CN112764068A

CN112764068A - GLONASS capture preprocessing method and device

Info

Publication number: CN112764068A
Application number: CN202011572620.4A
Authority: CN
Inventors: 宋挥师
Original assignee: Datang Semiconductor Design Co Ltd
Current assignee: Datang Semiconductor Design Co Ltd
Priority date: 2020-12-24
Filing date: 2020-12-24
Publication date: 2021-05-07

Abstract

Disclosed herein are a method and apparatus for GLONASS capture preprocessing, comprising: converting an input signal into a digital intermediate frequency signal through analog-to-digital conversion, and sending the digital intermediate frequency signal to at least one preprocessing branch; each preprocessing branch circuit executes preprocessing on the digital intermediate frequency signal, and the preprocessing comprises the following steps: mixing, selecting data to be output, filtering data of unwanted signals, down-sampling operation, and weighting operation; and storing the preprocessed data into a memory. In the application, the memory stores the data after down-sampling, the requirement on the storage space is small, the size of the memory can be reduced, and the hardware area of the receiver is further reduced.

Description

GLONASS capture preprocessing method and device

Technical Field

The invention relates to the technical field of navigation, in particular to a GLONASS capture preprocessing method and device.

Background

The Global Navigation Satellite System (GNSS) plays an increasingly irreplaceable important role in daily life of people, is applied to various industries, and particularly has an increasingly obvious role in the fields of Navigation, timing, surveying and mapping and the like. Currently, the Global Satellite NAvigation System mainly includes a Global Positioning System (GPS) System in the united states, a Bei Dou (BD) System in china, a Global NAvigation Satellite System (GLONASS) System in russia, and a Galileo (Galileo) System in europe. Among them, in China and Asia Pacific region, especially GPS and Beidou are widely applied; in Russia, GPS and GLONASS are used more frequently. At present, the Chinese Beidou navigation system moves to the world and actively develops global satellite navigation service; however, the european galileo navigation system is not mature yet and can not provide formal navigation services for a while. Of the four major satellite navigation systems, the GPS, BD and galileo all use Code Division Multiple Access (CDMA) signal systems, and only the GLONASS system uses Frequency Division Multiple Access (FDMA) signal systems.

FDMA signal systems require satellite signals to occupy a wider radio spectrum than CDMA signal systems. For example, the signal spectrum width of the GPS satellite is only 2.046MHz, the signal spectrum width of the BD satellite is also 4.092MHz, but the signal spectrum width of the GLONASS satellite reaches 8.3345 MHz. According to the nyquist sampling theorem, a wider signal spectrum requires a larger signal sampling rate, which may require more memory space, in order for aliasing of the signal spectrum to not occur, which increases the hardware complexity of the system.

Acquisition is an important function that is essential to navigation receivers. And only after the satellite signal acquisition is completed, the next satellite signal tracking can be carried out, so that the operations of positioning, constant speed and the like of the receiver are realized. Meanwhile, the starting time is an important index for measuring the navigation receiver. In order to shorten the start-up time of the navigation receiver, in the related art, the navigation receiver is usually configured with a plurality of satellite acquisition channels, that is, the receiver needs to acquire a plurality of satellites simultaneously. After the hardware is configured with a plurality of parallel acquisition channels, in order to acquire a plurality of satellites in parallel, the cooperation of an acquisition preprocessing unit is also needed.

For CDMA signals, since the signal spectra of all satellites overlap, the acquisition preprocessing scheme is simpler and the required sampling rate and memory space can be smaller. However, for FDMA signals, a larger signal sampling rate and a larger storage space are required to take care of the wider signal spectrum. In addition, the number of signal sample points required to be pre-stored for acquisition is very large, for example, data in excess of 100ms is required to be pre-stored, so it is important to reduce the size of the pre-storage space.

Disclosure of Invention

The invention provides a GLONASS capture preprocessing method and device, which can at least reduce the size of a pre-storage space and further reduce the hardware area of a receiver.

