CN111103602A - Doppler frequency offset processing method and device and terminal - Google Patents
Doppler frequency offset processing method and device and terminal Download PDFInfo
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- CN111103602A CN111103602A CN201911328240.3A CN201911328240A CN111103602A CN 111103602 A CN111103602 A CN 111103602A CN 201911328240 A CN201911328240 A CN 201911328240A CN 111103602 A CN111103602 A CN 111103602A
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Abstract
The application discloses a Doppler frequency offset processing method, a device and a terminal. The method comprises the following steps: determining respective power spectrums of all sampling points of a received signal to be processed based on a preset power spectrum estimation algorithm; carrying out spectrum peak value search processing on respective power spectrums of each sampling point of the received signal, and determining respective corresponding spectrum peaks of each sampling point of the received signal; and carrying out smooth filtering processing on the spectral peaks corresponding to the sampling points of the received signal. The method and the device have the advantages that in the prior art, the problems of large calculation amount and low accuracy of Doppler frequency offset estimation caused by the need of depending on auxiliary data or the need of carrying out symbol timing recovery are solved, and then the subsequent signal processing precision of a receiver is improved.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a doppler frequency offset processing method, an apparatus, and a terminal.
Background
The Low-Earth Orbit (LEO) satellite Orbit has Low height and fast movement speed, so that the doppler frequency offset relative to the ground receiving end is large and is fast time-varying. Therefore, the low-earth orbit satellite receiver needs to estimate and pre-compensate the doppler frequency offset which is rapidly time-varying in a large range in real time before the conventional demodulation operation.
The existing estimation method for satellite Doppler frequency shift mainly comprises an estimation algorithm based on a training sequence, an algorithm based on orbit parameter estimation and an algorithm based on M power demodulation. The algorithm based on the training sequence utilizes the known pilot frequency sequence inserted in the data frame to perform frequency offset estimation, and the premise is that the timing information is recovered and is only suitable for scenes with small relative frequency offset. The algorithm based on orbit parameter estimation predicts the Doppler frequency offset in the satellite visual time period according to the satellite ephemeris and the position of the ground receiver, needs prior information such as the satellite ephemeris and the position of the receiver, and requires that time synchronization is completed, but the accurate calculation computation workload of the satellite position is large. The algorithm based on M-power demodulation performs M-power operation on data for M-ary phase Shift Keying (MPSK) and M-ary Quadrature amplitude modulation (MQAM) signals to remove the influence of data information, and estimates the frequency offset, because the doppler component in situ at the frequency fd is moved to Mfd after the M-power operation, the sampling rate requirement is high and the operation amount is large when the doppler frequency offset is large.
Disclosure of Invention
In order to solve at least one technical problem, the present application provides a doppler frequency offset processing method, an apparatus and a terminal.
According to a first aspect of the present application, there is provided a doppler frequency offset processing method, including:
determining respective power spectrums of all sampling points of a received signal to be processed based on a preset power spectrum estimation algorithm;
carrying out spectrum peak value search processing on respective power spectrums of each sampling point of the received signal, and determining respective corresponding spectrum peaks of each sampling point of the received signal;
and carrying out smooth filtering processing on the spectral peaks corresponding to the sampling points of the received signal.
According to a second aspect of the present application, there is provided a doppler frequency shift processing apparatus, the apparatus including: a power spectrum determining module, a spectrum peak searching module and a filtering processing module,
the power spectrum determination module is used for determining the respective power spectrum of each sampling point of the received signal to be processed based on a preset power spectrum estimation algorithm;
the spectrum peak searching module is used for searching and processing the spectrum peak value of the power spectrum of each sampling point of the received signal and determining the spectrum peak corresponding to each sampling point of the received signal;
and the filtering processing module is used for performing smoothing filtering processing on each sampling point of the received signal correspondingly.
According to a third aspect of the present application, there is provided a terminal comprising: the doppler frequency shift processing method comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the computer program to realize the doppler frequency shift processing method.
According to a fourth aspect of the present application, there is provided a computer-readable storage medium storing computer-executable instructions for performing the above-mentioned doppler frequency shift processing method.
The method and the device solve the problems that in the prior art, auxiliary data is required to be relied on or symbol timing recovery is required to be carried out, so that the Doppler frequency offset estimation computation amount is large and the accuracy is low, and further the subsequent signal processing precision of a receiver is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments of the present application will be briefly described below.
