SSR short message coding and decoding method and device based on Beidou GSMC

Abstract

The invention discloses an SSR short message coding and decoding method and device based on Beidou GSMC, and relates to the technical field of satellite navigation and communication. Aiming at the high-precision positioning requirement of a scene without a ground base station, the invention constructs a cloud-end collaborative architecture in a breakthrough manner: a server side gathers multi-source SSR corrections through the Internet, and the data volume is compressed by more than 90% by combining an original SSR-OSR conversion algorithm with a newly proposed coding scheme; the user side generates a general position through pseudo-range single-point positioning and sends the general position to the server side, and the OSR correction with decimeter-level precision is issued through a Beidou GSMC short message. A user side fuses a GNSS observation value, a broadcast ephemeris and an OSR correction number, real-time precise single-point positioning without a ground base station is achieved, and the dynamic positioning precision reaches the decimeter level. According to the invention, breakthrough high-precision positioning support is provided for special scenes such as ocean exploration and emergency rescue.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of satellite navigation and communication technology, and particularly relates to a state space representation (SSR) short message encoding and decoding method and device based on Beidou Global Short Message Communication (GSMC). BACKGROUND

[0002] With the rapid development of global navigation satellite system (GNSS), precise point positioning (PPP) technology has become the core means to realize high-precision positioning. In the PPP technology, satellite orbit and clock error is a key factor affecting positioning accuracy, and real-time SSR correction can effectively correct these errors. At present, the international GNSS service (IGS) and multi-GNSS experiment (MGEX) analysis center (such as CAS, CNES, DLR, etc.) mainly broadcasts SSR correction through the Internet.

[0003] However, the existing technology faces several key bottlenecks: (1) strong network dependence, users cannot obtain SSR correction in real time in areas such as oceans, deserts, remote mountainous areas, etc. without stable Internet coverage; (2) bandwidth is severely limited, although the Beidou No. 3 GSMC function supports two-way communication in areas without network coverage, its single communication bandwidth is only 560 bits; (3) data capacity mismatch, traditional RTCM-SSR (Radio Technical Commission for Maritime Services-State Space Representation) format requires 6628 bits, far exceeding the short message transmission capacity; (4) insufficient real-time, existing encoding and decoding schemes are not optimized for narrow bandwidth, and it is difficult to meet the real-time requirements of high-precision positioning.

[0004] The current encoding and decoding scheme for Beidou short message has some shortcomings: (1) high data redundancy, no special compression algorithm is designed for SSR correction number characteristics; (2) weak anti-interference ability, transmission reliability is insufficient in complex electromagnetic environment; (3) poor scene adaptability, existing PPP technology relies on ground base stations or the Internet, and cannot meet the high-precision positioning needs in areas without network coverage.

[0005] There is an urgent need to develop an innovative SSR coding and decoding scheme, which can realize: (1) efficient transmission of SSR correction number under 560 bits of narrow bandwidth; (2) real-time decimeter-level positioning in network coverage-free areas; (3) improve the anti-interference ability in harsh environment; (4) break through the dependence of traditional PPP technology on ground base station. Solving the real-time transmission problem of SSR correction number under low bandwidth conditions has great value for promoting the application of Beidou system in key fields such as ocean navigation, geological exploration and emergency rescue, and is one of the core challenges of current satellite navigation technology development. SUMMARY

[0006] To solve the above technical problems, the present application provides a kind of based on Beidou GSMC's SSR short message coding and decoding method and device, by using BDS-3 GSMC full constellation real-time SSR correction number, more efficient correction number communication transmission is realized, thereby improve the reliability and stability of communication.

[0007] To achieve the above object, the technical scheme adopted by the present application is as follows:

[0008] A kind of based on Beidou GSMC's SSR short message coding and decoding method, the method comprises:

[0009] Step 1, service end receives multi-source SSR correction number stream in real time through Internet;

[0010] Step 2, user end is based on pseudorange single point positioning to generate sketchy position, and is encoded as Beidou GSMC short message and uploaded to service end;

[0011] Step 3, service end calculates satellite line-of-sight vector according to the sketchy position, converts SSR correction number stream into OSR correction number, and adopts dynamic bit width coding mechanism and first star full value-subsequent star difference differential layered coding mechanism to compress OSR correction number data, and is issued to user end;

[0012] Step 4, user end parses OSR (Observation Space Representation, observation space representation) correction number data, fuses GNSS observation value and broadcast ephemeris, realizes real-time precise single point positioning.

