CN114280641A - Data block preprocessing method and system for Beidou satellite received signals - Google Patents
Data block preprocessing method and system for Beidou satellite received signals Download PDFInfo
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Abstract
The invention discloses a data block preprocessing method for Beidou satellite received signals, which comprises the following steps: separating the carrier waves of weak signals to be captured, and carrying out block processing on the separated signals; performing FFT (fast Fourier transform) on the signals after the block processing to obtain first data; performing FFT (fast Fourier transform) and complex conjugate transform on the local signal to obtain second data; multiplying the first data and the second data and carrying out IFFT transformation to obtain a coherent integration result; carrying out difference processing on the coherent integration result to obtain a first difference value and a second difference value; and comparing the maximum value of the first difference value and the second difference value with a preset threshold, and if the maximum value is greater than the preset threshold, successfully capturing. The method realizes the capture of the weak signals by adopting a mode of combining a half bit method and a differential phase dry method, reduces noise and loss, improves the capture capability of the weak signals with long data length by a practical block processing method, and is beneficial to reducing the operation amount and improving the capture speed.
Description
Technical Field
The invention belongs to the technical field of GNSS weak signal receiving and capturing, and particularly relates to a data block preprocessing method and system for Beidou satellite receiving signals.
Background
The application range of the Beidou as a global satellite navigation system is wider and wider at present, and the research on the receiving technology of the Beidou under a weak signal environment is stimulated by emergency rescue and future military requirements, so that the Beidou satellite navigation system becomes a research hotspot. The application of the high-sensitivity receiving technology in the Beidou receiver is particularly emphasized because the high-sensitivity receiving technology is not limited by environments and conditions. In the high-sensitivity Beidou receiver, the capture algorithm is positioned at the forefront of baseband processing, so that the efficient weak Beidou signal capture algorithm is the key for improving the performance of the high-sensitivity Beidou receiver. The strength of a common weak signal environment is about 20-30dB lower than that of an outdoor signal, and the carrier-to-noise ratio is less than 28dB-Hz, so that the common weak signal environment is regarded as a weak signal, and the high-sensitivity Beidou receiver obtains high signal processing gain mainly through a signal processing algorithm. Therefore, a method for capturing the Beidou satellite receiving signal is urgently needed.
Disclosure of Invention
The invention aims to provide a data block preprocessing method and system for Beidou satellite received signals, and aims to solve the problems in the prior art.
On one hand, in order to achieve the above purpose, the invention provides a data block preprocessing method for Beidou satellite received signals, which comprises the following steps:
separating the carrier waves of weak signals to be captured, and carrying out block processing on the separated signals;
performing FFT (fast Fourier transform) on the signals after the block processing to obtain first data;
performing FFT (fast Fourier transform) and complex conjugate transform on the local signal to obtain second data;
multiplying the first data and the second data and carrying out IFFT transformation to obtain a coherent integration result;
carrying out difference processing on the coherent integration result to obtain a first difference value and a second difference value;
and comparing the maximum value of the first difference value and the second difference value with a preset threshold, and if the maximum value is greater than the preset threshold, successfully capturing.
Optionally, before separating the carrier of the weak signal to be captured, the weak signal to be captured and the local signal are mixed and then separated, and the separation mode adopts low-pass filtering.
Optionally, the block processing includes performing block superposition on the separated signals with a data length of 1ms per block, and performing coherent integration on the signals after superposition.
Optionally, the process of multiplying the first data and the second data and performing IFFT includes:
multiplying the first data and the second data by adopting a block by block;
and performing IFFT transformation on the result of the block multiplication to obtain the coherent integration result.
Optionally, the process of performing difference processing on the coherent integration result to obtain the first difference value and the second difference value includes:
and the coherent integration result comprises a plurality of data blocks, and the coherent integration values of the adjacent data blocks are subjected to differential multiplication to obtain a differential result.
Optionally, in the process of differentially multiplying coherent integration values of adjacent data blocks, the data length of the data block is 1ms, and one of the two adjacent data blocks has no data jump;
the data blocks are labeled and comprise a first data block, a second data block and an Nth data block … …;
taking every two data blocks as a group, and carrying out differentiation by adopting a half-bit alternation method, wherein the method comprises the following steps:
differentiating the odd-numbered segments and the odd-numbered segments to obtain the first differential value;
and differentiating the even number segment and the even number segment to obtain the second differential value.