Fig. 1 is a schematic flowchart of a doppler frequency shift processing method according to an embodiment of the present application;
fig. 2 is a schematic diagram of a processing framework for applying a doppler frequency shift processing method according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a processing framework of a receiver of a low earth orbit satellite communication system applying a Doppler frequency offset processing method according to an embodiment of the present application;
fig. 4 is a schematic diagram of a power spectrum and a spectrum peak thereof obtained by a doppler frequency offset processing method according to an embodiment of the present application;
fig. 5 is a block diagram illustrating a structure of a doppler frequency shift processing apparatus according to an embodiment of the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
It should be noted that although functional blocks are partitioned in a schematic diagram of an apparatus and a logical order is shown in a flowchart, in some cases, the steps shown or described may be performed in a different order than the partitioning of blocks in the apparatus or the order in the flowchart.
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
According to an embodiment of the present application, there is provided a doppler frequency shift processing method, as shown in fig. 1, the method including: step S101, step S102, and step S103.
Step S101: and determining the respective power spectrum of each sampling point of the received signal to be processed based on a preset power spectrum estimation algorithm.
In the embodiment of the application, the receiver determines the power spectrum corresponding to the received signal to be processed based on a preset power spectrum estimation algorithm. Specifically, when the receiver acquires the received signal to be processed, the receiver may first buffer the received signal through the buffer module, and then determine the power spectrum corresponding to the received signal to be processed by reading the received signal in the buffer module.
In the embodiment of the present application, the power spectrum characterizes the variation of the signal power with frequency, i.e. the distribution of the signal power in the frequency domain.
Step S102: and carrying out spectrum peak search processing on the respective power spectrum of each sampling point of the received signal, and determining the respective corresponding spectrum peak of each sampling point of the received signal.
Step S103: and carrying out smooth filtering processing on the spectral peaks corresponding to the sampling points of the received signal.
In the embodiment of the application, based on a preset power spectrum estimation algorithm, the respective power spectrum of each sampling point of a received signal to be processed is determined, the spectral peak value search processing is performed on the respective power spectrum of each sampling point of the received signal, and the spectral peak corresponding to each sampling point of the received signal is determined, so that the smooth filtering processing is performed on the spectral peak corresponding to each sampling point of the received signal, the problems that in the prior art, the doppler frequency offset estimation computation amount is large and the accuracy is low due to the fact that auxiliary data is needed to be relied on or symbol timing recovery is needed to be performed are solved, and the subsequent processing accuracy of a receiver on the signal is improved.
In one embodiment, the power spectrum estimation algorithm is a Time Varying Burg (TV-Burg) power spectrum estimation algorithm, and the AR model parameters corresponding to the Time Varying Burg power spectrum estimation algorithm include an order and a forgetting factor, which determine the Burg power spectrum in a Time iterative manner.
In one embodiment, as shown in fig. 1, the step S101 determines, based on a preset power spectrum estimation algorithm, a power spectrum of each sampling point of the received signal to be processed, including: step S1011 (not shown), step S1012 (not shown), and step S1013 (not shown).
Step S1011: initializing the model parameters of the AR model, and taking the initialized model parameters of the AR model as the model parameters of the AR model corresponding to the first sampling point of the received signal.
Step S1012: and determining a Burg power spectrum corresponding to the first sampling point of the received signal according to the model parameters of the AR model corresponding to the first sampling point of the received signal.
Step S1013: and performing iterative calculation based on the model parameters of the AR model corresponding to the first sampling point of the received signal, determining the model parameters of the AR model corresponding to each remaining sampling point of the received signal, and determining the Burg power spectrum corresponding to each remaining sampling point of the received signal according to the model parameters of the AR model corresponding to each remaining sampling point of the received signal.
In the embodiment of the application, a time recursion idea and a forgetting factor lambda (0< lambda <1) are introduced into a TV-Burg power spectrum estimation algorithm, so that each sampling point updates a model parameter of an AR model once, only an intermediate result of a previous sampling point is used, block processing of the traditional Burg algorithm is converted into flow processing, the purposes of reducing storage capacity and calculating amount are achieved, the function of adaptively adjusting the parameter of the AR model along with the change of Doppler frequency offset in a signal is achieved, the accuracy of the Doppler frequency offset processing result of each sampling point at the current moment is ensured, and therefore the method provided by the embodiment of the application is suitable for capturing the time-varying Doppler frequency offset of a low-orbit satellite.