[0013] On the other hand, the present application provides a kind of based on Beidou GSMC's SSR short message coding and decoding device, applied to the based on Beidou GSMC's SSR short message coding and decoding method described above, comprising:

[0014] The receiving module is used to make the service end receive multi-source SSR correction number stream in real time through Internet;

[0015] The transmission module is used to make user end generate sketchy position based on pseudorange single point positioning, and is encoded as Beidou GSMC short message and uploaded to service end;

[0016] a conversion module for enabling the server to calculate a satellite line-of-sight vector according to the approximate position, convert the SSR correction stream into an OSR correction, compress the OSR correction data using a dynamic bit-width encoding mechanism and a first-star full-differential and subsequent-star differential hierarchical encoding mechanism, and deliver the data to the user terminal;

[0017] a positioning module for enabling the user terminal to parse the OSR correction data, fuse GNSS observations and broadcast ephemeris, and realize real-time precise point positioning.

[0018] In a third aspect, the present application provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned method for encoding and decoding SSR short messages based on Beidou GSMC.

[0019] In a fourth aspect, the present application provides a computer-readable storage medium having stored executable instructions, which, when executed by a processor, enable the processor to implement the aforementioned method for encoding and decoding SSR short messages based on Beidou GSMC.

[0020] The present application has the following advantages:

[0021] Efficient data compression: By converting SSR corrections into OSR distance corrections, the data volume is reduced by 90%, effectively solving the contradiction between the BDS-3 short message bandwidth (560 bits) and the SSR correction requirement (6628 bits), and significantly improving the transmission efficiency.

[0022] Real-time: Using the two-way communication function of BDS-3 GSMC, the user terminal can upload the approximate position in real time, and the server can dynamically generate and broadcast optimized OSR corrections, realizing high-frequency (1 minute interval) real-time data updating and meeting the timeliness requirements of high-precision positioning.

[0023] Global coverage and high precision: Free from dependence on the Internet or ground base stations, the corrections can be directly broadcast through Beidou short messages, enabling dynamic decimeter-level precise point positioning (PPP) in areas without network coverage such as oceans and remote areas, and expanding the application scenarios of high-precision navigation.

[0024] Anti-interference and high reliability: The optimized encoding and decoding scheme reduces data transmission redundancy and enhances anti-interference capability, ensuring stable reception and analysis of corrections in complex communication environments. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 is a schematic diagram of a "cloud-terminal" collaborative architecture based on Beidou GSMC;

[0026] Figure 2 A flowchart of an efficient encoding and decoding scheme for a cloud-edge collaborative architecture;

[0027] Figure 3 Design schematic diagram of encoding and decoding scheme suitable for BeiDou GSMC;

[0028] Figure 4 This is a comparison chart of error sequences from the MAL2 single-BeiDou real-time dynamic PPP test at two stations based on two coding schemes;

[0029] Figure 5 This is a statistical diagram showing the horizontal and vertical accuracy of each IGS station. Detailed Implementation

[0030] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0031] This invention proposes an SSR short message encoding and decoding method based on BeiDou GSMC, which, compared to traditional SSR broadcasting schemes that rely on the Internet, offers advantages such as... Figure 1 As shown, this method innovatively proposes a "cloud-edge" collaborative architecture, utilizing the BeiDou-3 Global Short Message Communication (GSMC) channel and employing spatial projection and data compression technologies to achieve efficient transmission of SSR correction data, significantly improving the reliability of positioning services in areas without network coverage. Specifically, the method includes:

[0032] Step 1: The server receives multi-source SSR correction data streams in real time via the Internet, including satellite orbit, clock bias, and code deviation parameters.

