GLONASS capture preprocessing method and apparatus

Abstract

This paper discloses a method and apparatus for GLONASS acquisition preprocessing, comprising: converting an input signal into a digital intermediate frequency (IF) signal via analog-to-digital conversion and sending it to at least one preprocessing branch; each preprocessing branch performing preprocessing on the IF signal, the preprocessing including: mixing, selecting data to be output, filtering data with useless signals, downsampling, and weighting; and storing the preprocessed data in a memory. In this application, the memory stores the downsampled data, which requires less storage space and can reduce the size of the memory, thereby reducing the hardware area of ​​the receiver.

Description

Technical Field

[0001] This invention relates to the field of navigation technology, and more particularly to a GLONASS capture preprocessing method and apparatus. Background Technology

[0002] Global Navigation Satellite Systems (GNSS) play an increasingly irreplaceable role in people's daily lives, finding applications across various industries, particularly in navigation, timing, and surveying. Currently, the main GNSS systems include the US Global Positioning System (GPS), China's BeiDou system, Russia's GLONASS system, and Europe's Galileo system. In China and the Asia-Pacific region, GPS and BeiDou are particularly widely used; while in Russia, GPS and GLONASS are more prevalent. Currently, China's BeiDou navigation system has expanded globally and is actively developing global satellite navigation services; while Europe's Galileo system is still immature and cannot yet provide formal navigation services. Of the four major satellite navigation systems mentioned above, GPS, BD, and Galileo all use Code Division Multiple Access (CDMA) signaling, while only GLONASS uses Frequency Division Multiple Access (FDMA) signaling.

[0003] Compared to CDMA, FDMA requires satellite signals to occupy a wider radio spectrum. For example, the signal spectrum width of GPS satellites is only 2.046MHz, and that of BD satellites is only 4.092MHz, but that of GLONASS satellites reaches 8.3345MHz. According to the Nyquist sampling theorem, to avoid signal spectrum aliasing, a wider signal spectrum requires a higher signal sampling rate, which may require more storage space, thus increasing the hardware complexity of the system.

[0004] Satellite acquisition is an essential function of navigation receivers. Only after successfully acquiring satellite signals can subsequent satellite tracking be performed, enabling operations such as positioning and velocity determination. Startup time is a crucial performance indicator for navigation receivers. To shorten startup time, navigation receivers are typically configured with multiple satellite acquisition channels, meaning they need to acquire multiple satellites simultaneously. After configuring multiple parallel acquisition channels, a pre-processing unit is also required to enable parallel acquisition of multiple satellites.

[0005] For CDMA signals, since the signal spectra of all satellites overlap, the acquisition and preprocessing scheme is relatively simple, requiring a smaller sampling rate and storage space. However, for FDMA signals, to accommodate a wider signal spectrum, a larger signal sampling rate and storage space are needed. Furthermore, the number of signal sample points that need to be pre-stored during acquisition is enormous, often exceeding 100ms of data. Therefore, reducing the size of the pre-stored space is crucial. Summary of the Invention

[0006] This invention provides a GLONASS acquisition preprocessing method and apparatus, which can at least reduce the size of the pre-storage space, thereby reducing the hardware area of ​​the receiver.

[0007] This invention provides a method for GLONASS capture preprocessing, comprising:

[0008] The input signal is converted from analog to digital to a digital intermediate frequency signal and sent to at least one preprocessing branch;

[0009] Each preprocessing branch performs preprocessing on the digital intermediate frequency signal, and the preprocessing includes: mixing, selecting data to be output, filtering data with useless signals, downsampling, and weighting.

[0010] The preprocessed data is stored in the memory.

[0011] The present invention also provides a GLONASS capture preprocessing apparatus, comprising:

[0012] Analog-to-digital converter;

[0013] At least one preprocessing branch, the preprocessing branch comprising: a mixer, a data selector, a low-pass filter, a downsampling unit, and a weighting unit connected in sequence;

[0014] Memory;

[0015] The analog-to-digital converter is connected to the mixer of the at least one preprocessing branch, and the memory is connected to the at least one preprocessing branch to store the data after the weighting operation of the weighting unit.