Optionally, the maximum value of the first difference value and the second difference value is compared with a preset threshold, and if the maximum value is smaller than the preset threshold, the doppler shift is moved and the doppler shift is acquired again.
On the other hand, in order to achieve the above object, the present invention provides a data block preprocessing system for Beidou satellite received signals, including:
the preprocessing module is used for separating the carrier waves of the weak signals to be captured and carrying out block processing on the separated signals;
the first transformation module is used for performing FFT transformation on the signals after the block processing to obtain first data, and performing FFT transformation and complex conjugate transformation on the local signals to obtain second data;
a second transform module, configured to perform IFFT transform on a product of the first data and the second data to obtain a coherent integration result;
the difference module is used for carrying out difference processing on the coherent integration result to obtain a first difference value and a second difference value;
and the capturing judgment module is used for comparing the larger value of the first difference value and the second difference value with a preset threshold, and judging that the capturing is successful if the larger value is larger than the preset threshold.
Optionally, the preprocessing module includes a separation module and a block processing module;
the separation module is used for mixing and separating the weak signal to be captured and the local signal;
the block processing module is used for carrying out block superposition on the separated signals according to the data length of 1ms of each block and carrying out coherent integration on the superposed signals.
Optionally, the difference module includes a half-bit alternation module, and the half-bit alternation module is configured to perform difference on the odd-numbered segments and the odd-numbered segments to obtain the first difference value; and differentiating the even number segment and the even number segment to obtain the second differential value.
The invention has the technical effects that:
the method realizes the capture of the weak signals by adopting a mode of combining a half bit method and a differential phase dry method, reduces noise and loss, improves the capture capability of the weak signals with long data length by a practical block processing method, and is beneficial to reducing the operation amount and improving the capture speed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application. In the drawings:
FIG. 1 is a flow chart of a method in an embodiment of the invention;
fig. 2 is a schematic structural diagram of a system according to an embodiment of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
As shown in fig. 1, the present embodiment provides a data block preprocessing method for a beidou satellite received signal, including:
separating the carrier waves of weak signals to be captured, and carrying out block processing on the separated signals;
performing FFT (fast Fourier transform) on the signals after the block processing to obtain first data;
performing FFT (fast Fourier transform) and complex conjugate transform on the local signal to obtain second data;
multiplying the first data and the second data and carrying out IFFT transformation to obtain a coherent integration result;
carrying out difference processing on the coherent integration result to obtain a first difference value and a second difference value;
and comparing the maximum value of the first difference value and the second difference value with a preset threshold, and if the maximum value is greater than the preset threshold, successfully capturing.
Before separating the carrier of the weak signal to be captured, the weak signal to be captured and the local signal are mixed and then separated, and the separation mode adopts low-pass filtering.
The block processing includes block-wise superimposing the separated signals with a data length of 1ms per block, and performing coherent integration on the superimposed signals.
The process of multiplying the first data and the second data and performing the IFFT includes:
multiplying the first data and the second data by adopting block by block;
and performing IFFT transformation on the result of the block multiplication to obtain a coherent integration result.
The process of carrying out difference processing on the coherent integration result to obtain a first difference value and a second difference value comprises the following steps:
the coherent integration result comprises a plurality of data blocks, and the coherent integration values of adjacent data blocks are subjected to differential multiplication to obtain a differential result.
In the process of differentially multiplying coherent integration values of adjacent data blocks, the data length of the data block is 1ms, and one of the two adjacent data blocks has no data jump;
the data blocks are labeled and comprise a first data block, a second data block and an Nth data block … …;
taking every two data blocks as a group, and carrying out differentiation by adopting a half-bit alternation method, wherein the method comprises the following steps:
differentiating the odd-numbered segments and the odd-numbered segments to obtain a first differential value;
and differentiating the even number section and the even number section to obtain a second differential value.
And comparing the maximum value of the first difference value and the second difference value with a preset threshold, and if the maximum value is smaller than the preset threshold, moving the Doppler frequency shift and re-capturing.
As shown in fig. 2, the present invention provides a data block preprocessing system for Beidou satellite received signals, including:
the preprocessing module is used for separating the carrier waves of the weak signals to be captured and carrying out block processing on the separated signals;
the first transformation module is used for performing FFT transformation on the signals after the block processing to obtain first data, and performing FFT transformation and complex conjugate transformation on the local signals to obtain second data;
the second transformation module is used for carrying out IFFT transformation on the product of the first data and the second data to obtain a coherent integration result;
the difference module is used for carrying out difference processing on the coherent integration result to obtain a first difference value and a second difference value;
and the capturing judgment module is used for comparing the larger value of the first difference value and the second difference value with a preset threshold, and judging that the capturing is successful if the larger value is larger than the preset threshold.
