CN108900445B - Method and device for estimating signal symbol rate - Google Patents
Method and device for estimating signal symbol rate Download PDFInfo
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- CN108900445B CN108900445B CN201811001360.8A CN201811001360A CN108900445B CN 108900445 B CN108900445 B CN 108900445B CN 201811001360 A CN201811001360 A CN 201811001360A CN 108900445 B CN108900445 B CN 108900445B
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Abstract
The application discloses a method for estimating a signal symbol rate, which comprises the following steps: receiving a first signal for the firstSampling the signal to obtain a second signal; selecting a target signal from the second signal; estimating a first carrier frequency and a first bandwidth of a target signal; downconverting a target signal F (j ω) to F (j (ω - ω) in the frequency domain based on a first carrier frequencys))，ωsIs the first carrier frequency; performing low-pass filtering on the down-converted signal according to the first bandwidth to obtain a first low-pass signal; preprocessing the first low-pass signal to obtain a third signal; performing band-pass filtering on the third signal to obtain a first band-pass signal; carrying out nonlinear transformation on the first bandpass signal to obtain a spectrogram, wherein the spectrogram is a frequency domain representation after the nonlinear transformation of the first bandpass signal; acquiring the position of a peak spectral line in a spectral line graph; and estimating the symbol rate of the first bandpass signal according to the position of the peak spectral line. The scheme can improve the estimation accuracy of the signal symbol rate.
Description
Technical Field
The present invention relates to the field of communication technologies and signal processing technologies, and in particular, to a method and an apparatus for estimating a symbol rate of a signal.
Background
With the rapid development of computer technology and communication technology, new communication modes and systems are proposed to adapt to the increasing communication services and the types thereof, and a great research hotspot is brought forward. As a new communication mode, short-time burst communication is focused and researched by more and more researchers due to the characteristics of low interception rate, strong anti-interference performance, low power loss, high channel utilization rate and the like.
Before digital modulation, in order to avoid intersymbol interference caused by frequency domain radio expansion of a digital baseband signal, a raised cosine or a root raised cosine is generally required to be used for symbol shaping of the signal. This property is commonly used for modulation scheme identification and parameter estimation in uncooperative communications. The symbol rate is an important parameter of the digital modulation signal, and accurate estimation of the symbol rate is an important precondition for realizing effective reconnaissance of the measurement and control signal. In the digital modulation scheme, the symbol rate refers to the number of transmission symbols per unit time. For a non-cooperative receiver, accurate estimation of the symbol rate has direct influence on subsequent links such as filter bandwidth design, sampling rate conversion, timing synchronization and the like.
The computational complexity of the symbol rate estimation method based on the envelope square spectrum is much less than that of the symbol rate estimation method based on the cyclic spectrum. At present, under 10dB (symbol signal to noise ratio), at least 500 symbols are required for multilevel digital phase Modulation (MPSK) and Multilevel Quadrature Amplitude Modulation (MQAM) signals to estimate the symbol rate. When the acquired signal is a short burst (the number of symbols in each time slot is below 500), the traditional symbol rate estimation method based on the envelope square spectrum can not estimate the symbol rate accurately.
Disclosure of Invention
The application provides a method and a device for estimating a signal symbol rate, which can improve the estimation accuracy of the signal symbol rate.
In a first aspect, an embodiment of the present invention provides a method for estimating a symbol rate of a signal, including:
receiving a first signal, and sampling the first signal to obtain a second signal; selecting a target signal from the second signal; estimating a first carrier frequency and a first bandwidth of a target signal; downconverting a target signal F (j ω) to F (j (ω - ω) in the frequency domain based on a first carrier frequencys))，ωsIs the first carrier frequency; performing low-pass filtering on the down-converted signal according to the first bandwidth to obtain a first low-pass signal; preprocessing the first low-pass signal to obtain a third signal; performing band-pass filtering on the third signal to obtain a first band-pass signal; carrying out nonlinear transformation on the first bandpass signal to obtain a spectrogram, wherein the spectrogram is a frequency domain representation after the nonlinear transformation of the first bandpass signal; acquiring the position of a peak spectral line in a spectral line graph; and estimating the symbol rate of the first bandpass signal according to the position of the peak spectral line.
Under the conditions of low signal-to-noise ratio and no reduction of estimation precision, the embodiment of the invention can realize the improvement of the estimation accuracy of the signal symbol rate.
Preferably, the selecting the target signal from the second signals includes: selecting a signal in a specific frequency band from the second signal as a target signal; or, a threshold value is preset, and a signal with the amplitude larger than the threshold value in a specific frequency band is selected from the second signal as a target signal.
Preferably, estimating the first carrier frequency and the first bandwidth of the target signal comprises: a first carrier frequency and a first bandwidth of the target signal are estimated using a spectral centroid method.
Preferably, whether the first low-pass signal is a burst signal is detected; if the first low-pass signal is a burst signal, acquiring the starting time of a first burst in the first low-pass signal, and intercepting or zero-filling to 2 from the starting time of the first burstnObtaining the third signal by a plurality of data points, wherein n is a positive integer; or, if the first low-pass signal is not a burst signal, truncating or zero-filling the first low-pass signal to 2nAnd obtaining the third signal by a plurality of data points, wherein n is a positive integer.