[0016] The present invention also provides a navigation receiver, which includes the above-described GLONASS capture preprocessing device.

[0017] In this embodiment of the invention, the memory stores the downsampled data, which requires less storage space and can reduce the size of the memory, thereby reducing the hardware area of ​​the receiver.

[0018] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0019] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of the present invention and do not constitute a limitation on the technical solutions of the present invention.

[0020] Figure 1 This is a schematic diagram of the GLONASS capture preprocessing process in related technologies;

[0021] Figure 2 This is a flowchart illustrating the GLONASS capture preprocessing method in Example 1.

[0022] Figure 3 This is a schematic diagram of the GLONASS capture preprocessing device in Example 1;

[0023] Figure 4 This is a schematic diagram illustrating an exemplary implementation of GLONASS capture preprocessing in Embodiment 1. Detailed Implementation

[0024] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

[0025] The steps illustrated in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases the steps shown or described may be performed in a different order than that presented here.

[0026] In related technologies, the GLONASS capture preprocessing scheme can be found in [link to relevant documentation]. Figure 1.like Figure 1 As shown, the GLONASS acquisition preprocessing scheme involves the following steps: first, storing the data; then, dividing the data into several channels for processing, with each channel corresponding to one satellite. The data stored in the memory includes navigation signals emitted by all visible satellites. During actual data processing, each sample point read from the memory is simultaneously sent to all subsequent processing channels.

[0027] The following is a brief introduction Figure 1 The GLONASS acquisition preprocessing scheme is shown below: The signal input to the analog-to-digital converter (ADC) is an analog intermediate frequency (IF) signal, which becomes a digital IF signal after ADC conversion. First, a certain length of digital IF signal sample points are stored in memory for use by several subsequent processing branches. For each processing branch, a mixer is used to shift the satellite signal corresponding to the current branch from the IF frequency to near 0 MHz. Then, a low-pass filter is used to filter out signals useless to the current satellite. Finally, downsampling is performed, and the signal is sent to the acquisition channel. Each satellite preprocessing branch corresponds to one acquisition channel.

[0028] In the aforementioned GLONASS acquisition preprocessing scheme, the signal sampling rate at the location of the memory is relatively high, thus requiring a large storage space and increasing the hardware area of ​​the receiver. To address this issue, this application proposes a new GLONASS acquisition preprocessing scheme that can reduce the storage space required, thereby reducing the hardware area of ​​the receiver.

[0029] The implementation method of the technical solution of this application will be described in detail below.

[0030] Example 1

[0031] This embodiment provides a method for GLONASS capture preprocessing, such as... Figure 2 As shown, it may include:

[0032] Step 201: Convert the input signal into a digital intermediate frequency signal via analog-to-digital conversion and send it to at least one preprocessing branch;

[0033] Step 202, each preprocessing branch performs preprocessing on the digital intermediate frequency signal, the preprocessing including: mixing, selecting data to be output, filtering data of useless signals, downsampling operation and weighting operation;

[0034] Step 203: Store the preprocessed data in the memory.

[0035] In one implementation of this embodiment, mixing involves shifting the digital intermediate frequency signal to a desired frequency point; selecting the data to be output may include: selecting the output data based on the number of satellites corresponding to each preprocessing branch; filtering out useless signal data from the data using a low-pass filter; and downsampling operation involves reducing the sampling rate of the filtered data to a predetermined level.

[0036] In one implementation of this embodiment, the weighting operation may include: resetting the value of the data after the downsampling operation to a corresponding predetermined value based on a preset quantization threshold, so as to reduce the data to a preset width. For example, to reduce the data to 2 bits, the weighting operation may include: comparing the value of the data with a preset quantization threshold; resetting the value of the data to -3 when the value of the data is less than a negative value of the quantization threshold; resetting the value of the data to -1 when the value of the data is less than 0 but not less than a negative value of the quantization threshold; 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; and resetting the value of the data to 3 when the value of the data is greater than the quantization threshold.