The invention provides a GLONASS capture preprocessing method, which comprises the following steps:

converting an input signal into a digital intermediate frequency signal through analog-to-digital conversion, and sending the digital intermediate frequency signal to at least one preprocessing branch;

each preprocessing branch circuit executes preprocessing on the digital intermediate frequency signal, and the preprocessing comprises the following steps: mixing, selecting data to be output, filtering data of unwanted signals, down-sampling operation, and weighting operation;

and storing the preprocessed data into a memory.

The invention also provides a GLONASS capture preprocessing device, which comprises:

an analog-to-digital converter;

at least one pre-processing branch, the pre-processing branch comprising: the device comprises a mixer, a data selector, a low-pass filter, a down-sampling unit and a weighting unit which are connected in sequence;

a memory;

the analog-to-digital converter is connected with the mixer of the at least one preprocessing branch, and the memory is respectively connected with the at least one preprocessing branch and used for storing the data after the weight operation of the weight quantization unit.

The invention also provides a navigation receiver which comprises the GLONASS acquisition preprocessing device.

In the embodiment of the invention, the memory stores the data after down-sampling, the requirement on the storage space is small, the size of the memory can be reduced, and the hardware area of the receiver is further reduced.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

Drawings

The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the example serve to explain the principles of the invention and not to limit the invention.

FIG. 1 is a schematic diagram illustrating a pre-processing procedure of GLONASS capture in the related art;

FIG. 2 is a flowchart illustrating a GLONASS capture pre-processing method according to an embodiment;

FIG. 3 is a schematic structural diagram of an embodiment of a GLONASS capture preprocessing apparatus;

FIG. 4 is a diagram illustrating an exemplary implementation of the GLONASS capture pre-processing in the first embodiment.

Detailed Description

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be noted that the embodiments and features of the embodiments in the present application may be arbitrarily combined with each other without conflict.

The steps illustrated in the flow charts of the figures may be performed in a computer system such as a set of computer-executable instructions. Also, while a logical order is shown in the flow diagrams, in some cases, the steps shown or described may be performed in an order different than here.

In the related art, the scheme of the capture preprocessing of GLONASS is shown in fig. 1. As shown in FIG. 1, the processing procedure of the GLONASS acquisition preprocessing scheme includes: the data is stored and then divided into a plurality of channels to be processed, wherein each channel corresponds to one satellite. The data stored in the memory includes navigation signals transmitted by all visible satellites. When data processing is performed, each sample point read from the memory is sent to all subsequent processing channels simultaneously.

The capture preprocessing scheme for GLONASS shown in fig. 1 is briefly described as follows: the signal input to the analog-to-digital converter is an analog intermediate frequency signal, and becomes a digital intermediate frequency signal after analog-to-digital conversion. The digital intermediate frequency signal sample points with a certain time length are stored in a memory for a plurality of subsequent processing branches. For each processing branch, the frequency mixing is carried out through a frequency mixer, the satellite signal corresponding to the current branch is moved to the vicinity of 0 frequency from the intermediate frequency, a low-pass filter is used for filtering out the signal which is useless for the current satellite, and finally the down sampling is carried out and the signal is sent to a capturing channel. Each satellite preprocessing branch corresponds to one acquisition channel.

In the above scheme of GLONASS acquisition preprocessing, the signal sampling rate of the memory is higher, so the memory space requirement is larger, resulting in an increase of the hardware area of the receiver. In order to solve the problem, the application provides a new GLONASS capture preprocessing scheme, which can reduce the size of a storage space and further reduce the hardware area of a receiver.

The following describes in detail an implementation of the technical solution of the present application.

Example one

The present embodiment provides a method for preprocessing GLONASS capture, as shown in fig. 2, which may include:

step 201, converting an input signal into a digital intermediate frequency signal through analog-to-digital conversion, and sending the digital intermediate frequency signal to at least one preprocessing branch;

step 202, each of the preprocessing branches performs preprocessing on the digital intermediate frequency signal, where the preprocessing includes: mixing, selecting data to be output, filtering data of unwanted signals, down-sampling operation, and weighting operation;

step 203, storing the preprocessed data into a memory.