Preferably, the detecting whether the first low-pass signal is a burst signal includes: carrying out burst signal detection on the first low-pass signal by using a double-sliding-window signal detection algorithm based on an energy detection principle; or, performing burst signal detection on the first low-pass signal by using a preamble unique word-based detection algorithm.
Preferably, the band-pass filtering the third signal to obtain a first band-pass signal includes: and performing band-pass filtering on the third signal to obtain a first band-pass signal, wherein the passband range of the band-pass filtering is [ x, y ], and the values of x and y are determined by the first bandwidth.
Preferably, the nonlinear transformation of the first bandpass signal to obtain the spectral line graph includes: carrying out nonlinear transformation based on the envelope M power spectrum on the first bandpass signal to obtain a spectrum diagram; or, performing nonlinear transformation on the first bandpass signal based on a maximum and minimum linear combination algorithm to obtain a spectral diagram, wherein the maximum and minimum linear combination algorithm is complex vector magnitude estimation and is expressed as 'alpha A + beta B', wherein A is the maximum value in the imaginary part and the real part of the complex vector of the first bandpass signal, B is the minimum value in the imaginary part and the real part of the complex vector of the first bandpass signal, and alpha and beta are greater than or equal to 0.
Preferably, the obtaining of the position of the peak spectral line in the spectral line graph comprises: and acquiring the position of a peak spectral line by performing peak detection on the spectral line graph.
Preferably, after acquiring the position of the peak spectral line in the spectral line diagram, before performing symbol rate estimation on the first bandpass signal according to the position of the peak spectral line, the method further includes: the position of the peak spectral line is corrected.
Preferably, the correcting the position of the peak spectral line includes: and correcting the position of the peak spectral line by utilizing a frequency spectrum peak positioning interpolation algorithm.
Preferably, the estimating the symbol rate of the first bandpass signal according to the position of the peak spectral line includes: and estimating the symbol rate of the first bandpass signal according to the position of the corrected peak spectral line.
In a second aspect, an embodiment of the present invention further provides a device for estimating a symbol rate of a signal, where the device can achieve the functions and beneficial effects of the method for estimating a symbol rate of a signal in the first aspect. The functions of the device can be realized by hardware, and can also be realized by hardware executing corresponding software. The hardware or software includes at least one module corresponding to the above functions.
Preferably, the device comprises a first receiving unit, a signal selecting unit, a parameter estimating unit, a down-conversion unit, a low-pass filtering unit, a preprocessing unit, a band-pass filtering unit, a nonlinear conversion unit, a peak detecting unit and a symbol rate estimating unit. The first receiving unit is used for receiving a first signal and sampling the first signal to obtain a second signal; a signal selection unit for selecting a target signal from the second signal; a parameter estimation unit for estimating a first carrier frequency and a first bandwidth of a target signal; a down-conversion unit for down-converting the target signal F (j omega) into F (j (omega-omega) in the frequency domain according to the first carrier frequencys))，ωsIs the first carrier frequency; the low-pass filtering unit is used for performing low-pass filtering on the down-converted signal according to a first bandwidth to obtain a first low-pass signal; a pre-processing unit for pre-processing the first low-pass signalProcessing to obtain a third signal; the band-pass filtering unit is used for performing band-pass filtering on the third signal to obtain a first band-pass signal; the nonlinear transformation unit is used for carrying out nonlinear transformation on the first bandpass signal to obtain a spectrogram, and the spectrogram is a frequency domain representation after the nonlinear transformation of the first bandpass signal; the peak detection unit is used for acquiring the position of a peak spectral line in the spectral line graph; and the symbol rate estimation unit is used for estimating the symbol rate of the first bandpass signal according to the position of the peak spectral line.
Preferably, the first receiving unit comprises a second receiving unit and a sampling unit. A second receiving unit for receiving the first signal; and the sampling unit is used for sampling the first signal to obtain a second signal.
Preferably, the signal selecting unit is specifically configured to: selecting a signal in a specific frequency band from the second signal as a target signal; or, a threshold value is preset, and a signal with the amplitude larger than the threshold value in a specific frequency band is selected from the second signal as a target signal.
Preferably, the parameter estimation unit is specifically configured to: a first carrier frequency and a first bandwidth of a target signal are roughly estimated using a spectral center of gravity method.
Preferably, the pretreatment unit comprises: the device comprises a burst detection unit, an acquisition unit and a first interception unit, wherein the burst detection unit is specifically used for detecting whether a first low-pass signal is a burst signal; the obtaining unit is specifically configured to obtain a start time of a first burst in the first low-pass signal if the first low-pass signal is a burst signal; the first truncation unit is specifically configured to truncate or zero-fill from the first burst start time to 2nAnd obtaining the third signal by a plurality of data points, wherein n is a positive integer.
Preferably, the pretreatment unit comprises: a burst detection unit, specifically configured to detect whether the first low-pass signal is a burst signal, and a second truncation unit, specifically configured to truncate or zero-fill to 2 the first low-pass signal if the first low-pass signal is not a burst signalnAnd obtaining the third signal by a plurality of data points, wherein n is a positive integer.