[0037] Here, the weighting operation may further include: periodically adjusting the quantization threshold value so that the value of the data after weighting based on the quantization threshold value conforms to a normal distribution. In this way, the quantization threshold value can be adaptively adjusted with amplitude changes so that the value of the data after weighting conforms to a normal distribution, allowing it to be applied to satellite signal acquisition.

[0038] In one implementation of this embodiment, data from at least one of the preprocessing branches can be stored in the memory in parallel. In other words, storing data from different preprocessing branches in parallel in the memory helps improve the utilization of storage space.

[0039] In this embodiment, selecting the data to be output may include: selecting to output complex data when the current preprocessing branch corresponds to one satellite; and selecting to output real data when the current preprocessing branch corresponds to two or more satellites.

[0040] In this embodiment, the method may further include: reading the data from the memory and sending the data as sample points to at least one acquisition channel. In practical applications, the data of each preprocessing branch is sent as sample points to the acquisition channel according to the number of satellites corresponding to each preprocessing branch. If a preprocessing branch corresponds to multiple satellites, then the data of that preprocessing branch is sent as sample points to multiple acquisition channels corresponding to those multiple satellites. If a preprocessing branch corresponds to one satellite, then the data of that preprocessing branch is sent as sample points to one acquisition channel corresponding to that satellite.

[0041] Accordingly, this embodiment also provides a GLONASS capture preprocessing device, such as... Figure 3 As shown, it may include:

[0042] Analog-to-digital converter 31;

[0043] At least one preprocessing branch 32, the preprocessing branch including: a mixer 321, a data selector 322, a low-pass filter 323, a downsampling unit 324, and a weighting unit 325 connected in sequence;

[0044] Memory 33;

[0045] The analog-to-digital converter 31 is connected to the mixer of the at least one preprocessing branch 32, and the memory 33 is connected to the at least one preprocessing branch 32 to store the data after the weighting operation of the weighting unit 325.

[0046] In one implementation of this embodiment, the weighting unit 325 is used to perform a weighting operation, which may include: resetting the value of the data after the downsampling operation to a corresponding predetermined value based on a preset quantization threshold value, so as to reduce the data to a preset width. Here, the weighting unit 325 is used to perform a weighting operation, which may further include: periodically adjusting the quantization threshold value so that the value of the data after the weighting operation based on the quantization threshold value conforms to a normal distribution.

[0047] In one implementation of this embodiment, the memory 33 can store data from at least one of the preprocessing branches in parallel to improve the utilization of storage space.

[0048] Other technical details of the GLONASS capture preprocessing apparatus described in this embodiment can be found in the Method section above and the Examples section below.

[0049] In this embodiment, the memory stores the data after downsampling (i.e., the sample points at the time of capture), which requires less storage space and can reduce the size of the memory, thereby reducing the hardware area of ​​the receiver.

[0050] The exemplary implementation of this embodiment will be described below.

[0051] like Figure 4 The diagram illustrates an exemplary implementation of GLONASS capture preprocessing in this embodiment. The memory is placed after downsampling, where the signal sampling rate is significantly reduced, thus greatly minimizing the required storage space.

[0052] As shown in the example in Figure 4, the GLONASS capture preprocessing unit may include an analog-to-digital converter (ADC), multiple preprocessing branches, and a memory. The ADC is connected to the mixers of each of the multiple preprocessing branches. Each preprocessing branch includes, in sequence, a mixer, a data selector, a low-pass filter, a downsampling unit, and a weighting unit. The memory is connected to the outputs of the multiple preprocessing branches and externally connected to multiple capture channels.