In one implementation manner of this embodiment, the mixing is to shift the digital intermediate frequency signal to a desired frequency point; selecting data to output may include: selecting output data according to the number of satellites corresponding to each preprocessing branch; filtering out data of useless signals in the data through a low-pass filter; the down-sampling operation is to reduce the sampling rate of the filtered data to a predetermined level.

In an implementation manner of this embodiment, the weighting operation may include: and resetting the value of the data after the downsampling operation to be a corresponding preset value based on a preset quantization threshold value so as to reduce the data to a preset width. For example, when the data is to be reduced to 2 bits, the weighting operation may include: comparing the value of the data with a preset quantization threshold value; resetting the value of the data to-3 when the value of the data is less than the negative value of the quantization threshold value; resetting the value of the data to-1 when the value of the data is less than 0 but not less than the negative value of the quantization threshold value; resetting the value of the data to-1 when the value of the data is 0; resetting the value of the data to 1 when the value of the data is greater than 0 but not greater than the quantization threshold value; resetting the value of the data to 3 when the value of the data is greater than the quantization threshold value.

Here, the re-quantization operation may further include: and periodically adjusting the quantization threshold value to enable the value of the data subjected to the re-quantization operation based on the quantization threshold value to be in accordance with normal distribution. In this way, the quantization threshold value can be adaptively adjusted along with the amplitude change, so that the value of the data after the weighting operation conforms to the normal distribution, and the data can be applied to the acquisition of the satellite signal.

In one implementation of this embodiment, data from at least one of the preprocessing branches may be stored in parallel in the memory. In other words, the data from different preprocessing branches are stored in the memory in parallel, which helps to improve the utilization rate of the storage space.

In this embodiment, the selecting data to be output may include: when the current preprocessing branch corresponds to a satellite, selecting to output complex data; and when the current preprocessing branch corresponds to two or more satellites, selecting to output real part data.

In this embodiment, the method may further include: the data is read from the memory and sent as sample points to at least one capture channel. In practical application, the data of each preprocessing branch is taken as a sample point and sent to a capturing channel according to the number of satellites corresponding to each preprocessing branch. If a preprocessing branch corresponds to a plurality of satellites, the data of the preprocessing branch is sent to a plurality of acquisition channels corresponding to the plurality of satellites as sample points. If a preprocessing branch corresponds to a satellite, the data of the preprocessing branch is sent to an acquisition channel corresponding to the satellite as a sample point.

Accordingly, the present embodiment further provides a GLONASS capture preprocessing apparatus, as shown in fig. 3, which may include:

an analog-to-digital converter 31;

at least one pre-treatment branch 32, said pre-treatment branch comprising: a mixer 321, a data selector 322, a low-pass filter 323, a down-sampling unit 324, and a weighting unit 325 connected in sequence;

a memory 33;

the analog-to-digital converter 31 is connected to the mixer of the at least one preprocessing branch 32, and the memories 33 are respectively connected to the at least one preprocessing branch 32 and store the data after the quantization operation by the quantization unit 325.

In an implementation manner of this embodiment, the weighting unit 325 is configured to perform a weighting operation, where the weighting operation may include: and resetting the value of the data after the downsampling operation to be a corresponding preset value based on a preset quantization threshold value so as to reduce the data to a preset width. Here, the re-quantization unit 325 is configured to perform a re-quantization operation, and the re-quantization operation may further include: and periodically adjusting the quantization threshold value to enable the value of the data subjected to the re-quantization operation based on the quantization threshold value to be in accordance with normal distribution.

In an implementation manner of this embodiment, the memory 33 may store data from at least one of the preprocessing branches in parallel, so as to improve utilization of the storage space.

For further technical details of the GLONASS capture preprocessing apparatus of the present embodiment, reference may be made to the above method portion and the following example portion.

In this embodiment, the memory stores data after downsampling (i.e., sample points at the time of capture), and the memory has a small requirement for storage space, so that the size of the memory can be reduced, and the hardware area of the receiver can be reduced.

An exemplary implementation of the present embodiment is described below.

As shown in fig. 4, an exemplary implementation of the GLONASS capture pre-processing of the present embodiment is shown. Wherein the memory is placed after the down-sampling, where the signal sampling rate has been greatly reduced, the required memory space can be greatly reduced.