In the embodiment of the application, the order of the AR model is set to be 2, namely the model corresponding to the TV-burg power spectrum estimation algorithm is the 2-order AR model.
During specific application, firstly, initializing model parameters of an AR model, determining values of an order p and a forgetting factor lambda of the AR model, and determining an initialized intermediate result: cm[0]＝0,Dm[0]＝0,gm[0]＝0,m＝1,...,p。
The following procedure is performed for each sample point n in turn:
inputting: current sample point x [ n ]]Calculation result C of previous sampling pointm[n-1],Dm[n-1],gm[n-1],Km[n-1],m＝1,...,p。
Step 1: initializing forward and backward prediction errors f and g of a current point:
f0[n]＝g0[n]＝x[n]and let m equal to 1.
Step 2: updating the forward and backward prediction errors:
fm[n]＝fm-1[n]+Km[n-1]gm-1[n-1]
and step 3: solving the intermediate coefficient:
Dm[n]＝λDm[n-1]+0.5(1-λ)·(|fm-1[n]|2+|gm-1[n-1]|2)。
and 4, step 4: calculating a reflection coefficient:
and 5: calculating m-order AR model parameters
The model parameters of the AR model include amAnd (5) waiting for each-order autoregressive parameter.
am,m[n]＝Km[n]。
Step 6: and c, enabling m ← m +1, and repeating the steps 2 to 5 until the order recursion is completed, namely, when m ═ p, the order recursion is completed.
And 7: according to the obtained p-order AR model parameters
The Burg power spectrum at the current point is calculated according to the following formula (1).
Wherein σ2Is a signal functionRate, fsFor the sampling frequency,. DELTA.t.1/fsIs the sampling interval, f is the frequency, and j is the imaginary unit.
In another embodiment, as shown in fig. 1, step S103 performs a smoothing filtering process on the respective corresponding spectral peaks of the respective sampling points of the received signal, including step S1031, step S1032 and step S1033.
Step S1031 (not shown in the figure): and constructing a system state model, wherein the system state model comprises a first state quantity aiming at the Doppler frequency offset and a second state quantity aiming at the change rate of the Doppler frequency offset.
Step S1032 (not shown in the figure): and based on the system state model, calculating according to the respective corresponding spectral peaks of the sampling points of the received signal, and determining the respective corresponding Doppler frequency estimated values of the sampling points of the received signal.
Step S1033 (not shown in the figure): and carrying out smooth filtering processing according to the Doppler frequency estimated values corresponding to the sampling points of the received signal.
In one embodiment, the step S1033 performs a smoothing filtering process according to the respective doppler frequency estimated values corresponding to the respective sampling points of the received signal, including:
based on the predefined filter, and according to the Doppler frequency estimated value corresponding to each sampling point of the received signal, the smoothing filtering process is carried out.
In specific application, filters such as a Kalman filter, an alpha-beta filter and the like can be adopted for smoothing filtering processing. In the embodiment of the application, the smoothing filtering is processed by an alpha-beta filter.
Specifically, α and β parameters are selected in an interval (0,1), and the closer the value is to 1, the faster the filtering result can track transient change, the closer the value is to 0, the smaller the influence of noise in the filtering result is, and the smoother the result is.
For particular applications, α and β are generally determined according to equations (9) - (12):
α＝1-Γ2(11)；
in the above formula, σwAnd σvRespectively, process noise variance and metrology noise variance.
For example, assume that the smoothed Doppler frequency offset estimate (i.e., the state quantity at the current time) at sample point n is
The first order rate of change of the Doppler frequency offset after smooth filtering is
State quantity at last moment
And
under the known premise, the Doppler frequency offset estimation value corresponding to the power spectrum peak at the current moment n
The smoothing filtering process of (2) to (6) is shown in the following equations.
Where at is the sampling time interval,
is the filtered residual. Smoothing filter results for each sampling instant
Doppler frequency offset estimation as a stage 2
Specifically, the filter may initialize the state quantity according to the following formula:
wherein the content of the first and second substances,
is an estimate of the doppler frequency offset at time n,
is the doppler frequency offset estimate at time (n-1).
And
all are state quantities at time n, and Δ t is a unit sampling time.
In yet another embodiment, as shown in fig. 1, the method further comprises:
step S104 (not shown in the figure): determining Doppler frequency spectrum estimated values corresponding to all sampling points of the received signal after smoothing filtering, and performing frequency offset pre-compensation processing on the received signal to obtain a pre-compensation signal;
step S105 (not shown in the figure): and sequentially carrying out matched filtering, timing synchronization, carrier synchronization, de-mapping and decoding operations on the pre-compensation signal to obtain an output bit stream.