[0053] like Figure 4 In the example shown, the GLONASS acquisition preprocessing process can include: the input signal to the analog-to-digital converter (ADC) is an analog intermediate frequency (IF) signal, which is converted into a digital IF signal after ADC conversion. Then, the ADC simultaneously sends the digital IF signal to multiple preprocessing branches. Each preprocessing branch performs preprocessing, which includes: first, mixing to shift the digital IF signal to the desired frequency point; then, a data selector selects the output data of the mixer according to the number of satellites corresponding to each preprocessing branch; then, based on the desired useful signal bandwidth, low-pass filtering is performed on the data selected by the data selector to filter out out-of-band unwanted signal data; next, downsampling is performed to reduce the data sampling rate to a predetermined level; and then weighting is performed to reduce the data width. After each preprocessing branch completes preprocessing, the weighted data is output to memory for storage. Finally, according to the configuration of each preprocessing branch, the data in memory is sent to multiple acquisition channels to perform corresponding acquisition processing operations.

[0054] Each preprocessing branch can correspond to one or more GLONASS visible satellites. When the data selector selects the output data of the mixer, if the current preprocessing branch corresponds to only one satellite, it outputs both real and imaginary data (i.e., complex data); if the current preprocessing branch corresponds to multiple satellites, it outputs only the real data.

[0055] Here, the configuration of each preprocessing branch refers to how many satellites one preprocessing branch corresponds to, so that data in the memory can be sent to the corresponding acquisition channels according to this configuration. In practical applications, the number of acquisition channels corresponds to the total number of visible satellites acquired in parallel. If one preprocessing branch corresponds to one satellite, then a data point read from the memory of one preprocessing branch is sent as a sample point to the corresponding acquisition channel; if it corresponds to multiple satellites, then a data point read from the memory of one preprocessing branch is sent as a sample point to the corresponding multiple acquisition channels.

[0056] In one implementation, the weighted data output from multiple preprocessing branches can be stored in memory in parallel. This storage mode is more reasonable and has a higher storage space utilization rate, thereby further reducing the demand for storage space.

[0057] The following example illustrates this embodiment.

[0058] The ranging code rate of GLONASS is 0.511 Mbps, therefore the signal bandwidth of a single satellite is 1.022 MHz; to ensure that the signal does not aliasing, the signal sampling rate of a single satellite is at least 1.022 MHz. Meanwhile, GLONASS uses the FDMA signal standard, and the frequency distribution of its various satellites is shown in Table 1.

[0059]

[0060]

[0061] Table 1

[0062] As shown in Table 1, the spectrum range occupied by the GLONASS signal is (1598.0625~1605.375)MHz+ / -0.511MHz, with a total bandwidth of 8.3345MHz, and a total of 14 satellites.

[0063] In this example, the sampling rate of the analog-to-digital converter (ADC) is selected as 24.5535MHz, the intermediate frequency is selected as 6.0225MHz, and the bit width of the ADC is 2 bits.

[0064] Taking each preprocessing branch corresponding to 2 satellites as an example, parallel acquisition of 14 GLONASS satellites requires a total of 7 preprocessing branches. The GLONASS acquisition preprocessing process can include:

[0065] First, the mixer performs the mixing operation.

[0066] In one implementation, an exemplary implementation of the mixing operation can be as follows:

[0067] Let the signal sampled by the ADC be r(k), where k is the sample point index and the sampling rate is Fs. Here, we need to shift the desired frequency to frequency 0, so we can denote the desired frequency as f0. The f0 value is different for each preprocessing branch. The frequency of the mixer corresponding to each preprocessing branch is shown in Table 2 below. Table 2 gives the f0 value of each preprocessing branch.

[0068]

[0069]

[0070] Table 2

[0071] The signal after digital mixing is denoted as s_i(k) + j*s_q(k), where k represents the sampling point number. The specific calculation formula for the digital mixing operation is as follows:

[0072] s_i(k)=r(k)*cos(2*pi*k*f0 / Fs);

[0073] s_q(k)=r(k)*sin(-2*pi*k*f0 / Fs).

[0074] Where s_i(k) is the real part of the data and s_q(k) is the imaginary part of the data.