Preferably, the burst detection unit is specifically configured to: carrying out burst signal detection on the first low-pass signal by using a double-sliding-window signal detection algorithm based on an energy detection principle; or, performing burst signal detection on the first low-pass signal by using a preamble unique word-based detection algorithm.
Preferably, the band-pass filtering unit is specifically configured to perform band-pass filtering on the third signal to obtain a first band-pass signal, where a passband range of the band-pass filtering is [ x, y ], and a value of x, y is determined by the first bandwidth.
Preferably, the nonlinear transformation unit is specifically configured to: carrying out nonlinear transformation based on the envelope M power spectrum on the first bandpass signal to obtain a spectrum diagram; or, performing nonlinear transformation on the first bandpass signal based on a maximum and minimum linear combination algorithm to obtain a spectral diagram, wherein the maximum and minimum linear combination algorithm is complex vector magnitude estimation and is expressed as 'alpha A + beta B', wherein A is the maximum value in the imaginary part and the real part of the complex vector of the first bandpass signal, B is the minimum value in the imaginary part and the real part of the complex vector of the first bandpass signal, and alpha and beta are greater than or equal to 0.
Preferably, the peak detection unit is specifically configured to perform peak detection on spectral lines in the spectral line graph to obtain peak spectral line positions.
Preferably, the apparatus further includes a correcting unit, configured to correct the position of the peak spectral line before the symbol rate estimating unit performs symbol rate estimation on the first bandpass signal according to the position of the peak spectral line after the peak detecting unit acquires the position of the peak spectral line in the spectral line graph.
Preferably, the symbol rate estimation unit is specifically configured to perform symbol rate estimation on the first bandpass signal according to the position of the corrected peak spectral line.
In a third aspect, an embodiment of the present invention further provides a signal processing apparatus, where the signal processing apparatus is capable of implementing the functions and the advantageous effects of the method for estimating a symbol rate of a signal according to the first aspect. The functions of the signal processing device can be realized by hardware, and can also be realized by hardware executing corresponding software. The hardware or software includes at least one module corresponding to the above functions. The signal processing device comprises a transceiver and a processor, wherein the transceiver is used for receiving signals, and the processor is used for controlling and managing the action of the signal processing device. The signal processing device can be a frequency spectrum monitoring device or a wireless detection instrument and other devices.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, which has instructions stored thereon, and when the instructions are executed on a processor, the processor is caused to execute the method for estimating a signal symbol rate described in the first aspect.
In a fifth aspect, embodiments of the present invention provide a computer program product comprising instructions which, when run on a processor, cause the processor to perform the method for signal symbol rate estimation described in the first aspect above.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below.
Fig. 1 is a schematic structural diagram of a signal processing apparatus according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for symbol rate estimation according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a first signal spectrum according to an embodiment of the present invention;
FIG. 4-a is a schematic diagram of a target signal selection according to an embodiment of the present invention;
FIG. 4-b is a schematic diagram of another target signal selection provided by an embodiment of the present invention;
FIG. 5 is a schematic diagram of bandwidth estimation based on the spectral centroid method according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a first low-pass signal according to an embodiment of the present invention;
FIG. 7 is a schematic block diagram of a dual sliding window signal detection method based on energy detection principle according to an embodiment of the present invention;
FIG. 8-a is a diagram of a normalized autocorrelation burst signal according to an embodiment of the present invention;
FIG. 8-b is a schematic view of a dual sliding window provided by an embodiment of the present invention;
FIG. 8-c is a schematic signal detection diagram of a double sliding window signal detection algorithm based on an energy detection principle according to an embodiment of the present invention;
fig. 9 is a schematic block diagram of detection based on a preamble unique word according to an embodiment of the present invention;
FIG. 10 is a schematic diagram of band-pass filtering provided by an embodiment of the invention;
FIG. 11 is a schematic diagram of an envelope squared spectrum provided by an embodiment of the present invention;
FIG. 12 is a schematic diagram of a spectral peak location interpolation algorithm according to an embodiment of the present invention;
fig. 13 is a schematic structural diagram of an apparatus for estimating a symbol rate of a signal according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It is to be understood that the terminology used in the embodiments of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
The method for estimating the signal symbol rate provided by the embodiment of the invention can be applied to signal processing equipment such as frequency spectrum monitoring equipment or wireless detection instruments.
Referring to fig. 1, fig. 1 is a schematic diagram of a hardware structure of a signal processing apparatus for estimating a symbol rate of a signal according to an embodiment of the present invention, where the signal processing apparatus 100 includes: a transceiver 101, a memory 102, an input-output device 103, and a processor 104 coupled to the transceiver 101, the memory 102, and the input-output device 103. The transceiver 101 is used for receiving signals, the memory 102 is used for storing data and instructions, the input and output device 103 is used for inputting and outputting information related to signal processing, and the processor 104 is used for executing instructions. The method of signal symbol rate estimation may be performed according to instructions when executed by the processor 104. The input/output device 103 may be a display screen, a keyboard, a mouse, or the like.
The processor 104 may be used for signal processing operations such as signal sampling, parameter estimation, down-conversion low-pass filtering, burst signal detection, band-pass filtering, and signal nonlinear transformation. The processor 104 may be a Central Processing Unit (CPU), a general purpose processor, a Digital Signal Processor (DSP), an application-specific integrated circuit (ASIC), a Field Programmable Gate Array (FPGA), other programmable logic devices (plc), a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. A processor may also be a combination of computing functions, e.g., comprising one or more microprocessors, a DSP and a microprocessor, or the like.