[0033] Real-time aggregation of SSR corrections broadcast by IGS and MGEX analysis centers; key parameters such as orbit error and clock error are processed. At present, there are many IGS / MGEX analysis centers (International GNSS Service / Multi-GNSS Experiment) providing real-time SSR RTS correction (State Space Representation Real-Time Service), such as CAS, CNES, DLR, BKG, WHU, GMV, etc. The server uses GDDS software with multi-thread parallel processing function, simultaneously receives SSR RTS correction broadcast by multiple IGS / MGEX analysis centers, and performs SSR integration, including comprehensive evaluation of the stability, completeness and product accuracy of each SSR product data stream, so as to select SSR correction with strong reliability and high continuity, and prepare for subsequent SSR conversion to OSR. In the face of a large number of real-time SSR corrections, appropriate strategies need to be adopted for comprehensive utilization. Due to the inevitable network communication interruption of Internet transmission, there will be a lot of missing SSR products from some analysis centers. The present application relates to a multi-analysis center SSR product selection optimization strategy.

[0034] Step 2, the user end generates a rough position based on the pseudo-range single point positioning (SPP, Single Point Positioning) technology, encodes it into a Beidou GSMC short message and uploads it to the server. Thanks to the two-way communication function of the BDS-3 short message service, the user end GSMC device of the present application has the functions of collecting BDS / GNSS observation values and broadcast ephemeris, and sending information to the server. Therefore, the user's rough position can be sent to the server, preparing for the subsequent SSR conversion to OSR data source, so as to promote the implementation of the efficient encoding scheme of the server, which specifically includes:

[0035] Step 2.1, the user end calculates the rough position based on the BDS / GNSS pseudo-range observation value through least square estimation (typical accuracy: horizontal 10 meters, height 15 meters);

[0036] Step 2.2, encode the rough position into a Beidou GSMC short message (occupying ≤560 bits), upload it to the server through short message communication, and trigger the server to start user-specific correction calculation.

[0037] Step 3, the server calculates the satellite line-of-sight vector according to the approximate position, converts the SSR correction stream into OSR correction, and adopts the dynamic bit width encoding (DBWE) mechanism and the full-volume of the first satellite-differential for subsequent satellites hierarchical encoding (FDHE) mechanism to compress the OSR correction data and issue it to the user end; since the communication bandwidth of the BDS-3 GSMC short message is only 560 bits, in order to efficiently transmit the SSR correction, the data transmission amount must be compressed, and the application proposes to convert the large-capacity SSR correction into small-capacity OSR correction based on the approximate position of the user, and then use the self-developed compact encoding and decoding scheme to encode the OSR correction into the BDS-3 GSMC short message, and broadcast it to the user at a communication interval of 1 min, which greatly reduces the dependence on the communication bandwidth. Specifically includes:

[0038] Step 3.1, the server calculates the satellite line-of-sight vector (LOS) according to the approximate position of the user, projects the SSR orbit / clock difference correction number into one-dimensional distance domain OSR correction, and realizes the compression of data dimension.

[0039] The server calculates the satellite line-of-sight vector (Line-of-Sight Vector, LOS) based on the approximate position of the user, and fuses the SSR format orbit correction number (three-dimensional) and clock difference correction number (one-dimensional) into unified one-dimensional distance domain observation space correction number (Observation-Space Representation, OSR) through projection transformation, realizing the data compression from multi-dimensional correction number to single dimension. Among them: formula (1) defines the projection conversion principle of SSR orbit / clock difference correction number to OSR; formula (2) describes the clock difference compression strategy: based on time domain polynomial fitting (such as second-order polynomial) to extrapolate the clock difference trend; formula (3) describes the orbit compression strategy: based on spatial domain polynomial surface fitting to model the spatial distribution characteristics of the orbit correction number.

[0040] Converting the SSR correction number in the state domain into one-dimensional distance correction number OSR can significantly reduce the redundancy of the data. The mathematical essence is the dot product projection of the LOS vector and the SSR error vector:

[0041] (1)

[0042] In the formula, represents one-dimensional distance correction number, This represents the line-of-sight (LOS) vector from the satellite to the user. It represents the three-dimensional position error of satellite orbit (ECEF, Earth-Centered Earth-Fixed, ECEF, geocentric Earth-Fixed coordinate system). This represents the satellite clock error (speed of light × time difference).