Specifically, the matched filtering process uses a filter coefficient matched with the transmitting end forming filtering to carry out matched filtering on the signal, so that the signal-to-noise ratio is improved; the timing synchronization processing extracts a timing pulse sequence synchronous with the code element from the signal so as to ensure that the optimal sampling point can be found under the condition that the sampling clock has deviation; the carrier synchronization processing extracts training sequences such as pilot frequency from the received signal according to the timing information so as to further compensate the residual frequency offset and the phase offset in the signal; and finally, demodulating and decoding the data symbols in sequence to obtain a final output bit stream.
According to the embodiment of the application, the first-stage processing of the received signal is realized through the processing of the steps S101 to S103, that is, the Doppler frequency offset compensation of the received signal is realized, and the problem that the accuracy of subsequent processing of the signal to be processed is poor due to poor Doppler frequency offset processing accuracy in the prior art is solved, so that accurate data is provided for the subsequent processing of the step S104, and the accuracy of the signal processing of the receiver is ensured.
The following takes a receiver as an example to describe in detail the doppler frequency offset processing method provided in the embodiments of the present application.
In use, as shown in FIG. 2, the receiver acquires the received data y [ n ]]Then, for the received data y [ n ]]The process of (2) comprises two stages. The specific process of the stage 1 is as follows: the output of the first stage is obtained by TV-Burg spectral estimation
(i.e., determining a coarse estimate of the frequency offset by peak spectral peak search processing is recorded as
) Then filtering is carried out through an alpha-beta filter to obtain the output of the stage 2
I.e. to obtain a more accurate doppler frequency offset value for the compensation process. In particular, the subsequent processing of the receiver after obtaining the result output in fig. 2 can be determined with reference to fig. 3. As shown in FIG. 3, the receiver acquires received data y [ n ]]Then, firstly, Doppler pre-estimation is carried out by utilizing a TV-Burg power spectrum estimation algorithm, and output is carried out
Then, after the alpha-beta filter is used for smoothing, a more accurate Doppler pre-estimated value is obtained
By passing
Pre-compensation processing of received data is realized to obtain signal x [ n ] after pre-compensation of Doppler frequency offset]Then, the pre-compensated signal x [ n ] is processed]The matched filtering processing, the timing synchronization processing, the carrier synchronization processing, the demodulation and the decoding operation in the conventional communication system are sequentially carried out.
Specifically, the output results of stage 1 in fig. 2 are shown in fig. 4. Fig. 4 is a power spectrum (dotted line) estimated at 22ms by the TV-Burg spectrum estimation algorithm of stage 1, SNR-3 dB, and forgetting factor λ 0.99995. In fig. 4, a periodic map (solid line) obtained by 1024-point FFT at the same time is plotted at the same time for comparison. The five stars in the figure represent the true value of the frequency offset at the current time. It can be seen that when the signal-to-noise ratio is low, the periodic spectrum based on the FFT does not perform well for estimating the power spectrum of the QPSK received signal, and the peak position of the TV-Burg power spectrum (i.e., the position of the upper triangle in fig. 4) is a more accurate estimate of the doppler frequency offset.
Still another embodiment of the present application provides a doppler frequency shift processing apparatus, as shown in fig. 5, the apparatus includes: a power spectrum determination module 301, a spectral peak search module 302 and a filtering processing module 303.
A power spectrum determining module 301, configured to determine, based on a preset power spectrum estimation algorithm, respective power spectrums of sampling points of a received signal to be processed;
a spectrum peak searching module 302, configured to perform spectrum peak searching processing on the power spectrum of each sampling point of the received signal, and determine a spectrum peak corresponding to each sampling point of the received signal;
and the filtering processing module 303 is configured to perform smoothing filtering processing on each corresponding sampling point of the received signal.
In the embodiment of the application, based on a preset power spectrum estimation algorithm, the respective power spectrum of each sampling point of a received signal to be processed is determined, the spectral peak value search processing is performed on the respective power spectrum of each sampling point of the received signal, and the spectral peak corresponding to each sampling point of the received signal is determined, so that the smooth filtering processing is performed on the spectral peak corresponding to each sampling point of the received signal, the problems that in the prior art, the doppler frequency offset estimation computation amount is large and the accuracy is low due to the fact that auxiliary data is needed to be relied on or symbol timing recovery is needed to be performed are solved, and the subsequent processing accuracy of a receiver on the signal is improved.
