A GNSS pseudo-code blind estimation method, device, equipment and storage medium

Abstract

The present application relates to a GNSS pseudocode blind estimation method, apparatus, device, and storage medium. The method comprises: obtaining the pseudocode estimation value of the I / Q branch of each sampling point through pseudocode symbol judgment; for any branch, counting the pseudocode estimation values ​​of all sampling points in each code chip of the current branch, and obtaining the initial pseudocode estimation value of each code chip of the current branch through discrete integral operation; constructing two types of local code sequences corresponding to any code chip through positive and negative polarity assumptions and reconstructing and generating two types of local navigation signals; multiplying the received signal of each sampling point with the two types of local navigation signals of any code chip of the current branch point by point and accumulating them to obtain the two types of signal correlation values ​​of any code chip, and performing pseudocode symbol correction judgment on any code chip based on the difference between the two types of signal correlation values ​​to obtain the corrected pseudocode estimation value of any code chip of the current branch. This method can reduce the bit error rate and improve the accuracy of pseudocode estimation.

Description

Technical Field

[0001] The present application relates to the technical field of satellite navigation pseudocode estimation, and in particular to a GNSS pseudocode blind estimation method, apparatus, device and storage medium. Background Art

[0002] In non-cooperative GNSS (Global Navigation Satellite System) signal reception, accurate estimation of pseudo-code sequences is the key to achieving signal synchronization, demodulation, and navigation information extraction.

[0003] A typical existing approach is to separate the I / Q branch signals and leverage their orthogonality to directly determine the corresponding branch's pseudo-code sequence symbol based on the positive and negative polarity of the I / Q branch baseband signals. This method can effectively recover the pseudo-code sequence under ideal conditions, but in low signal-to-noise ratio (SNR) environments, noise can cause errors in the I / Q branch polarity determination, thereby affecting the accuracy of the pseudo-code estimation. Furthermore, the bit error rate (BER) of pseudo-code estimation exhibits a monotonically decreasing relationship with the SNR, and the theoretical limit of pseudo-code estimation performance is clear. When the SNR falls below a certain threshold, the BER rises sharply, making it difficult to meet the high-precision requirements of satellite navigation pseudo-code estimation. Summary of the Invention

[0004] Based on this, it is necessary to provide a GNSS pseudo-code blind estimation method, device, equipment and storage medium that can reduce the bit error rate and improve the accuracy of pseudo-code estimation in order to address the above technical problems.

[0005] A GNSS pseudocode blind estimation method, the method comprising:

[0006] Receive orthogonally modulated GNSS signals and perform sampling;

[0007] Separate the I / Q branch baseband signals from the received signals at each sampling point through orthogonal demodulation;

[0008] Perform pseudo code symbol judgment on the I / Q branch baseband signal to obtain the I / Q branch pseudo code estimation value at each sampling point;

[0009] For any branch, the pseudo code estimated values ​​of all sampling points in each chip of the current branch are counted, and the initial pseudo code estimated value of each chip of the current branch is obtained by discrete integration operation;

[0010] By making positive and negative polarity assumptions on the initial pseudo-code estimate of any chip in the current branch, two types of local code sequences corresponding to any chip are constructed, and two types of local navigation signals are reconstructed based on the two types of local code sequences.

[0011] The received signal of each sampling point is multiplied point by point with the two types of local navigation signals of any code chip of the current branch and accumulated to obtain the two types of signal correlation values ​​of any code chip. The pseudo-code symbol correction decision is performed on any code chip based on the difference between the two types of signal correlation values ​​to obtain the corrected pseudo-code estimate value of any code chip of the current branch.

[0012] In one embodiment, receiving and sampling a quadrature modulated GNSS signal includes:

[0013] Receive the orthogonally modulated GNSS signal and perform sampling to obtain the received signal at each sampling point, which is expressed as:

[0014] ;

[0015] in, For the The received signal of each sampling point; is the power of the P(Y) code sequence modulated by the I branch, is the power of the C / A code sequence modulated by the Q branch; and represent the P(Y) code sequence and the C / A code sequence respectively; Indicates the duration of the sampling point, is the sampling rate; and The data codes are P(Y) code sequence and C / A code sequence respectively; is the carrier frequency, is the Doppler shift, is the carrier center frequency; is complex Gaussian noise with mean 0 and variance .