[0043] To adapt to the bandwidth limitations of BeiDou-3 short messages, OSR corrections are further compressed based on spatiotemporal polynomials. The core of this approach is to fit the spatiotemporal variation trend of the OSR corrections using Taylor expansion, transmitting only the polynomial coefficients rather than the original observations. The fitting is first performed in the time domain (clock bias dominant term):

[0044] (2)

[0045] In the formula, The OSR correction for clock bias is represented by the number of clock errors. express OSR baseline value at time 10:00 This represents the rate of change of OSR (clock drift effect). This indicates OSR acceleration (the effect of clock drift rate). This indicates the accuracy loss term.

[0046] Then, the spatial correlation of OSR within the user region grid is fitted using spatial domain fitting (with orbital error as the dominant term):

[0047] (3)

[0048] In the formula, This represents the OSR correction for the orbital. Indicates the OSR value at the grid center point. These represent the gradients in the east-west and north-south directions, respectively. Indicates cross-coupling terms. These represent the user's approximate location (x, y) relative to a reference grid point ( The change in ).

[0049] Step 3.2: Compress OSR correction data using DBWE and FDHE mechanisms.

[0050] "Cloud-edge" collaborative architecture, such as Figure 2 As shown, Figure 3 This paper presents an efficient data structure design based on DBWE-allocated OSR corrections, representing an innovation in data coding within the field of satellite positioning. The core invention lies in hierarchical modular coding and a dynamic scaling mechanism, which will be analyzed in two parts below:

[0051] I. Dynamic Bit Width Coding Mechanism (DBWE).Figure 3 The data block in the data block is divided into 4 logical layers according to function: (1) header fixed area, containing signal correction number type, epoch time, satellite number (N) and other fields, fixed length 30 bits, ensuring fast analysis of basic information. (2) Satellite data dynamic area, first satellite full record: containing satellite number (PRN, Pseudo-Random Noise) + ephemeris data period number (IODE, Issue of Data Ephemeris) + observation space correction number (OSR), the length of each satellite is 13+X bits (X is the extension bit of OSR correction number); subsequent satellite incremental compression: only PRN differential value + OSR differential value is retained, the length of each satellite is 8+X bits. The key invention point is to reduce the redundancy of broadcast data volume by using the space-time correlation of correction number through differential value calculation. (3) Protocol reserved area, supporting future new fields (such as encryption identification, enhanced service type). (4) CRC (Cyclic Redundancy Check, Cyclic Redundancy Check) check area, 24-bit cyclic redundancy check code, covering all data blocks, anti-transmission error.

[0052] II. First star full value-subsequent star differential hierarchical encoding mechanism (FDHE). The dynamic area adopts the compression strategy of "first star full value + subsequent star differential", and the total length is defined by the formula: total length = 30 + first satellite (13+X) + subsequent satellite (N-1) x (8+X) + reserved length + 24. It has the following technical advantages: (1) Space efficiency is improved. When the number of satellites (N) increases, only 8+X bits are required for subsequent satellites (5 bits less than the first star), which can save about 35% bandwidth in a 100-satellite scenario. (2) Analysis real-time, fixed header length (30 bits) makes the receiver quickly lock the data start, and the differential structure reduces the decoding calculation complexity. (3) Flexible expansion, X is a variable parameter (such as X=12 represents 0.1mm level precision), which can adapt to different precision requirements; the reserved area supports protocol backward compatibility.

[0053] Step 3.3, encapsulate 12 satellite OSR data + check bit (total ≤560 bits), and send it to the user end through GSMC short message single frame. Single transmission of 12 satellite OSR data only needs 546 bits (including check bits), which is compressed by 91.7% compared with the RTCM-SSR format of 6628 bits, which is completely suitable for Beidou GSMC 560 bit short message capacity.

