A rate synchronization resampling method, device and medium based on satellite communication

Abstract

The present invention discloses a rate synchronization resampling method, device and medium based on satellite communication, including the following specific steps: obtaining a sampling signal, preprocessing the sampling signal, and obtaining a discrete signal with a discrete sequence number; constructing an NCO loop based on the Gardner bit synchronization algorithm, determining the sampling step and interpolation interval of the discrete signal; determining an offset value according to the sampling step and interpolation interval, and restoring and reconstructing the original signal in combination with the OMP algorithm. By preprocessing the sampling signal to obtain a discrete signal with a discrete sequence number, reducing the interference of noise on the sampling signal, constructing an NCO loop to determine the sampling step and interpolation interval of the discrete signal to reduce the sampling error of the resampled data, and improving the sampling accuracy, the OMP algorithm reconstructs the signal of the resampled data, simplifies the signal recovery process, and reduces the complexity of the algorithm.

Description

Technical Field

[0001] The present invention relates to the technical field of communication data processing, and in particular to a rate synchronization resampling method, device and medium based on satellite communication. Background Art

[0002] Satellite data has important application value in the field of remote sensing. However, due to the characteristics of satellite sensors and the data collection method, satellite data often have inconsistent spatial resolution. In order to solve this problem, it is necessary to use a resampling algorithm to process satellite data to adapt it to specific application requirements. The basic principle of the satellite data resampling algorithm is to redistribute the original data in space to achieve the required spatial resolution. The core of the resampling algorithm is the interpolation method, which is to estimate the value of the unknown position based on the value of the known data point.

[0003] In the resampling process, the existing technology often has the following problems:

[0004] 1. The receiver needs to process data for a long time to capture weak signals to improve the processing gain of the receiver, which will greatly increase the time of navigation satellite capture, resulting in a longer signal recovery process and high algorithm complexity;

[0005] 2. In general, the energy of the navigation satellite signal received by the receiver will be greatly weakened due to propagation in the air, and the received signal will also include various noises;

[0006] 3. For satellite remote sensing images, the sampling points are affected by factors such as payload imaging mode, earth curvature, satellite attitude, and satellite vibration, and often appear as irregular sampling;

[0007] In the application scenario of satellite high-speed digital transmission, a series of calculations such as demodulation, synchronization and decoding are required for the received signal. In order to achieve high-speed transmission, the computing delay of the processing equipment should be minimized, the signal processing throughput should be increased, and the processing delay should be reduced. Summary of the invention

[0008] The technical problem to be solved by the present invention is that the sampling signal is irregular, the sampling signal accuracy is low, the signal recovery process is long, and the algorithm complexity is high. The purpose is to provide a rate synchronous resampling method, device and medium based on satellite communication. By preprocessing the sampling signal, a discrete signal with a discrete sequence number is obtained, the interference of noise on the sampling signal is reduced, and an NCO loop is constructed to determine the sampling step size and interpolation interval of the discrete signal to reduce the sampling error of the resampled data and improve the sampling accuracy. The OMP algorithm reconstructs the signal of the resampled data, simplifies the signal recovery process, and reduces the algorithm complexity.

[0009] The present invention is achieved through the following technical solutions:

[0010] A first aspect of the present invention provides a rate synchronization resampling method based on satellite communication, comprising the following specific steps:

[0011] Acquire a sampling signal, pre-process the sampling signal, and obtain a discrete signal with a discrete sequence number;

[0012] Construct an NCO loop based on the Gardner bit synchronization algorithm to determine the sampling step size and interpolation interval of discrete signals;

[0013] The offset value is determined according to the sampling step size and interpolation interval, and the original signal is restored and reconstructed in combination with the OMP algorithm.

[0014] The present invention obtains a discrete signal with a discrete sequence number by preprocessing the sampled signal, reduces the interference of noise on the sampled signal, constructs an NCO loop to determine the sampling step size and interpolation interval of the discrete signal to reduce the sampling error of the resampled data and improve the sampling accuracy. The OMP algorithm reconstructs the signal of the resampled data, simplifies the signal recovery process, and reduces the algorithm complexity.

[0015] Furthermore, the method of obtaining a discrete signal with a discrete sequence number includes: performing a continuous wavelet transform on the sampled data to obtain two groups of discrete time series, and performing a cross wavelet transform on the two groups of discrete time series to obtain a discrete signal with a discrete sequence number.

[0016] Furthermore, the step of determining the sampling step and interpolation interval of the discrete signal specifically includes:

[0017] Construct an NCO loop and perform interpolation operation on the discrete signal to obtain the interpolation yt1 at the current moment;

[0018] Detect the timing error in the NCO loop and obtain the calibration error by loop filtering.