[0016] In one embodiment, separating the I / Q branch baseband signals from the received signal at each sampling point by orthogonal demodulation includes:

[0017] Through quadrature demodulation, the The received signal at each sampling point The I / Q branch baseband signals in are expressed as:

[0018] ;

[0019] ;

[0020] in, and Respectively represent The I-branch baseband signal and the Q-branch baseband signal of the sampling points; ,and and Respectively represent The I branch complex Gaussian noise and the Q branch complex Gaussian noise of the sampling points.

[0021] In one embodiment, performing pseudo code symbol determination on the I / Q branch baseband signal to obtain an I / Q branch pseudo code estimation value at each sampling point includes:

[0022] Respectively The baseband signal of the I branch at each sampling point and Q branch baseband signal Make pseudo code symbol decisions respectively and obtain the Pseudocode estimation value of the P(Y) code sequence of the I branch at sampling points and the estimated pseudo code value of the C / A code sequence of the Q branch , respectively expressed as:

[0023] ;

[0024] ;

[0025] in, is a sign function, for any real number , ; is the real number space.

[0026] In one embodiment, counting pseudo code estimation values ​​of all sampling points in each chip of the current branch and obtaining an initial pseudo code estimation value of each chip of the current branch by discrete integration operation includes:

[0027] When the current branch is the I branch, the pseudo code estimation values ​​of the P(Y) code sequence of all sampling points in each chip of the I branch are counted and averaged through discrete integral operation to obtain the pseudo code estimation mean of all sampling points in each chip, which is expressed as:

[0028] ;

[0029] in, Indicates the m The estimated mean value of the pseudo code of the P(Y) code sequence of all sampling points in the code chip, Indicates the number of sampling points in each chip, is the sampling rate, is the bit rate; is the floor function, is the ceiling function;

[0030] based on Make pseudo code symbol judgment and get the The initial estimated value of the pseudo code of the P(Y) code sequence of chips is expressed as:

[0031] .

[0032] In one embodiment, by making positive and negative polarity assumptions on the initial estimated pseudo code value of any chip of the current branch, two types of local code sequences corresponding to any chip are constructed, and two types of local navigation signals are reconstructed based on the two types of local code sequences, including:

[0033] By The initial estimated values ​​of the pseudo-code of the P(Y) code sequence of the first code chip are assumed to be positive or negative, while the initial estimated values ​​of the pseudo-code of the P(Y) code sequence of the remaining code chips remain unchanged, and the I branch is constructed. The two types of local code sequences corresponding to the chips are positive and negative polarities, respectively, and are expressed as:

[0034] ;

[0035] in, and Respectively represent the I branch A positive local code sequence and a negative local code sequence of chips;

[0036] According to the two types of local code sequences, the I branch is reconstructed and generated. The two types of local navigation signals of the chip are expressed as:

[0037] ;

[0038] ;

[0039] in, and Represent the positive local navigation signal and the negative local navigation signal respectively. Represents a time series of pseudo-code samples.

[0040] In one embodiment, the received signal at each sampling point is multiplied point by point with the two types of local navigation signals of any chip of the current branch and then accumulated to obtain correlation values ​​of the two types of signals for any chip, and a pseudo-code symbol correction decision is performed on any chip based on the difference between the two types of signal correlation values ​​to obtain a corrected pseudo-code estimate value of any chip of the current branch, including:

[0041] The first The received signal at each sampling point I branch The two types of local navigation signals of the chip are multiplied point by point and accumulated to obtain the I branch The two types of signal correlation values ​​of chips are expressed as:

[0042] ;

[0043] ;

[0044] in, and Respectively represent the I branch The positive signal correlation value and the negative signal correlation value of each chip; is the total number of sampling points;

[0045] The difference between the correlation values ​​of the two types of signals is defined as:

[0046] ;

[0047] based on The positive and negative conditions of the I branch The code chips are used to perform pseudo code symbol correction and judgment, and the first The pseudo code estimate of the P(Y) code sequence after chip correction is expressed as:

[0048] .