[0054] Step 4, the user terminal parses the OSR correction number, fuses the GNSS observation value and the broadcast ephemeris, and realizes real-time precise point positioning (RT-PPP); the user receives the observation value of the BDS / GNSS satellite, the broadcast ephemeris, and the OSR correction number from the service terminal, and performs real-time precise point positioning, so as to obtain dynamic decimeter-level positioning accuracy (without ground reference station) based on a single receiver in the global range. Specifically, it includes:

[0055] Step 4.1, the user terminal parses the OSR correction number, fuses the BDS / GNSS carrier phase and pseudorange observation value, and broadcast ephemeris, and constructs a dual-frequency ionosphere-free combination observation model;

[0056] Step 4.2, the user position is solved in real time by using the robust Kalman filter (Robust Kalman Filter), and a decimeter-level positioning result is output. The PPP technology adopts the robust Kalman filter, a mature algorithm, as a parameter estimation method. By dynamically fusing the multi-frequency BDS / GNSS satellite observation value (pseudorange, carrier phase) and external precise products (such as satellite orbit / clock error), the position, velocity, clock error and atmospheric delay of the receiver are estimated in real time. Its advantage lies in that it can effectively suppress the observation noise, solve the positioning continuity problem in the dynamic environment, and maintain the positioning accuracy when the satellite signal is temporarily interrupted, thereby providing high-robust real-time positioning capability for PPP. The specific principle can be referred to the related literature.

[0057] On the other hand, the application also relates to a SSR short message coding and decoding device based on the Beidou GSMC, each part of the device can realize each step of the foregoing method, and specifically includes:

[0058] The receiving module is used for enabling the service terminal to receive the multi-source SSR correction number stream in real time through the Internet;

[0059] The transmission module is used for enabling the user terminal to generate a rough position based on pseudorange point positioning, encode the rough position into a Beidou GSMC short message, and upload the short message to the service terminal;

[0060] The conversion module is used for enabling the service terminal to calculate a satellite line-of-sight vector according to the rough position, convert the SSR correction number stream into an OSR correction number, compress the OSR correction number data by using a dynamic bit width coding mechanism and a first star full value-subsequent star differential hierarchical coding mechanism, and deliver the OSR correction number data to the user terminal;

[0061] The positioning module is used for enabling the user terminal to parse the OSR correction number data, fuse the GNSS observation value and the broadcast ephemeris, and realize real-time precise point positioning.

[0062] Embodiment:

[0063] Single BDS PPP simulation dynamic positioning test, select the six global distribution of IGS station observation value (2025 year of 152-158), respectively, to the proposed coding scheme and the original RTCM-SSR scheme real-time simulation dynamic BDS PPP test. Take station MAL2 as an example, respectively, using the proposed GSMC coding scheme and the original RTCM-SSR coding scheme for single BDS real-time simulation dynamic PPP test, the time series of positioning error as shown in Figure 4 Figure 5 The horizontal and vertical accuracy of each station using two encoding methods is respectively counted; Table 1 counts the horizontal and vertical accuracy of each station using two encoding methods for 7 days.

[0064] Table 1

[0065]

[0066] PPP experiment shows that the average positioning accuracy is 0.089m in horizontal direction and 0.103m in vertical direction. The maximum RMS in horizontal and vertical directions is 0.129m and 0.126m respectively. The average convergence time is 29.6min. Therefore, based on the proposed GSMC encoding method, the decimeter level positioning accuracy can be achieved globally.

[0067] In a third aspect, the present application provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the foregoing one kind of based on Beidou GSMC's SSR short message encoding and decoding method and device.

[0068] In a fourth aspect, the present application provides a computer readable storage medium, which stores executable instructions, the instructions are executed by the processor to enable the processor to implement the foregoing one kind of based on Beidou GSMC's SSR short message encoding and decoding method and device.

[0069] The above specific embodiments further illustrate the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application should be included in the protection scope of the present application.​

Claims

1. A method for encoding and decoding SSR short messages based on BeiDou GSMC, characterized in that, The method includes: Step 1: The server receives the multi-source state space representation (SSR) correction data stream in real time via the Internet; Step 2: The user terminal generates an approximate location based on pseudorange single-point positioning, encodes it as a BeiDou GSMC short message, and uploads it to the server. Step 3: The server calculates the satellite line-of-sight vector based on the approximate location, converts the SSR correction stream into the observation space representation OSR correction number and compresses it, and sends it to the user terminal; Step 4: The user terminal parses the OSR correction data, integrates GNSS observations and broadcast ephemeris, and achieves real-time precise single-point positioning.