The pretreatment module comprises a separation module and a block processing module;
the separation module is used for mixing and separating the weak signal to be captured and the local signal;
the block processing module is used for carrying out block superposition on the separated signals according to the data length of 1ms of each block and carrying out coherent integration on the superposed signals.
The differential module comprises a half-bit alternating module, and the half-bit alternating module is used for differentiating the odd-numbered segments and the odd-numbered segments to obtain a first differential value; and differentiating the even number section and the even number section to obtain a second differential value.
The first factor to be considered in weak signal acquisition is the magnitude of the S/N ratio of the input satellite signal. Different S/N values of signal-to-noise ratio are adopted, and corresponding signal accumulation algorithms and parameters are adopted so as to obtain enough gain, so that the decision variable after processing can obtain the expected acquisition performance.
During capture, the signal-to-noise ratio gain and the capture sensitivity can be improved through superposition of multiple coherent operations of an accumulation algorithm.
Three common accumulation methods are: coherent integration, non-coherent integration, differential coherent integration.
Coherent integration can eliminate high-frequency components and noise of signals, is the most effective method for improving signal-to-noise ratio gain, and utilizes the property of strong autocorrelation of pseudo codes. And carrying out correlation operation between different code phases on certain section of data of the input signal and the local pseudo code, and if the maximum correlation peak value is larger than a threshold value, successfully capturing the satellite. The common Beidou signal can realize capturing only by data coherent integration with the length of 1ms, but when the signal power is low, the signal cannot be captured effectively by using the data of 1 ms. Weak signals require increased coherent integration time to obtain greater signal-to-noise gain.
The non-coherent integration removes phase information and only retains amplitude information, so that the integration time is not limited by navigation data bit flipping, and the non-coherent integration has high tolerance to residual Doppler, which is an advantage of the non-coherent integration.
Compared with coherent integration, the effect of improving the signal-to-noise ratio of a signal is not obvious as that of coherent integration because of square loss of incoherent integration.
Non-coherent integration to improve the tolerance to residual doppler shifts, non-coherent integration performs a squaring operation, causing a squaring loss. The length of the coherent integration time can not be increased endlessly, and is limited by the jump of navigation data bits.
Non-coherent integration is a compromise proposed for the limitation of coherent integration, and this method can perform data accumulation for a longer time, but since the noise of different data segments is superimposed in an energy manner in the non-coherent integration method, the total noise energy is increased, so that the signal-to-noise ratio gain of the non-coherent integration is not as good as that of coherent integration, that is, the square loss. Aiming at the problem of square loss of non-coherent integration, a differential coherent integration method is proposed, which mainly utilizes independence between noises of two adjacent segments of data and utilizes a method of multiplication of front and back delays to eliminate accumulation of the noises, but while the noises are suppressed, because the signal correlation of two adjacent segments of data is not as good as the autocorrelation of a segment of data, the accumulation of signal energy is not as much as that of coherent integration and non-coherent integration. Generally speaking, under the same accumulation time, the processing gain of coherent integration is maximum, the non-coherent integration is minimum, and the differential coherent integration is between the two.
In summary, coherent integration is the best in terms of signal-to-noise ratio gain, detection performance and computation amount, and in a weak signal environment, in order to obtain enough signal-to-noise ratio gain, the acquisition sensitivity is improved by increasing coherent integration time. However, because of the influence of navigation data bit hopping and residual doppler frequency shift, the coherent integration time generally cannot exceed 1ms, and in a weak signal environment, only coherent integration cannot meet the requirements, and non-coherent integration needs to be combined. The calculation amount of the non-coherent integration is large, the signal-to-noise ratio gain is small, and the navigation data bit jump is insensitive. The capture performance is not satisfactory. The differential coherent integration has smaller computation amount and incoherent phase, and can overcome the influence of navigation data bit turnover and effectively avoid the condition of low signal-to-noise ratio gain caused by incoherent integration square loss, so that the differential coherent integration is most suitable for capturing weak signals.
The Beidou signal strength under different conditions is shown in Table 1.