[0049] A GNSS pseudocode blind estimation device, comprising:

[0050] A signal receiving and sampling module is used to receive and sample the orthogonally modulated GNSS signal;

[0051] A demodulation and separation module is used to separate the I / Q branch baseband signals from the received signal of each sampling point through orthogonal demodulation;

[0052] A preliminary pseudo code estimation module is used to perform pseudo code symbol judgment on the I / Q branch baseband signal and obtain the I / Q branch pseudo code estimation value of each sampling point;

[0053] The discrete integral operation module is used to count the pseudo code estimation values ​​of all sampling points in each chip of the current branch for any branch, and obtain the initial pseudo code estimation value of each chip of the current branch through discrete integral operation;

[0054] A hypothesis reconstruction module is used to construct two types of local code sequences corresponding to any code chip by making positive and negative polarity assumptions on the initial estimated pseudo code value of any code chip of the current branch, and reconstruct two types of local navigation signals based on the two types of local code sequences;

[0055] The pseudo code estimation and correction module is used to multiply the received signal of each sampling point with the two types of local navigation signals of any code chip of the current branch point by point and accumulate them to obtain the two types of signal correlation values ​​of any code chip, and perform pseudo code symbol correction judgment on any code chip based on the difference between the two types of signal correlation values ​​to obtain the corrected pseudo code estimation value of any code chip of the current branch.

[0056] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0057] Receive orthogonally modulated GNSS signals and perform sampling;

[0058] Separate the I / Q branch baseband signals from the received signals at each sampling point through orthogonal demodulation;

[0059] Perform pseudo code symbol judgment on the I / Q branch baseband signal to obtain the I / Q branch pseudo code estimation value at each sampling point;

[0060] For any branch, the pseudo code estimated values ​​of all sampling points in each chip of the current branch are counted, and the initial pseudo code estimated value of each chip of the current branch is obtained by discrete integration operation;

[0061] By making positive and negative polarity assumptions on the initial pseudo-code estimate of any chip in the current branch, two types of local code sequences corresponding to any chip are constructed, and two types of local navigation signals are reconstructed based on the two types of local code sequences.

[0062] The received signal of each sampling point is multiplied point by point with the two types of local navigation signals of any code chip of the current branch and accumulated to obtain the two types of signal correlation values ​​of any code chip. The pseudo-code symbol correction decision is performed on any code chip based on the difference between the two types of signal correlation values ​​to obtain the corrected pseudo-code estimate value of any code chip of the current branch.

[0063] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0064] Receive orthogonally modulated GNSS signals and perform sampling;

[0065] Separate the I / Q branch baseband signals from the received signals at each sampling point through orthogonal demodulation;

[0066] Perform pseudo code symbol judgment on the I / Q branch baseband signal to obtain the I / Q branch pseudo code estimation value at each sampling point;

[0067] For any branch, the pseudo code estimated values ​​of all sampling points in each chip of the current branch are counted, and the initial pseudo code estimated value of each chip of the current branch is obtained by discrete integration operation;

[0068] By making positive and negative polarity assumptions on the initial pseudo-code estimate of any chip in the current branch, two types of local code sequences corresponding to any chip are constructed, and two types of local navigation signals are reconstructed based on the two types of local code sequences.

[0069] The received signal of each sampling point is multiplied point by point with the two types of local navigation signals of any code chip of the current branch and accumulated to obtain the two types of signal correlation values ​​of any code chip. The pseudo-code symbol correction decision is performed on any code chip based on the difference between the two types of signal correlation values ​​to obtain the corrected pseudo-code estimate value of any code chip of the current branch.

[0070] The above-mentioned GNSS pseudo-code blind estimation method, device, equipment and storage medium can effectively suppress the influence of random noise on the pseudo-code estimation performance in a low signal-to-noise ratio environment by counting the pseudo-code estimation values ​​of multiple sampling points in each code chip and performing discrete integration, thereby improving the accuracy and reliability of the initial pseudo-code estimation of a single code chip in a low signal-to-noise ratio environment. At the same time, the multiple sampling points in the code chip provide more complete statistical characteristics for subsequent pseudo-code correction, which is conducive to reducing the bit error rate of the pseudo-code estimation; further, by making positive and negative polarity assumptions on the initial pseudo-code estimation value of any code chip, reconstructing and generating local navigation signals with positive and negative polarities and performing correlation calculations with the received signals of each sampling point, it is possible to correct the polarity errors of the code chip pseudo-code initial estimation due to noise, multipath or quantization error based on the difference in correlation values, thereby further improving the accuracy of the pseudo-code estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 1 is a flow chart of a GNSS pseudocode blind estimation method according to an embodiment;