[0019] Combined with the calibration error, numerically controlled oscillation is used to obtain the sampling step size and the interpolation interval calculated based on the interpolation yt1;

[0020] Repeat the steps to detect the timing error in the NCO loop until it is detected that the timing error is smaller than the set threshold, and output the sampling step size and interpolation interval.

[0021] Further, determining the offset value according to the sampling step size and the interpolation interval includes:

[0022] Performing compression measurement on the sampling signal according to the sampling step length and the interpolation interval to obtain a compressed sampling signal;

[0023] Perform sparse transformation on the compressed sampling signal to obtain the offset value.

[0024] Further, the compressing and measuring the sampled signal according to the sampling step size and the interpolation interval specifically includes:

[0025] Resampling the sampled signal according to the sampling step size and the interpolation interval to obtain a resampled signal;

[0026] Splitting the resampled signal, and splicing adjacent resampled signals after the splitting;

[0027] Get the local pseudo code sequence, split it, and put the splitted sequence into the local pseudo code sequence with double zero padding;

[0028] Perform circular correlation operation on the spliced ​​resampled signal and the double zero-filled local pseudo code sequence to obtain a correlation matrix;

[0029] Perform FFT operation on each column of the correlation matrix, and extract the maximum value of the FFT output through peak detection as the compressed sampling signal.

[0030] Further, the performing sparse transformation on the signal includes:

[0031] The maximum value of the FFT output is extracted by peak detection to determine the Doppler shift;

[0032] According to the Doppler frequency shift range, the Doppler frequency shift range is equally divided to obtain the Doppler step, and the Doppler frequency deviation vector is determined according to the Doppler step;

[0033] A frequency offset matrix is ​​constructed according to the Doppler vector, and the frequency offset matrix is ​​used to perform sparse changes on the compressed sampling signal.

[0034] Furthermore, the step of performing sparse changes on the compressed sampling signal by using the frequency offset matrix specifically includes:

[0035] The number of sampling points L of the compressed sampling signal is obtained, and a local pseudo code vector having a length of L sampling points is cyclically shifted to construct a code phase matrix;

[0036] According to the code phase matrix, a frequency conversion signal with a length of L sampling points is taken to obtain a correlation vector after code phase stripping;

[0037] The Doppler frequency offset is stripped from the signal after stripping the code phase according to the frequency offset matrix to obtain an offset value.

[0038] Furthermore, the recovering and reconstructing the original signal by combining the OMP algorithm specifically includes:

[0039] Based on the OMP algorithm, the signal correlation peak is restored according to the offset value, the code phase and Doppler frequency deviation of the signal are solved, and the original signal is reconstructed.

[0040] A second aspect of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a rate synchronization resampling method based on satellite communication is implemented.

[0041] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a rate synchronization resampling method based on satellite communication.

[0042] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0043] By preprocessing the sampled signal, a discrete signal with a discrete sequence number is obtained, reducing the interference of noise on the sampled signal, and constructing an NCO loop to determine the sampling step and interpolation interval of the discrete signal to reduce the sampling error of the resampled data and improve the sampling accuracy. The OMP algorithm reconstructs the resampled data, simplifies the signal recovery process, and reduces the complexity of the algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other relevant drawings can be obtained based on these drawings without creative work. In the drawings:

[0045] Figure 1 This is the resampling method in the embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0047] Example 1

[0048] like Figure 1 As shown, the first aspect of this embodiment provides a rate synchronization resampling method based on satellite communication, including the following specific steps: acquiring a sampling signal, preprocessing the sampling signal, and obtaining a discrete signal with a discrete sequence number; constructing an NCO loop based on the Gardner bit synchronization algorithm, and determining the sampling step and interpolation interval of the discrete signal; determining an offset value according to the sampling step and the interpolation interval, and restoring and reconstructing the original signal in combination with the OMP algorithm.

[0049] This embodiment obtains a discrete signal with a discrete sequence number by preprocessing the sampled signal, reduces the interference of noise on the sampled signal, constructs an NCO loop to determine the sampling step size and interpolation interval of the discrete signal to reduce the sampling error of the resampled data and improve the sampling accuracy. The OMP algorithm reconstructs the signal of the resampled data, simplifies the signal recovery process, and reduces the complexity of the algorithm.