[0075] Second, the data selector selects the output data;

[0076] Here, each preprocessing branch corresponds to 2 satellites, so the data selector only needs to select the real data output, that is, select the output data s_i(k).

[0077] Third, the data selected by the data selector enters the low-pass filter, which filters out data related to out-of-band useless signals.

[0078] 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. Therefore, the one-sided bandwidth of the low-pass filter is 1.5845 / 2 = 0.79225MHz. Here, a finite impulse response (FIR) filter can be used as the low-pass filter. Besides this, other types of low-pass filters can also be used as long as the bandwidth and sampling rate requirements are met.

[0079] Fourth, the data filtered by the low-pass filter enters the downsampling unit for downsampling.

[0080] In this example, we choose an integer downsampling operation of 12, reducing the signal sampling rate to 24.5535MHz / 12 = 2.046125MHz. Here, since 2.046125MHz > 1.5845MHz, the signal will not be contaminated.

[0081] Fifth, the data after the downsampling operation enters the weighting unit for weighting operation;

[0082] In this example, the input real number data is weighted to a pre-defined data width using a weighting operation. In this example, the data width is set to 2 bits. In other words, the input real number data is weighted to 2 bits using a weighting operation.

[0083] Here is a specific example of a weighting implementation: A quantization threshold TH is set. Let the input sample point value be S(k), and the weighted sample point value be S2(k). The 2-bit weighting implementation process can be as follows:

[0084]

[0085] As can be seen from the above, after quantization, there are only four possible values: -3, -1, 1, and 3. Therefore, only 2 bits are needed to represent them.

[0086] In this embodiment, the quantization threshold TH can be adaptively adjusted according to the amplitude pattern of the input signal. The purpose of this adaptive adjustment of the quantization threshold TH is to ensure that the weighted numerical distribution conforms to a normal distribution. That is, the number of sample points with a value of 3, the number of sample points with a value of 1, and the number of sample points with values ​​of -3 and -1 should conform to a normal distribution, and the proportion of one or more values ​​should not be too high or too low. Specific parameters can be obtained through theoretical derivation and experience based on the characteristics of the navigation signal.

[0087] In one implementation, the adaptive adjustment process of the quantization threshold TH may include: first, setting an initial threshold value and an adjustment period (e.g., adjusting once every 2000 sample points). In each adjustment period, the proportion of sample points with a weighted value of 3 or -3 is statistically analyzed and compared with pre-set multi-level proportion threshold values. Based on the comparison results, the quantization threshold TH is adjusted accordingly, for example, by increasing, decreasing, or keeping it unchanged. In the next adjustment period, the quantization threshold TH obtained in the previous period is adjusted again. The multi-level proportion threshold values ​​can be set as needed, and this application embodiment does not limit this; when adjusting the quantization threshold TH according to the comparison results, adjustments can be made according to the actual situation, and this application embodiment does not limit this.

[0088] Sixth, after the weighting operation is completed, the 2 bits of data obtained from each preprocessing branch are stored in parallel into the memory.

[0089] In this example, the 7 preprocessing branches have a total width of 14 bits, and the memory depth can be determined according to the number of sample points that need to be stored.

[0090] Finally, the data is read from the memory and sent as a sample point to the corresponding capture channel for capture processing.

[0091] In practical applications, acquiring a satellite using a single acquisition channel requires carrier Doppler search and acquisition (i.e., mixing), followed by filtering (this filtering operation can be omitted), and code phase search-related operations. During code phase search, to conserve hardware resources, the sampling rate needs to be further adjusted to 1.022MHz. It should be noted that code Doppler also causes local sampling rate changes, requiring further sampling rate adjustments.

[0092] The acquisition channel consists of several parts: a mixer (to remove carrier Doppler), a filter (optional), resampling (to adjust the sampling rate to 1.022MHz), and an accumulator correlator. In this example, since one preprocessing branch corresponds to two satellites, after reading a data point (i.e., a sample point), the center frequency of the satellite signals in both channels needs to be shifted to 0. This step can be accomplished using the mixer in the acquisition channel. Then, a low-pass filter is used to filter out signals outside the 0.511MHz band (this step can be omitted). Next, the sampling rate of 2.046125MHz is reduced to 1.022MHz by combining the code Doppler; this step can be accomplished by the resampling module. Finally, the accumulator correlator also acts as a low-pass filter, further filtering out signals that are useless to the current satellite.