[0072] Figure 2 FIG. 1 is a schematic diagram showing the effect of I / Q branch pseudo-code estimation at each sampling point when the signal-to-noise ratio is -10 dB in an embodiment; wherein, Figure 2 (a) is a schematic diagram of the pseudo code estimation effect of the I branch. Figure 2 (b) is a schematic diagram of the pseudo code estimation effect of the Q branch;

[0073] Figure 3 A schematic diagram of pseudo code estimation performance of an existing method under different signal-to-noise ratios in one embodiment;

[0074] Figure 4 Schematic diagram of pseudo code estimation performance under different sampling rates and different signal-to-noise ratios after correction of the present application in one embodiment;

[0075] Figure 5 Schematic diagram of pseudo code estimation performance gain under different sampling rates and different signal-to-noise ratios after correction of the present application in one embodiment;

[0076] Figure 6 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0077] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0078] In one embodiment, Figure 1 As shown, a GNSS pseudocode blind estimation method is provided, comprising the following steps:

[0079] Step S1: receiving a quadrature modulated GNSS signal and performing sampling.

[0080] The sampling rate of the received signal can be set according to the signal-to-noise ratio environment of the specific application of the pseudo code estimation. The higher the sampling rate, the more sampling points are provided within the code chip, which has more information and provides more complete statistical characteristics for pseudo code correction, thereby gradually reducing the bit error rate of the pseudo code estimation.

[0081] Step S2: Separate the I / Q branch baseband signals from the received signal at each sampling point through orthogonal demodulation.

[0082] Quadrature demodulation decomposes the received signal into two quadrature components (I (in-phase) and Q (quadrature)), multiplies them with the in-phase and quadrature components of the local carrier, and then extracts the baseband signal through low-pass filtering.

[0083] Step S3: Perform pseudo code symbol decision on the I / Q branch baseband signal to obtain the I / Q branch pseudo code estimation value of each sampling point.

[0084] The pseudo code estimation value of the I / Q branch at each sampling point is directly determined based on the positive and negative polarity of the I / Q branch baseband signal. Considering that in a low signal-to-noise ratio environment, noise may cause errors in the I / Q branch polarity judgment, thereby affecting the accuracy of the pseudo code estimation, further pseudo code estimation correction is required.

[0085] Step S4: for any branch, the pseudo code estimation values ​​of all sampling points in each chip of the current branch are counted, and the initial pseudo code estimation value of each chip of the current branch is obtained by discrete integration operation.

[0086] The discrete integral operation means averaging the pseudo-code estimation values ​​of all sampling points within the code chip. By integrating and averaging all sampling points within the code chip, it is beneficial to suppress the impact of random noise at the sampling points and improve the reliability of the pseudo-code estimation of a single code chip.

[0087] Step S5: By making positive and negative polarity assumptions on the initial estimated pseudo code value of any chip of the current branch, two types of local code sequences corresponding to any chip are constructed, and two types of local navigation signals are reconstructed based on the two types of local code sequences.

[0088] In step S6, the received signal of each sampling point is multiplied point by point with the two types of local navigation signals of any code chip of the current branch and accumulated to obtain the two types of signal correlation values ​​of any code chip, and the pseudo-code symbol correction judgment is performed on any code chip based on the difference between the two types of signal correlation values ​​to obtain the corrected pseudo-code estimate value of any code chip of the current branch.

[0089] In the above-mentioned GNSS pseudocode blind estimation method, by statistically analyzing the pseudocode estimates of multiple sampling points within each chip and performing discrete integration, the impact of random noise on pseudocode estimation performance in low signal-to-noise ratio environments can be effectively suppressed, thereby improving the accuracy and reliability of the initial pseudocode estimate for a single chip in low signal-to-noise ratio environments. At the same time, the multiple sampling points within the chip provide more complete statistical characteristics for subsequent pseudocode correction, which is conducive to reducing the bit error rate of the pseudocode estimation. Furthermore, by making positive and negative polarity assumptions for the initial pseudocode estimate of any chip, reconstructing local navigation signals with positive and negative polarity and performing correlation calculations with the received signals at each sampling point, it is possible to correct for polarity errors in the initial pseudocode estimate of the chip due to noise, multipath, or quantization error based on the differences in correlation values, further improving the accuracy of the pseudocode estimation.