Further, the power spectrum estimation algorithm is a time-varying Burg power spectrum estimation algorithm, and the AR model parameters corresponding to the time-varying Burg power spectrum estimation algorithm comprise an order and a forgetting factor.
Further, the power spectrum determination module comprises 301: an initialization processing unit (not shown), a power spectrum determination unit (not shown), and an iteration processing unit (not shown).
The initial processing unit is used for initializing model parameters of the AR model, and taking the initialized model parameters of the AR model as the model parameters of the AR model corresponding to the first sampling point of the received signal;
the power spectrum determination unit is used for determining a Burg power spectrum corresponding to the first sampling point of the received signal according to the model parameter of the AR model corresponding to the first sampling point of the received signal;
and the iteration processing unit is used for performing iterative calculation based on the model parameters of the AR model corresponding to the first sampling point of the received signal, determining the model parameters of the AR model corresponding to the rest sampling points of the received signal, and determining the Burg power spectrum corresponding to the rest sampling points of the received signal according to the model parameters of the AR model corresponding to the rest sampling points of the received signal.
Further, the filtering processing module 303 includes: a model creation unit (not shown in the figure), a frequency estimation unit (not shown in the figure), and a smoothing processing unit (not shown in the figure).
And the model creating unit is used for constructing a system state model, and the system state model comprises a first state quantity aiming at the Doppler frequency offset and a second state quantity aiming at the change rate of the Doppler frequency offset.
The frequency estimation unit is used for calculating according to the spectral peaks corresponding to the sampling points of the received signal based on the system state model and determining Doppler frequency estimation values corresponding to the sampling points of the received signal;
and the smoothing processing unit is used for carrying out smoothing filtering processing according to the Doppler frequency estimated values corresponding to the sampling points of the received signal.
Further, the smoothing processing unit includes: a smoothing subunit (not shown in the figure), wherein,
and the smoothing processing subunit is used for performing smoothing filtering processing on the basis of a predefined filter according to the Doppler frequency estimated values corresponding to the sampling points of the received signal.
Further, the apparatus further comprises: a pre-compensation processing module (not shown) and a signal re-processing module (not shown), wherein,
the pre-compensation processing module is used for determining Doppler frequency spectrum estimated values corresponding to all sampling points of the received signal after the smoothing filtering processing, and performing frequency offset pre-compensation processing on the received signal to obtain a pre-compensation signal;
and the signal reprocessing module is used for sequentially carrying out matched filtering, timing synchronization, carrier synchronization, de-mapping and decoding operations on the pre-compensation signal to obtain an output bit stream.
The doppler frequency offset processing apparatus of this embodiment may execute the doppler frequency offset processing method provided in this embodiment, and the implementation principles thereof are similar, and are not described herein again.
Another embodiment of the present application provides a terminal, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executing the computer program realizes the above-mentioned doppler frequency shift processing method.
In particular, the processor may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, 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.
In particular, the processor is coupled to the memory via a bus, which may include a path for communicating information. The bus may be a PCI bus or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc.
The memory may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an EEPROM, a CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
Optionally, the memory is used for storing codes of computer programs for executing the scheme of the application, and the processor is used for controlling the execution. The processor is configured to execute the application program codes stored in the memory to implement the actions of the doppler frequency shift processing apparatus provided by the embodiment shown in fig. 5.
In the embodiment of the application, based on a preset power spectrum estimation algorithm, the respective power spectrum of each sampling point of a received signal to be processed is determined, the spectral peak value search processing is performed on the respective power spectrum of each sampling point of the received signal, and the spectral peak corresponding to each sampling point of the received signal is determined, so that the smooth filtering processing is performed on the spectral peak corresponding to each sampling point of the received signal, the problems that in the prior art, the doppler frequency offset estimation computation amount is large and the accuracy is low due to the fact that auxiliary data is needed to be relied on or symbol timing recovery is needed to be performed are solved, and the subsequent processing accuracy of a receiver on the signal is improved.
Yet another embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions for performing the above-mentioned doppler frequency shift processing method.