Optionally, the signal processing apparatus 100 may further include a bus. The transceiver 101, the memory 102, the input/output device 103, and the processor 104 may be connected to each other through a bus; the bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 1, but it is not intended that there be only one bus or one type of bus.
In addition to the transceiver 101, the memory 102, the input/output device 103, the processor 104 and the bus shown in fig. 1, the signal processing device 100 in the embodiment may also include other hardware according to the actual function of the device, which is not described again.
Referring to fig. 2, fig. 2 is a schematic flow chart of a method for estimating a symbol rate of a signal according to an embodiment of the present invention.
As shown in fig. 2, a method for estimating a symbol rate of a signal according to an embodiment of the present invention may include:
s210, receiving the first signal, and sampling the first signal to obtain a second signal.
And receiving a first signal in a preset frequency band range, wherein the preset frequency band range is set in advance by a user, and obtaining a second signal through signal sampling. For example, the second signal spectrum is shown in fig. 3. Preferably, the second signal spectrum is displayed on a screen of the signal processing device.
And S220, selecting a target signal from the second signal.
As a preferred embodiment, a first operation of the user is received, the first operation is that the user directly selects a desired signal as a target signal from a second signal by means of a mouse, touch control, and the like, for example, a selection button is arranged on a screen of the signal processing apparatus, a size-adjustable movable selection box is displayed on the screen by receiving the second operation of the user, the second operation is that the user clicks the selection button, the target signal is selected from the second signal by receiving a third operation of the user, the third operation is that the user adjusts the selection box by means of a mouse, touch control, and the like, and a signal in the selection box is the target signal.
As another preferred embodiment, the signal processing device intelligently selects the target signal from the second signal by presetting a selection rule, wherein the selection rule is set by a user in advance and can be changed by the user.
Preferably, the preset selection rule is as follows: selecting a particular frequency bin from the second signalIs the target signal. As shown in FIG. 4-a, a frequency band [ x ] is selected1,x2]The signal between Hz is the target signal.
Or, the preset selection rule is as follows: presetting a threshold value, and selecting a signal with the amplitude larger than the threshold value in a specific frequency band as a target signal from the second signal. As shown in FIG. 4-b, a frequency band [ x ] is selected3,x4]Amplitude value in Hz is larger than threshold value y1Is the target signal.
According to the embodiment, the signal processing device intelligently selects the target signal from the second signal through the preset selection rule, so that the signal selection efficiency is greatly improved, a user only needs to set the selection rule in advance, and the user can modify the selection rule at any time without reducing the flexibility of signal selection.
And S230, estimating a first carrier frequency and a first bandwidth of the target signal.
Preferably, the first carrier frequency and the first bandwidth of the target signal are estimated using a spectral centroid method. The specific implementation steps of the spectrum gravity center method are as follows: firstly, searching a local maximum value on a frequency spectrum of a target signal by using a search algorithm, backing gdB a local maximum value point, and calculating a frequency difference value of two frequency points corresponding to a backing gdB, wherein the frequency difference value is a first bandwidth of the target signal; and calculating the normalized power spectrum of the target signal, wherein the integrated value of the normalized power spectrum between the two frequency points is the first carrier frequency of the target signal.
For example, g equals 3, see fig. 5, as shown in fig. 5: firstly, searching the frequency spectrum of the target signal to obtain the local maximum value edB of the target signal, and estimating the first bandwidth B of the target signal if the ratio of two frequency points corresponding to (e-3) dB is cHz and dHzwIs (d-c) Hz.
Carrying out autocorrelation operation on a target signal, carrying out Fourier transform on the obtained autocorrelation signal to obtain a power spectrum of the target signal, further obtaining a normalized power spectrum S (omega) of the target signal, and estimating a first carrier frequency omega of the target signalsComprises the following steps:
s240, according to the first carrier frequency, down-converting the target signal F (j omega) into F (j (omega-omega) in the frequency domains))，ωsIs the first carrier frequency.
And S250, performing low-pass filtering on the down-converted signal according to the first bandwidth to obtain a first low-pass signal.
And low-pass filtering the down-converted signal to obtain a first low-pass signal. For example, the down-converted signal is low-pass filtered by:
wherein the content of the first and second substances,
the first low-pass signal is G (j ω) which is the down-converted signal, and H (j ω) which is a low-pass filter. For example, fig. 6 shows a first low-pass signal diagram.
The target signal is reserved through low-pass filtering, irrelevant signals are filtered, subsequent symbol rate estimation is facilitated, and the symbol rate estimation performance is improved.
And S260, preprocessing the first low-pass signal to obtain a third signal.
Preferably, whether the first low-pass signal is a burst signal is detected; if the first low-pass signal is a burst signal, acquiring the starting time of a first burst in the first low-pass signal, and intercepting or zero-filling to 2 from the starting time of the first burstnObtaining the third signal by a plurality of data points, wherein n is a positive integer; or, if the first low-pass signal is not a burst signal, truncating or zero-filling the first low-pass signal to 2nAnd obtaining the third signal by a plurality of data points, wherein n is a positive integer.