[0090] In one embodiment, step S1 specifically includes: taking as an example receiving a QPSK (Quadrature Phase Shift Keying) modulated signal transmitted by a GPS satellite, the signal comprises two orthogonal components: the I branch modulates the P(Y) code (precision ranging code), and the Q branch modulates the C / A code (coarse acquisition code). The received signal is sampled to obtain the received signal at each sampling point, which is expressed as:

[0091] ;

[0092] in, For the The received signal of each sampling point; is the power of the P(Y) code sequence modulated by the I branch, is the power of the C / A code sequence modulated by the Q branch; and represent the P(Y) code sequence and the C / A code sequence respectively; Indicates the duration of the sampling point, is the sampling rate; and The data codes are P(Y) code sequence and C / A code sequence respectively; is the carrier frequency, is the Doppler shift, is the carrier center frequency; is complex Gaussian noise with mean 0 and variance .

[0093] In one embodiment, step S2 specifically includes: separating the first The received signal at each sampling point The I / Q branch baseband signals in are expressed as:

[0094] ;

[0095] ;

[0096] in, and Respectively represent The I-branch baseband signal and the Q-branch baseband signal of the sampling points; ,and and Respectively represent The I branch complex Gaussian noise and the Q branch complex Gaussian noise of the sampling points.

[0097] In one embodiment, step S3 specifically includes: The baseband signal of the I branch at each sampling point and Q branch baseband signal Make pseudo code symbol decisions respectively and obtain the Pseudocode estimation value of the P(Y) code sequence of the I branch at sampling points and the estimated pseudo code value of the C / A code sequence of the Q branch , respectively expressed as:

[0098] ;

[0099] ;

[0100] in, is a sign function, for any real number , ; This decision is essentially based on the minimum phase distance criterion for symbol decision. Although it can achieve pseudo code estimation of each sampling point to a certain extent, under low signal-to-noise ratio conditions (such as -10dB), Figure 2 As shown in FIG, there are many errors in the pseudo code estimation of the I / Q branch signal at each sampling point, which is caused by noise contaminating the phase of the sampling point. Therefore, the pseudo code estimation value needs to be further corrected. Figure 2 The horizontal axis represents the sampling point.

[0101] In one embodiment, step S4 includes: when the current branch is the I branch, first counting the pseudo code estimation values ​​of the P(Y) code sequence of all sampling points in each chip of the I branch and averaging them through discrete integral operation to obtain the pseudo code estimation mean value of all sampling points in each chip, which is expressed as:

[0102] ;

[0103] in, Indicates the All sampling points in the chip The estimated mean of the pseudo code sequence, Indicates the number of sampling points in each chip, is the sampling rate, is the bit rate; is the floor function, is a rounding function. Specifically, for the QPSK modulated signal transmitted by the GPS satellite, By taking the average, the influence of random noise on a single sampling point can be suppressed, and the decision reliability of a single chip can be improved.

[0104] Based on Make pseudo code symbol judgment and get the m The initial estimated value of the pseudo code of the P(Y) code sequence of chips is expressed as:

[0105] .

[0106] In one embodiment, step S5 includes: when the current branch is the I branch, first The initial estimated values ​​of the pseudo-code of the P(Y) code sequence of the first code chip are assumed to be positive or negative, while the initial estimated values ​​of the pseudo-code of the P(Y) code sequence of the remaining code chips remain unchanged, and the I branch is constructed. The two types of local code sequences corresponding to the chips are positive and negative polarities, respectively, and are expressed as:

[0107] ;

[0108] in, and Respectively represent the I branch The positive local code sequence and the negative local code sequence of the chip.

[0109] Then, the I branch is reconstructed based on the two types of local code sequences. The two types of local navigation signals of the chip are expressed as:

[0110] ;

[0111] ;

[0112] in, and Represent the positive local navigation signal and the negative local navigation signal respectively. Represents a time series of pseudo-code samples.

[0113] In one embodiment, step S6 includes: when the current branch is branch I, first The received signal at each sampling point Respectively with I branch The two types of local navigation signals of the chip are multiplied point by point and accumulated to obtain the I branch The two types of signal correlation values ​​of chips are expressed as:

[0114] ;

[0115] ;

[0116] in, and Respectively represent the I branch The positive signal correlation value and the negative signal correlation value of each chip; is the total number of sampling points.