[0050] In some possible embodiments, the cross wavelet transform can analyze the energy resonance and covariance distribution law of two groups of time series in the time-frequency space, and can reveal the consistency and correlation of the frequency periods of the two groups of sequences on different time scales. Therefore, this embodiment uses the cross wavelet transform to obtain a discrete signal with a discrete sequence number, specifically including: performing a continuous wavelet transform on the sampled data to obtain two groups of discrete time series, and performing a cross wavelet transform on the two groups of discrete time series to obtain a discrete signal with a discrete sequence number. By extracting the consistency and correlation of the frequency periods of the two groups of sequences on different time scales, the regularity of the sampled signal is improved and the difficulty of subsequent processing is reduced.

[0051] In some possible embodiments, determining the sampling step and interpolation interval of a discrete signal specifically includes: constructing an NCO loop, whose function is to produce a sampling interval; inputting the discrete signal into the NCO loop, performing an interpolation operation through an interpolation filter at time t1 to obtain the interpolation yt1 at time t1, performing a timing error detection in the NCO loop after the interpolation operation according to a timing error detector, and performing loop filtering of the timing error through a loop filter to obtain a calibration error; inputting the calibration error into a numerically controlled oscillator to obtain a sampling step and an interpolation interval calculated according to the interpolation yt1; repeating the steps to detect the timing error in the NCO loop until the timing error is detected to be less than a set threshold, and outputting the sampling step and interpolation interval. Among them, the initial value of the numerically controlled oscillator register is set to 1, that is, the depth of the numerically controlled oscillator register is 1, and when the value of the numerically controlled oscillator register passes through the zero point, the value of the numerically controlled oscillator register of the next symbol period is obtained. This is the position where the discrete signal is resampled, that is, the sampling step and interpolation interval.

[0052] In some possible embodiments, determining the offset value according to the sampling step size and the interpolation interval includes:

[0053] Performing compression measurement on the sampling signal according to the sampling step length and the interpolation interval to obtain a compressed sampling signal;

[0054] The compressed sampled signal is sparsely transformed to obtain the offset value. The sampled signal is compressed and measured, and the resource overhead of the high-dynamic navigation and short message signal capture algorithm can be effectively reduced by compressing the sampled signal. The compression method can accurately reconstruct the complete signal by selecting relatively few random sampling points, thereby significantly reducing the amount of signal sampling data and greatly saving the time and cost of signal transmission and processing.

[0055] In some possible embodiments, performing compressive measurement on the sampled signal according to the sampling step size and the interpolation interval specifically includes:

[0056] Resampling the sampled signal according to the sampling step size and the interpolation interval to obtain a resampled signal;

[0057] Splitting the resampled signal, and splicing adjacent resampled signals after the splitting;

[0058] Get the local pseudo code sequence, split it, and put the splitted sequence into the local pseudo code sequence with double zero padding;

[0059] Perform circular correlation operation on the spliced ​​resampled signal and the double zero-filled local pseudo code sequence to obtain a correlation matrix;

[0060] Perform FFT operation on each column of the correlation matrix, extract the maximum value of FFT output by peak detection, and use it as the compressed sampling signal. The block correlation method can reduce the number of operation points of subsequent FFT, and the non-periodic problem of pseudo-random sequence after block is solved by zero padding.

[0061] In some possible embodiments, since the compressed sampling signal itself is usually not sparse, it is necessary to use sparse transformation to make it conform to the sparse characteristics. Signal sparse representation is a method of representing a signal as a sparse vector. Compared with other signal representation methods, signal sparse representation can better compress the representation signal, thereby saving storage space, and can describe complex signals in a more concise way. Signal sparse representation can remove the influence of signal noise through filtering, parity inversion, and polynomial interpolation, thereby improving the quality of the signal. By performing a sparse basis transformation on the image, the image can be represented as a sparse vector, thereby achieving image compression and noise suppression.

[0062] Among them, the sparse transformation of the signal includes: extracting the maximum value of the FFT output through peak detection to determine the Doppler frequency shift; according to the Doppler frequency shift range, the Doppler frequency shift range is equally divided to obtain the Doppler step, and the Doppler frequency deviation vector is determined according to the Doppler step; the frequency deviation matrix is ​​constructed according to the Doppler vector, and the compressed sampling signal is sparsely changed using the frequency deviation matrix. The sparse change of the compressed sampling signal using the frequency deviation matrix specifically includes: obtaining the number of sampling points L of the compressed sampling signal, cyclically shifting the local pseudo code vector of L sampling points to construct the code phase matrix; according to the code phase matrix, taking the variable frequency signal of L sampling points to obtain the correlation vector after the code phase is stripped; according to the frequency deviation matrix, the signal after the code phase is stripped is Doppler frequency deviation stripped to obtain the offset value. Due to the high relative flight speed between the low-orbit satellite and the navigation satellite, the signal transmitted between the communicating parties has a large frequency deviation due to the Doppler frequency shift. The Doppler frequency deviation error will affect the correlation value of the signal, so it is necessary to compensate for the Doppler frequency deviation. It speeds up the signal acquisition speed by segment matching. However, the frequency coverage of the PMF-FFT algorithm is related to the number of matching segments. The more segments there are, the larger the frequency coverage. When the Doppler frequency deviation is large, the resource overhead of the algorithm is also large. This embodiment studies the Doppler frequency deviation range, constructs a frequency deviation matrix according to the Doppler vector, and uses the frequency deviation matrix to perform sparse changes on the compressed sampling signal, thereby reducing resource overhead.