And detecting whether the first low-pass signal is a burst signal, namely performing burst signal detection on the first low-pass signal in a time domain.
As a preferred implementation, the first low-pass signal is burst signal detected based on an energy detection principle. The core idea of the energy detection principle is as follows: after the sending end sends out a signal, the energy of the burst signal received by the receiving end is larger than the energy of the signal without the burst gap.
Preferably, the first low-pass signal is subjected to burst signal detection by using a double sliding window signal detection algorithm based on an energy detection principle.
The double sliding window signal detection algorithm based on the energy detection principle can quickly acquire the start time of a burst signal, and a schematic block diagram of the algorithm is shown in fig. 7, and the basic principle of the algorithm is as follows: and carrying out autocorrelation operation on the first low-pass signal to obtain an autocorrelation signal of the first low-pass signal, setting two windows to slide on the autocorrelation signal simultaneously, setting the two windows to be relatively static in the sliding process, and calculating the energy values of the two windows in front and at the back. And setting a burst threshold, using the energy ratio of the two windows as a decision quantity, and comparing the decision quantity with the burst threshold to judge whether the first low-pass signal is a burst signal. And if the first low-pass signal is judged to be a burst signal by comparing with a burst threshold, the energy ratio of the two windows can be further used as a decision quantity to obtain the starting moment of the first burst in the first low-pass signal.
For example, the first low-pass signal is autocorrelation, as shown in fig. 8-a as a time-domain autocorrelation signal after normalizing the amplitude values. Then, double sliding windows w1 and w2 are constructed with an offset in time as shown in fig. 8-b, where t1 is about r symbol times in length and t2 is about m symbol times in length. When windows w1 and w2 slide from left to right point by point, when all signals in the windows are noise, the signal energy in the windows is stable at a small value, when burst signals enter a window body, the signal energy in the windows gradually increases, when all the signals in the whole windows are burst signals, the signal energy reaches a maximum value and continuously stabilizes until the noise starts to enter the window body, namely when the burst signals start to move out of the window body, the energy in the windows starts to decrease along with the sliding of the window body until the burst signals completely move out of the window body, and the signal energy in the windows is restored to a small value again and continuously enters the window body until the next burst signal enters the window body. The energy value of the window w1 is the sum of the data in the window w1, and the energy value of the window w2 is the sum of the data in the window w 2.
The sliding filtering of the autocorrelation signal using w1 and w2, respectively, as shown in fig. 8-c, is a signal detection diagram of a dual sliding window signal detection algorithm based on the energy detection principle, and the ordinate of the signal detection diagram represents the normalized energy ratio of the window w2 and the window w 1. Setting a burst threshold zsBy comparison with a burst threshold z, as shown in FIG. 8-csAnd comparing, judging that the first low-pass signal is a burst signal, and obtaining a pulse waveform consistent with the initial time of the first burst signal. And further, the starting moment of the first burst signal is obtained through pulse waveform peak detection, so that the first burst signal is identified and captured.
As another preferred implementation, the first low-pass signal is subjected to burst signal detection by using a preamble unique word-based detection algorithm. The core idea of the detection algorithm based on the lead code unique word is as follows: the initial part of each burst of different users and the primary station has a unique code, and the self-correlation characteristic of the unique code is used for burst signal detection, namely, a local unique code sequence is slid on a receiving sequence, and when the local unique code sequence is aligned with the receiving sequence, the correlation value of the local unique code sequence and the receiving sequence is the largest.
Preferably, a schematic block diagram of the detection based on the preamble unique word is shown in fig. 9. As shown in fig. 9, the basic principle of the algorithm is: differentiating the first low-pass signal, namely, performing conjugate multiplication on a signal obtained by delaying the first low-pass signal by one symbol and the first low-pass signal; carrying out modulation on the local unique word sequence in the same modulation mode as the received signal, and then carrying out difference on the modulated local unique word sequence, namely delaying the modulated local unique word sequence by one symbol and then carrying out conjugate multiplication on the delayed local unique word sequence and the modulated local unique word sequence; and performing sliding cross correlation on the differential signal of the first low-pass signal and the differential signal of the local unique word sequence modulation signal, and if the peak value of the occurrence of the correlation coefficient is greater than a set threshold, judging that a burst signal occurs, and finding out the initial position of a burst frame.
And S270, performing band-pass filtering on the third signal to obtain a first band-pass signal.
Performing band-pass filtering on the third signal to obtain a first band-pass signal, wherein the band-pass range of the band-pass filtering is [ x1,x2]Wherein x is1，x2A value is determined by the first bandwidth.
As a preferred embodiment, the third signal is band-pass filtered by a band-pass filter having a passband in the range of [ x ] to obtain a first bandpass signal1,x2]Wherein x is1，x2A value is determined by the first bandwidth. For example, the bandpass filter has a passband in the range of [0.8B ]w,1.3Bw]Wherein B iswIs a first bandwidth of the target signal.