[0117] Then, the difference between the correlation values ​​of the two types of signals is defined as:

[0118] ;

[0119] Finally, based on The positive and negative conditions of the I branch The code chips are used to perform pseudo code symbol correction and judgment, and the first The pseudo code estimate of the P(Y) code sequence after chip correction is expressed as:

[0120] .

[0121] Among them, by performing correlation calculations on the reconstructed positive and negative polarity local navigation signals and the received signals at each sampling point, it is possible to correct the polarity errors caused by noise, multipath or quantization errors in the initial estimation of the code chip pseudocode based on the difference in correlation values, thereby further improving the accuracy of the pseudocode estimation.

[0122] In order to verify the pseudo code estimation performance of the method proposed in this application, further experimental verification was carried out. Since the existing method directly performs pseudo code symbol judgment based on the minimum phase distance, its pseudo code estimation performance is only related to the signal-to-noise ratio. Therefore, the pseudo code estimation performance under different signal-to-noise ratios was simulated, as shown in the following figure. Figure 3As shown in the figure, the bit error rate is used to represent the code estimation performance. The lower the bit error rate, the better the code estimation performance. Figure 3 It shows that the pseudo code estimation performance of existing methods is low in low signal-to-noise ratio environment. Figure 4 This is a schematic diagram of the pseudo code estimation performance under different sampling rates and different signal-to-noise ratios after correction in this application, as shown in Figure 4 As shown in the figure, under a fixed signal-to-noise ratio, as the sampling rate increases, the bit error rate of the pseudo-code estimation gradually decreases. This is because the high sampling rate provides more sampling points within the code chip, which has more information and provides more complete statistical characteristics for pseudo-code correction. Figure 5 The bit error rate reduction shows the pseudo code estimation performance gain under different sampling rates and different signal-to-noise ratios after correction of this application, which is shown by Figure 5 It can be seen that under a fixed signal-to-noise ratio, the pseudo code estimation performance gain increases with the increase of sampling rate. This is due to the amount of correction information brought by the increase in the number of sampling points in the code, and the bit error rate can be reduced by up to 21.15%. Figure 4 and Figure 5 It can be seen that even in a low signal-to-noise ratio environment, the present application can improve the pseudo code estimation performance by increasing the sampling rate.

[0123] In one embodiment, a GNSS pseudocode blind estimation device is provided, comprising:

[0124] A signal receiving and sampling module is used to receive and sample the orthogonally modulated GNSS signal;

[0125] A demodulation and separation module is used to separate the I / Q branch baseband signals from the received signal of each sampling point through orthogonal demodulation;

[0126] A preliminary pseudo code estimation module is used to perform pseudo code symbol judgment on the I / Q branch baseband signal and obtain the I / Q branch pseudo code estimation value of each sampling point;

[0127] The discrete integral operation module is used to count the pseudo code estimation values ​​of all sampling points in each chip of the current branch for any branch, and obtain the initial pseudo code estimation value of each chip of the current branch through discrete integral operation;

[0128] A hypothesis reconstruction module is used to construct two types of local code sequences corresponding to any code chip by making positive and negative polarity assumptions on the initial estimated pseudo code value of any code chip of the current branch, and reconstruct two types of local navigation signals based on the two types of local code sequences;

[0129] The pseudo code estimation and correction module is used to multiply the received signal of each sampling point with the two types of local navigation signals of any code chip of the current branch point by point and accumulate them to obtain the two types of signal correlation values ​​of any code chip, and perform pseudo code symbol correction judgment on any code chip based on the difference between the two types of signal correlation values ​​to obtain the corrected pseudo code estimation value of any code chip of the current branch.

[0130] For the specific definition of a GNSS pseudocode blind estimation device, please refer to the definition of a GNSS pseudocode blind estimation method above, which will not be repeated here. The various modules in the above-mentioned GNSS pseudocode blind estimation device can be implemented in whole or in part by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0131] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a GNSS pseudocode blind estimation method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.

[0132] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0133] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0134] Receive orthogonally modulated GNSS signals and perform sampling;

[0135] Separate the I / Q branch baseband signals from the received signals at each sampling point through orthogonal demodulation;

[0136] Perform pseudo code symbol judgment on the I / Q branch baseband signal to obtain the I / Q branch pseudo code estimation value at each sampling point;

[0137] For any branch, the pseudo code estimated values ​​of all sampling points in each chip of the current branch are counted, and the initial pseudo code estimated value of each chip of the current branch is obtained by discrete integration operation;

[0138] By making positive and negative polarity assumptions on the initial pseudo-code estimate of any chip in the current branch, two types of local code sequences corresponding to any chip are constructed, and two types of local navigation signals are reconstructed based on the two types of local code sequences.