[0063] In some possible embodiments, signal reconstruction is mainly a process of processing the offset value through the OMP algorithm, restoring the signal correlation peak, solving the signal code phase and Doppler frequency deviation, and reconstructing the original signal.

[0064] A second aspect of this embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a rate synchronization resampling method based on satellite communication is implemented.

[0065] A third aspect of the present embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a rate synchronization resampling method based on satellite communication.

[0066] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A rate synchronization resampling method based on satellite communication, characterized in that: The specific steps include: Acquire a sampling signal, pre-process the sampling signal, and obtain a discrete signal with a discrete sequence number; Construct an NCO loop based on the Gardner bit synchronization algorithm to determine the sampling step size and interpolation interval of discrete signals; Determine the offset value according to the sampling step size and the interpolation interval, and restore and reconstruct the original signal in combination with the OMP algorithm, including: based on the OMP algorithm, restore the signal correlation peak according to the offset value, solve the signal code phase and Doppler frequency deviation, and reconstruct the original signal; Specifically, The step of obtaining a discrete signal with a discrete sequence number includes: performing a continuous wavelet transform on the sampled data to obtain two groups of discrete time series, and performing a cross wavelet transform on the two groups of discrete time series to obtain a discrete signal with a discrete sequence number; The step of determining the sampling step and interpolation interval of the discrete signal specifically includes: Construct an NCO loop and perform interpolation operation on the discrete signal to obtain the interpolation yt1 at the current moment; Detect the timing error in the NCO loop and obtain the calibration error by loop filtering. Combined with the calibration error, numerically controlled oscillation is used to obtain the sampling step size and the interpolation interval calculated based on the interpolation yt1; Repeat the steps to detect the timing error in the NCO loop until it is detected that the timing error is less than the set threshold, and output the sampling step size and interpolation interval; Determining the offset value according to the sampling step length and the interpolation interval includes: Performing compression measurement on the sampling signal according to the sampling step length and the interpolation interval to obtain a compressed sampling signal; Perform sparse transformation on the compressed sampling signal to obtain an offset value; The compressing and measuring the sampled signal according to the sampling step length and the interpolation interval specifically includes: Resampling the sampled signal according to the sampling step size and the interpolation interval to obtain a resampled signal; Splitting the resampled signal, and splicing adjacent resampled signals after the splitting; Get the local pseudo code sequence, split it, and put the splitted sequence into the local pseudo code sequence with double zero padding; Perform circular correlation operation on the spliced ​​resampled signal and the double zero-filled local pseudo code sequence to obtain a correlation matrix; Perform FFT operation on each column of the correlation matrix, and extract the maximum value of FFT output by peak detection as the compressed sampling signal; The sparse transformation of the compressed sampling signal comprises: The maximum value of the FFT output is extracted by peak detection to determine the Doppler shift; According to the Doppler frequency shift range, the Doppler frequency shift range is equally divided to obtain the Doppler step, and the Doppler frequency deviation vector is determined according to the Doppler step; Constructing a frequency offset matrix according to the Doppler vector, and using the frequency offset matrix to perform sparse changes on the compressed sampling signal; The method of using the frequency offset matrix to perform sparse changes on the compressed sampling signal specifically includes: The number of sampling points L of the compressed sampling signal is obtained, and a local pseudo code vector having a length of L sampling points is cyclically shifted to construct a code phase matrix; According to the code phase matrix, a frequency conversion signal with a length of L sampling points is taken to obtain a correlation vector after code phase stripping; The Doppler frequency offset is stripped from the signal after stripping the code phase according to the frequency offset matrix to obtain an offset value.

2. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the rate synchronization resampling method based on satellite communication as claimed in claim 1 is implemented.

3. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the rate synchronization resampling method based on satellite communication as claimed in claim 1 is implemented.

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