As another preferred embodiment, the first bandpass signal is fourier transformed; the transformed spectrum is then filtered by: will measure [ -f ] in the frequency spectrums/2,-x2]，[-x1,x1]And [ x2, fs/2]Spectral data within intervals is zeroed, [ -x [ ]2,-x1]And [ x ]1,x2]The spectral data in the interval, where x remains unchanged1，x2A value is determined by the first bandwidth; and then carrying out Fourier inverse transformation on the filtered signal. For example, Fourier transform is performed on the first bandpass signal to obtain the frequency spectrum of the first bandpass signal, as shown in FIG. 10, and then [ -0.4B ] is added to the frequency spectrumw,0.4Bw]，[-fs/2,-0.65Bw]And [0.65Bw,fs/2]Spectral data in intervals is zeroed, [ -0.65Bw,-0.4Bw]And [0.4Bw,0.65Bw]The spectral data in the interval remains unchanged, wherein BwAnd performing inverse fourier transform on the filtered signal in fig. 10 to obtain a first bandpass signal, which is the first bandwidth of the target signal.
And S280, carrying out nonlinear transformation on the first bandpass signal to obtain a spectrogram, wherein the spectrogram is a frequency domain representation obtained after the nonlinear transformation is carried out on the first bandpass signal.
In a preferred embodiment, the first bandpass signal is subjected to a nonlinear transformation based on an envelope M-th power spectrum to obtain a spectral diagram.
Preferably, the first bandpass signal is subjected to nonlinear transformation based on an M-th power spectrum to obtain a spectral diagram, where M is equal to or greater than 1. The specific implementation mode is as follows: and carrying out M-power enveloping operation on the first bandpass signal in a time domain, carrying out Fourier transform on the data subjected to M-power enveloping operation to obtain an M-power enveloping spectrum, wherein the M-power enveloping spectrum is the spectrum diagram. For example, as shown in fig. 11, a diagram of the square spectrum of the envelope is shown.
As another preferred embodiment, the envelope spectrum-based nonlinear transformation is simplified into a maximum-minimum linear combination algorithm-based nonlinear transformation, that is, the first bandpass signal is subjected to nonlinear transformation based on the maximum-minimum linear combination algorithm to obtain a spectral diagram, and the maximum-minimum linear combination algorithm is complex vector magnitude estimation and is denoted as "α a + β B", where a is a maximum value of an imaginary part and a real part of the complex vector of the first bandpass signal, B is a minimum value of the imaginary part and the real part of the complex vector of the first bandpass signal, and α and β are greater than or equal to 0. The specific implementation mode is as follows: and performing maximum and minimum linear combination operation on the first bandpass signal envelope in a time domain, and performing Fourier transform on the operated data to obtain the spectrogram.
And S290, acquiring the position of the peak spectral line in the spectral line graph.
Preferably, to avoid interference of the DC component, [0.05f ] in the spectral diagrams,0.5fs]And searching the maximum value on the interval by using peak detection, and then acquiring the position k of the peak spectral line corresponding to the maximum value. For example, as shown in FIG. 11, a peak point y is obtained2And y3And the corresponding spectral line position of any point is the position k of the peak spectral line.
Preferably, after the position of the peak spectral line in the spectral line diagram is obtained, before the symbol rate estimation is performed on the first bandpass signal according to the position of the peak spectral line, the method further includes correcting the position of the peak spectral line. For example, the position of the peak spectral line is corrected according to an interpolation algorithm, and referring to fig. 12, a specific implementation of the spectral peak localization interpolation algorithm is as follows: constructing an estimation sample by using the k value and three similar sample value points; using estimated sample pointsEstimating an error delta according to a linear interpolation algorithm; correcting the position k of the peak spectral line to kpeak，kpeakK + δ. For example, the sample point coordinate pair is estimated as (k-1, | X)k-1|)、(k,|XkI) and (k +1, | Xk+1|), the error calculation is expressed as follows:
δ＝(|Xk+1|-|Xk-1|)/(4|Xk|-2|Xk-1|-2|Xk+1|)
the position of the peak spectral line is corrected, so that the peak spectral line is accurately positioned, and the symbol rate estimation precision is improved.
And S291, estimating the symbol rate of the first bandpass signal according to the position of the peak spectral line.
Preferably, when the position of the peak spectral line is corrected, the corrected position k of the peak spectral line is used as a referencepeakPerforming symbol rate estimation on the first bandpass signal, the symbol rate of the first bandpass signal being represented as follows:
wherein f issIs the sampling rate.
In summary, the embodiments of the present invention can use a smaller number of symbols to achieve accurate estimation of the symbol rate of the signal under the conditions of low snr and no reduction of the estimation accuracy. In addition, the technical scheme provided by the embodiment of the invention can reduce the operation complexity in the real-time signal processing, thereby accelerating the operation speed and saving the hardware resources.
Fig. 13 shows a possible structure of the apparatus for estimating the symbol rate of the signal in the case of using an integrated unit. As shown in fig. 13, the apparatus 1300 for estimating a symbol rate of a signal includes: first receiving section 1301, signal selecting section 1302, parameter estimating section 1303, down-converting section 1304, low-pass filtering section 1305, preprocessing section 1306, band-pass filtering section 1307, nonlinear converting section 1308, peak detecting section 1309, and symbol rate estimating section 1310.
The signal receiving unit 1301 is configured to receive a first signal, and sample the first signal to obtain a second signal.