[0139] The received signal of each sampling point is multiplied point by point with the two types of local navigation signals of any code chip of the current branch and accumulated to obtain the two types of signal correlation values ​​of any code chip. The pseudo-code symbol correction decision is performed on any code chip based on the difference between the two types of signal correlation values ​​to obtain the corrected pseudo-code estimate value of any code chip of the current branch.

[0140] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0141] Receive orthogonally modulated GNSS signals and perform sampling;

[0142] Separate the I / Q branch baseband signals from the received signals at each sampling point through orthogonal demodulation;

[0143] Perform pseudo code symbol judgment on the I / Q branch baseband signal to obtain the I / Q branch pseudo code estimation value at each sampling point;

[0144] For any branch, the pseudo code estimated values ​​of all sampling points in each chip of the current branch are counted, and the initial pseudo code estimated value of each chip of the current branch is obtained by discrete integration operation;

[0145] By making positive and negative polarity assumptions on the initial pseudo-code estimate of any chip in the current branch, two types of local code sequences corresponding to any chip are constructed, and two types of local navigation signals are reconstructed based on the two types of local code sequences.

[0146] The received signal of each sampling point is multiplied point by point with the two types of local navigation signals of any code chip of the current branch and accumulated to obtain the two types of signal correlation values ​​of any code chip. The pseudo-code symbol correction decision is performed on any code chip based on the difference between the two types of signal correlation values ​​to obtain the corrected pseudo-code estimate value of any code chip of the current branch.

[0147] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0148] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0149] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person skilled in the art may make various modifications and improvements without departing from the scope of the present application, and such modifications and improvements are all within the scope of protection of the present application.

Claims

1. A GNSS pseudo-code blind estimation method, characterized in that: The method comprises: Receive orthogonally modulated GNSS signals and perform sampling; Separate the I / Q branch baseband signals from the received signals at each sampling point through orthogonal demodulation; Performing pseudo code symbol decision on the I / Q branch baseband signal to obtain an I / Q branch pseudo code estimation value at each sampling point; For any branch, the pseudo code estimated values ​​of all sampling points in each chip of the current branch are counted, and the initial pseudo code estimated value of each chip of the current branch is obtained by discrete integration operation; By making positive and negative polarity assumptions on the initial pseudo-code estimate of any chip in the current branch, two types of local code sequences corresponding to any chip are constructed, and two types of local navigation signals are reconstructed based on the two types of local code sequences. The received signal of each sampling point is multiplied point by point with the two types of local navigation signals of any code chip of the current branch and accumulated to obtain the two types of signal correlation values ​​of any code chip. The pseudo-code symbol correction decision is performed on any code chip based on the difference between the two types of signal correlation values ​​to obtain the corrected pseudo-code estimate value of any code chip of the current branch.

2. The method according to claim 1, characterized in that Receive and sample quadrature modulated GNSS signals, including: Receive the orthogonally modulated GNSS signal and perform sampling to obtain the received signal at each sampling point, which is expressed as: ； in, For the The received signal of each sampling point; is the power of the P(Y) code sequence modulated by the I branch, is the power of the C / A code sequence modulated by the Q branch; and represent the P(Y) code sequence and the C / A code sequence respectively; Indicates the duration of the sampling point, is the sampling rate; and The data codes are P(Y) code sequence and C / A code sequence respectively; is the carrier frequency, is the Doppler shift, is the carrier center frequency; is complex Gaussian noise with mean 0 and variance .

3. The method according to claim 2, characterized in that The I / Q branch baseband signals in the received signal at each sampling point are separated by orthogonal demodulation, including: Through quadrature demodulation, the The received signal at each sampling point The I / Q branch baseband signals in are expressed as: ； ； in, and Respectively represent The I branch baseband signal and the Q branch baseband signal of the sampling points; ,and and Respectively represent The I branch complex Gaussian noise and the Q branch complex Gaussian noise of the sampling points.

