to the frequency bandwidth of the intermediate frequency signal, and obtaining baseband IQ data of the single signal; Identify the modulation pattern of the intermediate frequency signal according to the baseband IQ data, and determine the category to which the intermediate frequency signal belongs; According to the category to which the intermediate frequency signal belongs, a multi-dimensional spectrum calculation of the intermediate frequency signal is completed; Performing signal energy statistics on multiple maximum points of the square spectrum of the intermediate frequency signal to obtain relative signal power; The accurate signal power is calculated based on the multi-square spectrum maximum value and the relative signal power.

2. The high-precision power measurement method for digitally modulated communication signals according to claim 1, characterized in that: The determining the category to which the intermediate frequency signal belongs comprises: Calculate the instantaneous amplitude fluctuation rate of the signal, and determine the coarse category of the intermediate frequency signal according to a first preset threshold, wherein the coarse category includes BPSK\16QAM and QPSK\8PSK; The instantaneous phase of the signal is calculated, and the instantaneous phase jump of the signal is obtained. According to the instantaneous phase jump of the signal and the second preset threshold, the sub-category of the intermediate frequency signal is determined, and the sub-category includes BPSK, 16QAM, QPSK and 8PSK.

3. The high-precision power measurement method for digitally modulated communication signals according to claim 2, characterized in that: The method of determining the detailed category of the intermediate frequency signal according to the instantaneous phase jump of the signal and the second preset threshold specifically includes: The signal phase jump range distribution is obtained based on a histogram statistical method, and the detailed category of the intermediate frequency signal is determined according to the phase jump range distribution in the histogram.

4. The high-precision power measurement method for digitally modulated communication signals according to claim 2, characterized in that: The step of completing the multi-spectrum calculation of the intermediate frequency signal according to the category to which the intermediate frequency signal belongs specifically includes: The BPSK signal completes a second spectrum calculation, the QPSK or 16QAM signal completes a fourth spectrum calculation, and the 8PSK signal completes an eighth spectrum calculation.

5. The high-precision power measurement method for digitally modulated communication signals according to any one of claims 1 to 4, characterized in that: The method further includes judging the validity of the multi-spectrum maximum point: The ratio of the multi-power spectrum maximum to the spectrum mean within a preset range is calculated, and when the ratio is greater than a preset first ratio threshold, it is determined to be valid.

6. The high-precision power measurement method for digitally modulated communication signals according to claim 1, characterized in that: The signal energy statistics of the multi-spectrum maximum points of the intermediate frequency signal specifically include: The energy of the maximum point and the points adjacent to the maximum point on both sides is statistically calculated as the relative statistical result of the signal energy.

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