TABLE 1
It can be seen from table 1 that the signals in the room are mostly below-160 dBW and have a large relationship with the elevation angle of the satellite. For a common Beidou receiver, the power of a received signal at least needs to be more than-160 dBW, and the Beidou receiver can normally work, so that the Beidou receiver capable of normally working in a weak signal environment needs to be developed and researched.
For the Beidou LIC/A code signal, the typical signal power is-130 dBm (namely-160 dBW), and considering the noise of the antenna and the radio frequency front end, if the noise level is-174 dBm, the carrier-to-noise ratio is 44 dB-Hz. But the capture sensitivity of the conventional ordinary receiver is between 35dB-Hz-37dB-Hz at present. According to the data in the table 2, in the environment of city, canyon, viaduct, indoor and the like, the Beidou signal is shielded by the obstacle to cause attenuation (which can reach 20-30dB) in certain situations, so that the signal power becomes very weak. The weak signal capturing technology studied by the invention is just to capture the attenuated weak signal.
TABLE 2
The above description is only for the preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A data block preprocessing method for Beidou satellite received signals is characterized by comprising the following steps:
separating the carrier waves of weak signals to be captured, and carrying out block processing on the separated signals;
performing FFT (fast Fourier transform) on the signals after the block processing to obtain first data;
performing FFT (fast Fourier transform) and complex conjugate transform on the local signal to obtain second data;
multiplying the first data and the second data and carrying out IFFT transformation to obtain a coherent integration result;
carrying out difference processing on the coherent integration result to obtain a first difference value and a second difference value;
and comparing the maximum value of the first difference value and the second difference value with a preset threshold, and if the maximum value is greater than the preset threshold, successfully capturing.
2. The method according to claim 1, wherein the carrier of the weak signal to be captured is separated after mixing the weak signal to be captured with the local signal, and the separation is performed by low-pass filtering.
3. The method of claim 1, wherein the block processing comprises block-wise superimposing the separated signals at a data length of 1ms per block, and coherently integrating the superimposed signals.
4. The method of claim 1, wherein multiplying the first data and the second data and performing IFFT comprises:
multiplying the first data and the second data by adopting a block by block;
and performing IFFT transformation on the result of the block multiplication to obtain the coherent integration result.
5. The method of claim 1, wherein the differentiating the coherent integration result to obtain the first differential value and the second differential value comprises:
and the coherent integration result comprises a plurality of data blocks, and the coherent integration values of the adjacent data blocks are subjected to differential multiplication to obtain a differential result.
6. The method of claim 5, wherein during the differential multiplication of the coherent integration values of the adjacent data blocks, the data length of the data block is 1ms, and there is one of the adjacent data blocks in which no data transition occurs;
the data blocks are labeled and comprise a first data block, a second data block and an Nth data block … …;
taking every two data blocks as a group, and carrying out differentiation by adopting a half-bit alternation method, wherein the method comprises the following steps:
differentiating the odd-numbered segments and the odd-numbered segments to obtain the first differential value;
and differentiating the even number segment and the even number segment to obtain the second differential value.
7. The method of claim 1, wherein a maximum value of the first difference value and the second difference value is compared with a predetermined threshold, and if the maximum value is smaller than the predetermined threshold, moving doppler shift is performed for reacquisition.
8. The utility model provides a data block pretreatment of big dipper satellite received signal system which characterized in that includes:
the preprocessing module is used for separating the carrier waves of the weak signals to be captured and carrying out block processing on the separated signals;
the first transformation module is used for performing FFT transformation on the signals after the block processing to obtain first data, and performing FFT transformation and complex conjugate transformation on the local signals to obtain second data;
a second transform module, configured to perform IFFT transform on a product of the first data and the second data to obtain a coherent integration result;
the difference module is used for carrying out difference processing on the coherent integration result to obtain a first difference value and a second difference value;
and the capturing judgment module is used for comparing the larger value of the first difference value and the second difference value with a preset threshold, and judging that the capturing is successful if the larger value is larger than the preset threshold.
9. The system of claim 8, wherein the pre-processing module comprises a separation module and a block processing module;
the separation module is used for mixing and separating the weak signal to be captured and the local signal;
the block processing module is used for carrying out block superposition on the separated signals according to the data length of 1ms of each block and carrying out coherent integration on the superposed signals.
10. The system of claim 8, wherein the difference module comprises a half-bit alternation module configured to perform a difference on an odd segment and an odd segment to obtain the first difference value; and differentiating the even number segment and the even number segment to obtain the second differential value.
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