2. The SSR short message encoding and decoding method based on BeiDou GSMC according to claim 1, characterized in that, The multi-source SSR correction data stream in step 1 includes satellite orbit, clock bias, and code bias parameters.

3. The SSR short message encoding and decoding method based on BeiDou GSMC according to claim 1, characterized in that, Step 2 includes: Step 2.1: The user terminal calculates the approximate location based on BDS / GNSS pseudorange observations using least squares estimation; Step 2.2: Encode the approximate location into a BeiDou GSMC short message and upload it to the server via short message communication to trigger the server to start the calculation of the user-specific correction number.

4. The SSR short message encoding and decoding method based on BeiDou GSMC according to claim 1, characterized in that, Step 3 includes: Step 3.1: The server calculates the satellite line-of-sight vector based on the user's approximate location and projects the SSR orbit / clock error corrections into one-dimensional range domain OSR corrections; Step 3.2: Compress OSR corrections using a dynamic bit-width encoding mechanism and a first-satellite full-data-subsequent-satellite differential layered encoding mechanism. The dynamic bit-width encoding mechanism dynamically adjusts the bit width of the data through variable parameters. The first-satellite full-data-subsequent-satellite differential layered encoding mechanism includes transmitting the full data of the first satellite and transmitting the differential data corresponding to the first satellite in subsequent satellites. Step 3.3: Encapsulate all satellite OSR correction data and check bits, and send them to the user terminal in a single frame via GSMC short message.

5. The SSR short message encoding and decoding method based on BeiDou GSMC according to claim 1, characterized in that, Step 4 includes: Step 4.1: The user terminal parses the OSR corrections, integrates BDS / GNSS carrier phase and pseudorange observations with broadcast ephemeris, and constructs a dual-frequency ionospheric-free combined observation model; Step 4.2: Calculate the position in real time using robust Kalman filtering and output the decimeter-level positioning result.

6. The SSR short message encoding and decoding method based on BeiDou GSMC according to claim 4, characterized in that, Step 3.1 specifically includes: the server first calculates the satellite line-of-sight vector (LOS) based on the user's approximate location, and projects the SSR orbit / clock error corrections onto a one-dimensional distance domain to generate OSR corrections, thereby compressing the data dimension; during data processing, the clock error dominant term is first fitted in the time domain, and then the orbit error dominant term is fitted in the spatial domain, and the spatial domain fitting is based on the spatial correlation of OSR within the user's area grid.

7. The SSR short message encoding and decoding method based on BeiDou GSMC according to claim 4, characterized in that, In step 3.2, the dynamic bit-width encoding mechanism and the first satellite full-subsequent satellite differential layered encoding include dividing the data structure design into four layers, where the header is set to a fixed 30 bits for encoding type, time, and number of satellites; the first middle part serves as the dynamic area for satellite data, where the first satellite is fully recorded and subsequent satellites are differentially compressed; the second middle part serves as the protocol reserved area; and the tail serves as a 24-bit CRC.

8. An SSR short message encoding and decoding device based on BeiDou GSMC, applied to the SSR short message encoding and decoding method based on BeiDou GSMC as described in any one of claims 1-7, characterized in that, include: The receiving module is used to enable the server to receive multi-source SSR correction data streams in real time via the Internet; The transmission module is used to enable the user terminal to generate an approximate location based on pseudorange single-point positioning, and encode it into a BeiDou GSMC short message and upload it to the server. The conversion module is used to enable the server to calculate the satellite line-of-sight vector based on the approximate location, convert the SSR correction data stream into OSR correction data, and compress the OSR correction data using a dynamic bit-width encoding mechanism and a first-satellite full-subsequent-satellite differential layer encoding mechanism before sending it to the user terminal. The positioning module enables the user terminal to parse OSR correction data, fuse GNSS observations with broadcast ephemeris, and achieve real-time precise single-point positioning.

9. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When one or more programs are executed by the one or more processors, the one or more processors implement the SSR short message encoding and decoding method based on BeiDou GSMC as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores executable instructions, which, when executed by a processor, enable the processor to implement the SSR short message encoding and decoding method based on BeiDou GSMC as described in any one of claims 1-7.

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