In the embodiment of the application, based on a preset power spectrum estimation algorithm, the respective power spectrum of each sampling point of a received signal to be processed is determined, the spectral peak value search processing is performed on the respective power spectrum of each sampling point of the received signal, and the spectral peak corresponding to each sampling point of the received signal is determined, so that the smooth filtering processing is performed on the spectral peak corresponding to each sampling point of the received signal, the problems that in the prior art, the doppler frequency offset estimation computation amount is large and the accuracy is low due to the fact that auxiliary data is needed to be relied on or symbol timing recovery is needed to be performed are solved, and the subsequent processing accuracy of a receiver on the signal is improved.
The above-described embodiments of the apparatus are merely illustrative, and the units illustrated as separate components may or may not be physically separate, may be located in one place, or may be distributed over a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
One of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
While the present invention has been described with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A doppler frequency offset processing method, comprising:
determining respective power spectrums of all sampling points of a received signal to be processed based on a preset power spectrum estimation algorithm;
carrying out spectrum peak value search processing on respective power spectrums of all sampling points of the received signal, and determining respective corresponding spectrum peaks of all sampling points of the received signal;
and carrying out smooth filtering processing on the spectral peaks corresponding to the sampling points of the received signal.
2. The method according to claim 1, wherein the power spectrum estimation algorithm is a time-varying Burg power spectrum estimation algorithm, and the AR model parameters corresponding to the time-varying Burg power spectrum estimation algorithm comprise an order and a forgetting factor.
3. The method according to claim 2, wherein the determining the respective power spectrum of each sampling point of the received signal to be processed based on a preset power spectrum estimation algorithm comprises:
initializing the model parameters of the AR model, and taking the initialized model parameters of the AR model as the model parameters of the AR model corresponding to the first sampling point of the received signal;
determining a Burg power spectrum corresponding to the first sampling point of the received signal according to the model parameter of the AR model corresponding to the first sampling point of the received signal;
and performing iterative computation based on the model parameters of the AR model corresponding to the first sampling point of the received signal, determining the model parameters of the AR model corresponding to each of the rest sampling points of the received signal, and determining the Burg power spectrum corresponding to each of the rest sampling points of the received signal according to the model parameters of the AR model corresponding to each of the rest sampling points of the received signal.
4. The method according to claim 1, wherein the performing a smoothing filtering process on the respective corresponding spectral peaks of the respective sampling points of the received signal comprises:
constructing a system state model, wherein the system state model comprises a first state quantity aiming at Doppler frequency offset and a second state quantity aiming at the change rate of the Doppler frequency offset;
based on the system state model, calculating according to the respective corresponding spectral peaks of the sampling points of the received signal, and determining the respective corresponding Doppler frequency estimation values of the sampling points of the received signal;
and carrying out smooth filtering processing according to the Doppler frequency estimation values corresponding to the sampling points of the received signal.
5. The method according to claim 4, wherein the performing the smoothing filtering process according to the respective Doppler frequency estimated values corresponding to the respective sampling points of the received signal comprises:
and based on a predefined filter, carrying out smoothing filtering processing according to Doppler frequency estimated values corresponding to all sampling points of the received signal.
6. The method of claim 1, further comprising:
determining Doppler frequency spectrum estimated values corresponding to all sampling points of the received signal after smoothing filtering, and performing frequency offset pre-compensation processing on the received signal to obtain a pre-compensation signal;
and sequentially carrying out matched filtering, timing synchronization, carrier synchronization, de-mapping and decoding operations on the pre-compensation signal to obtain an output bit stream.
7. A doppler frequency shift processing apparatus, comprising: the device comprises a power spectrum determining module, a spectrum peak searching module and a filtering processing module;
the power spectrum determination module is used for determining the respective power spectrum of each sampling point of the received signal to be processed based on a preset power spectrum estimation algorithm;
the spectrum peak searching module is used for performing spectrum peak searching processing on the respective power spectrum of each sampling point of the received signal and determining the respective corresponding spectrum peak of each sampling point of the received signal;
and the filtering processing module is used for performing smooth filtering processing on the spectral peaks corresponding to the sampling points of the received signals.
8. The apparatus of claim 7, wherein the power spectrum estimation algorithm is a time-varying Burg power spectrum estimation algorithm, and the AR model parameters corresponding to the time-varying Burg power spectrum estimation algorithm comprise an order and a forgetting factor.
9. A terminal, comprising: memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method of any of claims 1 to 6.
10. A computer-readable storage medium storing computer-executable instructions for performing the method of any one of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911328240.3A CN111103602A (en) | 2019-12-20 | 2019-12-20 | Doppler frequency offset processing method and device and terminal |
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