A signal selecting unit 1302, configured to select a target signal from the second signal.
And a parameter estimation unit 1303, configured to estimate a first carrier frequency and a first bandwidth of the target signal.
A down-conversion unit 1304 for down-converting the target signal F (j ω) to F (j (ω - ω) in the frequency domain according to the first carrier frequencys))，ωsIs the first carrier frequency.
The low-pass filtering unit 1305 is configured to perform low-pass filtering on the down-converted signal according to the first bandwidth to obtain a first low-pass signal.
And a preprocessing unit 1306, configured to preprocess the first low-pass signal to obtain a third signal.
Preferably, whether the first low-pass signal is a burst signal is detected; if the first low-pass signal is a burst signal, acquiring the starting time of a first burst in the first low-pass signal, and intercepting or zero-filling to 2 from the starting time of the first burstnObtaining the third signal by a plurality of data points, wherein n is a positive integer; or, if the first low-pass signal is not a burst signal, truncating or zero-filling the first low-pass signal to 2nAnd obtaining the third signal by a plurality of data points, wherein n is a positive integer.
A band-pass filtering unit 1307 is configured to perform band-pass filtering on the third signal to obtain a first band-pass signal.
Preferably, the band-pass filtering unit is specifically configured to: performing band-pass filtering on the third signal to obtain the first band-pass signal, wherein the passband range of the band-pass filtering is [ x ]1,x2]Wherein x is1，x2A value is determined by the first bandwidth.
A nonlinear transformation unit 1308, configured to perform nonlinear transformation on the first bandpass signal to obtain a spectral line graph, where the spectral line graph is a frequency domain representation after the nonlinear transformation of the first bandpass signal.
Preferably, the nonlinear transformation unit is specifically configured to: carrying out nonlinear transformation based on an envelope M power spectrum on the first bandpass signal to obtain a spectrogram; or carrying out envelope nonlinear transformation on the first bandpass signal based on a maximum and minimum linear combination algorithm to obtain an envelope spectrum diagram, wherein the maximum and minimum linear combination algorithm is complex vector magnitude estimation and is expressed as 'alpha A + beta B', A is the maximum value in the imaginary part and the real part of the complex vector of the first bandpass signal, B is the minimum value in the imaginary part and the real part of the complex vector of the first bandpass signal, and alpha and beta are greater than or equal to 0.
A peak detecting unit 1309 is used to obtain the position of the peak spectral line in the spectral line graph.
Preferably, the signal symbol rate estimation apparatus 1300 further includes a correction unit configured to correct the position of the peak spectral line before the symbol rate estimation unit performs symbol rate estimation on the first bandpass signal according to the position of the peak spectral line after the peak detection unit acquires the position of the peak spectral line in the spectral line.
A symbol rate estimation unit 1310, configured to perform symbol rate estimation on the first bandpass signal according to the position of the peak spectral line.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware or in software executed by a processor. The software instructions may be composed of corresponding software modules, and the software modules may be stored in a Random Access Memory (RAM), a flash memory, a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a register, a hard disk, a removable hard disk, a compact disc read only memory (CD-ROM), or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an ASIC. Additionally, the ASIC may reside in a network device. Of course, the processor and the storage medium may reside as discrete components in a network device.
Those skilled in the art will recognize that, in one or more of the examples described above, the functions described in connection with the embodiments of the invention may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the embodiments of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only specific embodiments of the present invention, and are not intended to limit the scope of the embodiments of the present invention.
Claims (14)
1. A method for estimating a symbol rate of a signal, the method comprising:
receiving a first signal, and sampling the first signal to obtain a second signal;
selecting a target signal from the second signal;
estimating a first carrier frequency and a first bandwidth of the target signal;
down-converting the target signal F (j ω) to F (j (ω - ω) in a frequency domain according to the first carrier frequencys))，ωsIs the first carrier frequency;
performing low-pass filtering on the down-converted signal according to the first bandwidth to obtain a first low-pass signal;
preprocessing the first low-pass signal to obtain a third signal;
performing band-pass filtering on the third signal to obtain a first band-pass signal;
carrying out nonlinear transformation on the first bandpass signal to obtain a spectrogram, wherein the spectrogram is a frequency domain representation after the nonlinear transformation of the first bandpass signal;
acquiring the position of a peak spectral line in the spectral line graph;
and estimating the symbol rate of the first bandpass signal according to the position of the peak spectral line.
2. The method of claim 1, wherein preprocessing the first low-pass signal to obtain a third signal comprises:
detecting whether the first low-pass signal is a burst signal;
if the first low-pass signal is a burst signal, acquiring the starting time of a first burst in the first low-pass signal, and intercepting or zero-filling to 2 from the starting time of the first burstnObtaining the third signal by a plurality of data points, wherein n is a positive integer; or, if the first low-pass signal is not a burst signal, truncating or zero-filling the first low-pass signal to 2nAnd obtaining the third signal by a plurality of data points, wherein n is a positive integer.
3. The method of claim 1, wherein band-pass filtering the third signal to obtain a first band-pass signal comprises:
and performing band-pass filtering on the third signal to obtain the first band-pass signal, wherein the passband range of the band-pass filtering is [ x, y ], and the value of x and y is determined by the first bandwidth.