In an example shown in fig. 4, the GLONASS capture preprocessing means may include: analog-to-digital converter, many preliminary treatment branches and memory, wherein, analog-to-digital converter links to each other with the mixer of many preliminary treatment branches respectively, and every preliminary treatment branch includes: the device comprises a mixer, a data selector, a low-pass filter, a down-sampling unit and a weighting unit which are connected in sequence. The memory is connected with the output ends of the preprocessing branches and is externally connected with a plurality of capturing channels.

As in the example shown in fig. 4, the process of GLONASS capture pre-processing may include: the signal input to the analog-to-digital converter is an analog intermediate frequency signal, and becomes a digital intermediate frequency signal after analog-to-digital conversion. Then, the analog-to-digital converter sends the digital intermediate frequency signals to a plurality of preprocessing branches at the same time. Each pretreatment branch is respectively pretreated, and the pretreatment comprises the following steps: firstly, mixing frequency, and moving the digital intermediate frequency signal to a desired frequency point; then, the data selector selects the output data of the frequency mixer according to the satellite number corresponding to each preprocessing branch; then, according to the expected useful signal bandwidth, low-pass filtering processing is carried out on the data selected and output by the data selector, and data with out-of-band useless signals are filtered; next, performing a down-sampling operation to reduce the sampling rate of the data to a predetermined level; then, the weighting operation is executed to reduce the data width. And after each preprocessing branch finishes preprocessing, outputting the data after the weighting operation to a memory for storage. And finally, according to the configuration of each preprocessing branch, sending the data in the memory to a plurality of capturing channels, and executing corresponding capturing processing operation.

Each preprocessing branch may correspond to one or more GLONASS visible satellites. When the data selector selects the output data of the mixer, if the current preprocessing branch only corresponds to one satellite, real part data and imaginary part data (namely complex data) are output; and if the current preprocessing branch corresponds to a plurality of satellites, only real part data is output.

Here, the configuration of each preprocessing branch refers to that one preprocessing branch corresponds to several satellites, so that data in the memory is sent to the corresponding acquisition channel according to the configuration. In practice, the number of acquisition channels corresponds to the total number of visible satellites acquired in parallel. If one preprocessing branch corresponds to one satellite, one data of one preprocessing branch read out from the memory is taken as a sample point and sent to a corresponding capturing channel; if there are multiple satellites, one data of one preprocessing branch read from the memory is sent to multiple capture channels as a sample point.

In one implementation, the data after the weighting operation output by the preprocessing branches can be stored in the memory in parallel, the storage mode is more reasonable, and the storage space utilization rate is higher, so that the requirement on the storage space is further reduced.

The present embodiment will be described with reference to a specific example.

The code rate of the ranging code of GLONASS is 0.511Mbps, so the signal bandwidth of one satellite is 1.022 MHz; in order to ensure that the signals do not alias, the signal sampling rate of one satellite is at least 1.022 MHz. Meanwhile, the signal system adopted by GLONASS is FDMA, and the frequency point distribution of each satellite is shown in table 1.

TABLE 1

As can be seen from Table 1, the GLONASS signals occupy a spectrum within the range of (1598.0625-1605.375) MHz +/-0.511MHz, and have a bandwidth of 8.3345MHz in total for 14 satellites.

In this example, the sampling rate of the analog-to-digital converter (ADC) is chosen to be 24.5535MHz, the frequency point of the intermediate frequency is chosen to be 6.0225MHz, and the bit width of the analog-to-digital converter is 2 bits.

Taking 2 satellites corresponding to each preprocessing branch as an example, 7 preprocessing branches are needed for parallel capturing of 14 GLONASS satellites, and the GLONASS capturing preprocessing process may include:

first, the mixer performs a mixing operation.

In one implementation, an exemplary implementation of the mixing operation may be as follows:

the signal after ADC sampling is recorded as r (k), k is the sample point index, and the sampling rate is Fs. Here, the expected frequency point needs to be shifted to 0 frequency, so the expected frequency point is assumed to be f0, the f0 value of each preprocessing branch is different, and the frequency points of the mixer corresponding to each preprocessing branch are as shown in table 2 below, that is, the f0 value of each preprocessing branch is shown in table 2.