[0093] As can be seen from the above example, storing 1ms of data requires only 28,645 bits, while related solutions require 49,107 bits. Therefore, this embodiment can significantly reduce storage space, especially when the required storage time is very long.

[0094] The method in this embodiment can be implemented using a navigation receiver.

[0095] In this embodiment, the GLONASS acquisition preprocessing device can be implemented through a navigation receiver or integrated within the navigation receiver. In one implementation, the GLONASS acquisition preprocessing device can be implemented through the baseband digital signal processing module of the navigation receiver. The analog-to-digital converter 31, mixer 321, data selector 322, low-pass filter 323, downsampling unit 324, weighting unit 325, and memory 33 can be software, hardware, or a combination of both.

[0096] Other technical details of this embodiment can be found in Embodiment 1.

[0097] Example 3

[0098] This application also provides a navigation receiver that includes the aforementioned GLONASS acquisition preprocessing device. Specific technical details can be found in Embodiments 1 and 2.

[0099] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and changes to the form and details of the implementation without departing from the spirit and scope disclosed herein; however, the scope of patent protection of this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A method for GLONASS capture preprocessing, characterized in that, include: The input signal is converted from analog to digital to a digital intermediate frequency signal and sent to at least one preprocessing branch; Each of the preprocessing branches performs preprocessing on the digital intermediate frequency signal, the preprocessing including: mixing, selecting data to be output, filtering data with useless signals, downsampling, and weighting. The preprocessed data is stored in a memory; The weighting operation includes: periodically adjusting the quantization threshold value so that the value of the data after weighting based on the quantization threshold value conforms to a normal distribution; The selection of the data to be output includes: when the current preprocessing branch corresponds to one satellite, selecting to output complex data; when the current preprocessing branch corresponds to two or more satellites, selecting to output real data.

2. The method according to claim 1, characterized in that, The weighting operation further includes: resetting the value of the data after the downsampling operation to a corresponding predetermined value based on a pre-set quantization threshold value, so as to reduce the data to a pre-set width.

3. The method according to claim 1, characterized in that, The step of storing the preprocessed data into the memory includes: Data from at least one of the preprocessing branches are stored in parallel into the memory.

4. The method according to claim 1, characterized in that, The method further includes: The data is read from the memory and sent as sample points to at least one capture channel.

5. A GLONASS capture preprocessing apparatus, characterized in that, include: Analog-to-digital converter; At least one preprocessing branch, the preprocessing branch comprising: a mixer, a data selector, a low-pass filter, a downsampling unit, and a weighting unit connected in sequence; Memory; The analog-to-digital converter is connected to the mixer of the at least one preprocessing branch, and the memory is connected to the at least one preprocessing branch to store the data after the weighting operation of the weighting unit. The weighting unit is used to perform a weighting operation, which further includes: periodically adjusting the quantization threshold value so that the value of the data after the weighting operation based on the quantization threshold value conforms to a normal distribution. The data selector is used to select the data to be output, including: when the current preprocessing branch corresponds to one satellite, selecting to output complex data; when the current preprocessing branch corresponds to two or more satellites, selecting to output real data.

6. The apparatus according to claim 5, characterized in that, Also includes: The weighting unit is used to perform a weighting operation, which includes: resetting the value of the data after the downsampling operation to a corresponding predetermined value based on a preset quantization threshold value, so as to reduce the data to a preset width.

7. The apparatus according to claim 5, characterized in that: The memory stores data from at least one of the preprocessing branches in parallel.

8. A navigation receiver, characterized in that, The navigation receiver includes the GLONASS capture preprocessing device as described in any one of claims 5 to 7.

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