4. The method of claim 2, wherein band-pass filtering the third signal to obtain a first band-pass signal comprises:
and performing band-pass filtering on the third signal to obtain the first band-pass signal, wherein the passband range of the band-pass filtering is [ x, y ], and the value of x and y is determined by the first bandwidth.
5. The method according to any of claims 1 to 4, wherein the non-linear transformation of the first bandpass signal results in a spectral plot comprising:
carrying out nonlinear transformation based on an envelope M power spectrum on the first bandpass signal to obtain a spectrogram;
alternatively, the first and second electrodes may be,
and carrying out envelope nonlinear transformation on the first bandpass signal based on a maximum and minimum linear combination algorithm to obtain a spectral diagram, wherein the maximum and minimum linear combination algorithm is complex vector magnitude estimation and is expressed as alpha A + beta B, A is the maximum value in the imaginary part and the real part of the complex vector of the first bandpass signal, B is the minimum value in the imaginary part and the real part of the complex vector of the first bandpass signal, and alpha and beta are more than or equal to 0.
6. The method according to any one of claims 1 to 4, wherein after obtaining the position of the peak spectral line in the spectral line graph, before performing symbol rate estimation on the first bandpass signal according to the position of the peak spectral line, further comprising:
and correcting the position of the peak spectral line.
7. The method of claim 5, wherein after obtaining the location of the peak spectral line in the spectral line pattern, before performing symbol rate estimation on the first bandpass signal according to the location of the peak spectral line, further comprising:
and correcting the position of the peak spectral line.
8. An apparatus for signal symbol rate estimation, the apparatus comprising:
the first receiving unit is used for receiving a first signal and sampling the first signal to obtain a second signal;
a signal selection unit for selecting a target signal from the second signal;
a parameter estimation unit, configured to estimate a first carrier frequency and a first bandwidth of the target signal;
a down-conversion unit for down-converting the target signal F (j ω) into F (j (ω - ω) in a frequency domain according to the first carrier frequencys))，ωsIs the first carrier frequency;
the low-pass filtering unit is used for performing low-pass filtering on the signal subjected to the down-conversion according to the first bandwidth to obtain a first low-pass signal;
the preprocessing unit is used for preprocessing the first low-pass signal to obtain a third signal;
the band-pass filtering unit is used for performing band-pass filtering on the third signal to obtain a first band-pass signal;
a nonlinear transformation unit, configured to perform nonlinear transformation on the first bandpass signal to obtain a spectral line graph, where the spectral line graph is a frequency domain representation after the nonlinear transformation of the first bandpass signal;
the peak detection unit is used for acquiring the position of a peak spectral line in the spectral line graph;
and the symbol rate estimation unit is used for estimating the symbol rate of the first bandpass signal according to the position of the peak spectral line.
9. The apparatus according to claim 8, wherein the preprocessing unit is specifically configured to:
detecting whether the first low-pass signal is a burst signal;
if the first low-pass signal is a burst signal, acquiring the starting time of a first burst in the first low-pass signal, and intercepting or zero-filling to 2 from the starting time of the first burstnObtaining the third signal by a plurality of data points, wherein n is a positive integer; or, if the first low-pass signal is not a burst signal, truncating or zero-filling the first low-pass signal to 2nAnd obtaining the third signal by a plurality of data points, wherein n is a positive integer.
10. The apparatus according to claim 8, wherein the band-pass filtering unit is specifically configured to:
and performing band-pass filtering on the third signal to obtain the first band-pass signal, wherein the passband range of the band-pass filtering is [ x, y ], and the value of x and y is determined by the first bandwidth.
11. The apparatus according to claim 9, wherein the band-pass filtering unit is specifically configured to:
and performing band-pass filtering on the third signal to obtain the first band-pass signal, wherein the passband range of the band-pass filtering is [ x, y ], and the value of x and y is determined by the first bandwidth.
12. The apparatus according to any of the claims 8 to 11, wherein the nonlinear transformation unit is specifically configured to:
carrying out nonlinear transformation based on an envelope M power spectrum on the first bandpass signal to obtain a spectrogram;
alternatively, the first and second electrodes may be,
and carrying out nonlinear transformation on the first bandpass signal based on a maximum and minimum linear combination algorithm to obtain a spectrogram, wherein the maximum and minimum linear combination algorithm is complex vector magnitude estimation and is expressed as 'alpha A + beta B', A is the maximum value in the imaginary part and the real part of the complex vector of the first bandpass signal, B is the minimum value in the imaginary part and the real part of the complex vector of the first bandpass signal, and alpha and beta are more than or equal to 0.
13. The apparatus of any one of claims 8 to 11, further comprising:
and the correcting unit is used for correcting the position of the peak spectral line before the symbol rate estimating unit estimates the symbol rate of the first bandpass signal according to the position of the peak spectral line after the peak detecting unit acquires the position of the peak spectral line in the spectral line diagram.
14. The apparatus of claim 12, further comprising:
and the correcting unit is used for correcting the position of the peak spectral line before the symbol rate estimating unit estimates the symbol rate of the first bandpass signal according to the position of the peak spectral line after the peak detecting unit acquires the position of the peak spectral line in the spectral line diagram.
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