TABLE 2

The signal after digital mixing is denoted as s _ i (k) + j × s _ q (k), where k denotes the sample number, and the specific calculation formula of the digital mixing operation is as follows:

s_i(k)＝r(k)*cos(2*pi*k*f0/Fs)；

s_q(k)＝r(k)*sin(-2*pi*k*f0/Fs)。

where s _ i (k) is real data and s _ q (k) is imaginary data.

Secondly, the data selector selects the output data;

here, each preprocessing branch corresponds to 2 satellites, and the data selector only needs to select real part data to output, that is, select output data s _ i (k).

Thirdly, the data selected by the data selector enters a low-pass filter, and the low-pass filter filters data related to the out-of-band useless signals in the data;

in this example, each preprocessing branch corresponds to two satellites, and the signal bandwidth of the two satellites is 0.511 × 2+0.5625 — 1.5845MHz, so that the single-side bandwidth of the low-pass filter is 1.5845/2 — 0.79225 MHz. Here, the low-pass filter may be a Finite Impulse Response (FIR) filter. In addition, other types of low pass filters may be used as long as the bandwidth and sampling rate requirements are met.

Fourthly, the data filtered by the low-pass filter enters a down-sampling unit to perform down-sampling operation;

in this example, a 12-fold integer downsampling operation is selected to reduce the signal sampling rate to 24.5535 MHz/12-2.046125 MHz. Here, since 2.046125MHz >1.5845MHz, the signal is not contaminated.

Fifthly, the data after the down-sampling operation enters a weighting unit to carry out weighting operation;

in this example, the input real number data is weighted to a predetermined data width by the weighting operation. In this example, the data width is set to 2 bits. In other words, the input real data is quantized to 2 bits using a quantization operation.

Here, an exemplary implementation of a specific re-quantization is as follows: a quantization threshold value TH is set. The input sample point value is recorded as S (k), the re-quantized sample point value is recorded as S2(k), and the implementation process of 2-bit re-quantization may be as follows:

as can be seen from the above, only four values of-3, -1, 1 and 3 are obtained after quantization, so that only 2 bits are needed for representation.

In this embodiment, the quantization threshold TH may be adaptively adjusted according to the amplitude rule of the input signal. Here, the purpose of adaptive adjustment of the quantization threshold TH is to expect that the distribution of the values after the weighting is in accordance with the normal distribution, that is, the number of sample points having a value of 3, the number of sample points having a value of 1, and the number of sample points having a value of-3 and-1 are in accordance with the normal distribution, and the number of one or some values should not be too much or too little. The specific parameters can be obtained through theoretical derivation and experience according to the navigation signal rule.

In one implementation, the adaptive adjustment process of the quantization threshold TH may include: a threshold initial value and an adjustment period (e.g., one adjustment for 2000 sample points) are set. In each adjusting period, the sample point number ratio with the value of 3 or-3 after the weight quantization is counted is compared with a preset multi-gear ratio threshold value, and the quantization threshold value TH is correspondingly adjusted according to the comparison result, for example, is increased, reduced or kept unchanged. In the next adjustment period, the quantization threshold value TH obtained in the previous period is adjusted. The multi-gear ratio threshold value can be set according to needs, and the embodiment of the application does not limit the multi-gear ratio threshold value; when the quantization threshold TH is adjusted accordingly according to the comparison result, the adjustment may be performed according to the actual situation, which is not limited in the embodiment of the present application.

Sixthly, after the weighting operation is executed, the 2-bit data obtained by each preprocessing branch is stored in a memory in parallel.

In this example, the width of the 7 preprocessing branches is 14 bits, and the memory depth can be determined according to the number of sample points needing to be stored.

And finally, reading out data from the memory, and sending the data serving as a sample point to a corresponding capturing channel for capturing.

In practical applications, one acquisition channel searches for and acquires one satellite, and search acquisition (i.e., mixing) needs to be performed on carrier doppler, filtering processing (filtering operation can also be omitted) needs to be performed after mixing, and search correlation operation needs to be performed on code phases. When performing code phase search, the sampling rate needs to be further adjusted to 1.022MHz in order to save hardware resources. It should be noted that code doppler also causes local sampling rate changes, and the sampling rate needs to be adjusted.