4. The method according to claim 3, characterized in that Performing pseudo code symbol determination on the I / Q branch baseband signal to obtain an I / Q branch pseudo code estimation value at each sampling point includes: Respectively The baseband signal of the I branch at each sampling point and Q branch baseband signal Make pseudo code symbol decisions respectively and obtain the Pseudocode estimation value of the P(Y) code sequence of the I branch at sampling points and the estimated pseudo code value of the C / A code sequence of the Q branch , respectively expressed as: ； ； in, is a sign function, for any real number , ; is the real number space.

5. The method according to claim 4, characterized in that Count the pseudo code estimated values ​​of all sampling points in each chip of the current branch, and obtain the initial pseudo code estimated value of each chip of the current branch through discrete integration operation, including: When the current branch is the I branch, the pseudo code estimation values ​​of the P(Y) code sequence of all sampling points in each chip of the I branch are counted and averaged through discrete integral operation to obtain the pseudo code estimation mean of all sampling points in each chip, which is expressed as: ； in, Indicates the m The estimated mean value of the pseudo code of the P(Y) code sequence of all sampling points in the code chip, Indicates the number of sampling points in each chip, is the sampling rate, is the bit rate; is the floor function, is the ceiling function; based on Make pseudo code symbol judgment and get the m The initial estimated value of the pseudo code of the P(Y) code sequence of chips is expressed as: 。 6. The method according to claim 5, characterized in that By making positive and negative polarity assumptions on the initial pseudo-code estimate of any chip in the current branch, two types of local code sequences corresponding to any chip are constructed. Two types of local navigation signals are reconstructed based on the two types of local code sequences, including: By The initial estimated values ​​of the pseudo-code of the P(Y) code sequence of the first code chip are assumed to be positive or negative, while the initial estimated values ​​of the pseudo-code of the P(Y) code sequence of the remaining code chips remain unchanged, and the I branch is constructed. The two types of local code sequences corresponding to the chips are positive and negative polarities, respectively, and are expressed as: ； in, and Respectively represent the I branch A positive local code sequence and a negative local code sequence of chips; According to the two types of local code sequences, the I branch is reconstructed and generated. The two types of local navigation signals of the chip are expressed as: ； ； in, and Represent the positive local navigation signal and the negative local navigation signal respectively. Represents a time series of pseudo-code samples.

7. The method according to claim 6, characterized in that The received signal at each sampling point is multiplied point by point with the two types of local navigation signals of any chip of the current branch and then accumulated to obtain the correlation value of the two types of signals of any chip. The pseudo-code symbol correction decision is performed on any chip based on the difference between the two types of signal correlation values ​​to obtain the corrected pseudo-code estimate of any chip of the current branch, including: The first The received signal at each sampling point Respectively with I branch The two types of local navigation signals of the chip are multiplied point by point and accumulated to obtain the I branch The two types of signal correlation values ​​of chips are expressed as: ； ； in, and Respectively represent the I branch The positive signal correlation value and the negative signal correlation value of each chip; is the total number of sampling points; The difference between the correlation values ​​of the two types of signals is defined as: ； based on The positive and negative conditions of the I branch The code chips are used to perform pseudo code symbol correction and judgment, and the first The pseudo code estimate of the P(Y) code sequence after chip correction is expressed as: 。 8. A GNSS pseudo-code blind estimation device, characterized in that: The device comprises: A signal receiving and sampling module is used to receive and sample the orthogonally modulated GNSS signal; A demodulation and separation module is used to separate the I / Q branch baseband signals from the received signal of each sampling point through orthogonal demodulation; A preliminary pseudo code estimation module is used to perform pseudo code symbol judgment on the I / Q branch baseband signal and obtain an I / Q branch pseudo code estimation value at each sampling point; The discrete integral operation module is used to count the pseudo code estimation values ​​of all sampling points in each chip of the current branch for any branch, and obtain the initial pseudo code estimation value of each chip of the current branch through discrete integral operation; A hypothesis reconstruction module is used to construct two types of local code sequences corresponding to any code chip by making positive and negative polarity assumptions on the initial estimated pseudo code value of any code chip of the current branch, and reconstruct two types of local navigation signals based on the two types of local code sequences; The pseudo code estimation and correction module is used to multiply the received signal of each sampling point with the two types of local navigation signals of any code chip of the current branch point by point and accumulate them to obtain the two types of signal correlation values ​​of any code chip, and perform pseudo code symbol correction judgment on any code chip based on the difference between the two types of signal correlation values ​​to obtain the corrected pseudo code estimation value of any code chip of the current branch.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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