The capture channel comprises a plurality of portions: mixer (remove carrier doppler), filter (may be omitted), resampling (adjust sampling rate to 1.022MHz), accumulating correlators. In this example, since one preprocessing branch corresponds to 2 satellites, after one data (i.e., a sample point) is read, the central frequency points of the satellite signals of two channels need to be shifted to 0 frequency, and this step can be completed by using a mixer in the capture channel; then, using a low-pass filter to filter out signals except for 0.511MHz (this step can be omitted); next, the sampling rate of 2.046125MHz is reduced to 1.022MHz in combination with code doppler, and this step can be accomplished by the aid of a resampling module; the last accumulation correlator also plays the role of a low-pass filter, and further filters signals which are useless for the current satellite.

As can be seen from the above example, if 1ms of data is stored, only 28645 bits need to be stored, whereas the related art scheme needs to store 49107 bits. Therefore, the embodiment can obviously reduce the storage space, and is especially obvious when the time length needing to be stored is large.

The method of this embodiment may be implemented by a navigation receiver.

The GLONASS capture preprocessing apparatus of this embodiment may be implemented by or disposed in a navigation receiver. In one implementation, the GLONASS capture pre-processing means may be implemented by a baseband digital signal processing module of the navigation receiver. The analog-to-digital converter 31, the mixer 321, the data selector 322, the low-pass filter 323, the down-sampling unit 324, the weighting unit 325, and the memory 33 may be software, hardware, or a combination of the two, respectively.

Other technical details of the present embodiment may refer to the first embodiment.

EXAMPLE III

The application also provides a navigation receiver which comprises the GLONASS acquisition preprocessing device. Specific technical details can be found in reference to the first embodiment and the second embodiment.

Although the embodiments of the present invention have been described above, the above description is only for the convenience of understanding the present invention, and is not intended to limit the present invention. 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

1. A method of GLONASS capture pre-processing, comprising:

each preprocessing branch circuit executes preprocessing on the digital intermediate frequency signal, and the preprocessing comprises: mixing, selecting data to be output, filtering data of unwanted signals, down-sampling operation, and weighting operation;

and storing the preprocessed data into a memory.

2. The method of claim 1,

the weighting operation comprises: and resetting the value of the data after the downsampling operation to be a corresponding preset value based on a preset quantization threshold value so as to reduce the data to a preset width.

3. The method of claim 2,

the weighting operation further comprises: and periodically adjusting the quantization threshold value to enable the value of the data subjected to the re-quantization operation based on the quantization threshold value to be in accordance with normal distribution.

4. The method of claim 1, wherein storing the pre-processed data in a memory comprises:

storing data from at least one of the preprocessing branches in parallel into the memory.

5. The method of claim 1,

the selecting data to be output includes: when the current preprocessing branch corresponds to a satellite, selecting to output complex data; and when the current preprocessing branch corresponds to two or more satellites, selecting to output real part data.

6. The method of claim 1, further comprising:

the data is read from the memory and sent as sample points to at least one capture channel.

7. A GLONASS capture preprocessing apparatus, comprising:

an analog-to-digital converter;

a memory;

8. The apparatus of claim 7, further comprising:

the weight quantization unit is used for executing weight quantization operation, and the weight quantization operation comprises the following steps: and resetting the value of the data after the downsampling operation to be a corresponding preset value based on a preset quantization threshold value so as to reduce the data to a preset width.

9. The apparatus of claim 7,

the weighting unit is used for executing weighting operation, and the weighting operation further comprises: and periodically adjusting the quantization threshold value to enable the value of the data subjected to the re-quantization operation based on the quantization threshold value to be in accordance with normal distribution.

10. The apparatus of claim 7, wherein:

the memory stores data from at least one of the preprocessing branches in parallel.

11. A navigation receiver, characterized in that the navigation receiver comprises the GLONASS acquisition preprocessing unit as claimed in any of claims 7 to 10.