A method and device for encoding and decoding a short message of a SSR based on a Beidou GSMC

Abstract

The application discloses a kind of based on Beidou GSMC's SSR short message encoding and decoding method and device, it is related to satellite navigation and communication technical field.Aiming at the high-precision positioning demand of no ground station scene, the application has broken through to build "cloud-end" collaborative architecture: service end gathers multi-source SSR correction number through Internet, realizes data volume compression more than 90% by original SSR-OSR conversion algorithm in combination with newly proposed encoding scheme;User end generates sketchy position by pseudorange single point positioning, and sends to service end by Beidou GSMC short message to issue decimeter level precision OSR correction number.User end fuses GNSS observation value, broadcast ephemeris and OSR correction number, realizes real-time precise point positioning without ground station, and dynamic positioning precision reaches decimeter level.The application provides breakthrough high-precision positioning support for special scene such as ocean exploration, emergency rescue etc..

Description

Technical Field

[0001] This invention belongs to the field of satellite navigation and communication technology, specifically relating to a method and apparatus for encoding and decoding SSR (State Space Representation) short messages based on BeiDou GSMC (Global Short Message Communication). Background Technology

[0002] With the rapid development of Global Navigation Satellite Systems (GNSS), Precise Point Positioning (PPP) technology has become a core means of achieving high-precision positioning. In PPP, satellite orbit and clock errors are key factors affecting positioning accuracy, and real-time SSR corrections can effectively correct these errors. Currently, the International GNSS Service (IGS) and its Multi GNSS Experiments (MGEX) analysis centers (such as CAS, CNES, and DLR) primarily broadcast SSR corrections via the internet.

[0003] However, existing technologies face several key bottlenecks: (1) Strong network dependence. In areas without stable Internet coverage, such as oceans, deserts, and remote mountainous areas, users cannot obtain SSR correction data in real time; (2) Severely limited bandwidth. Although the Beidou-3 GSMC function supports bidirectional communication in areas without network coverage, its single communication bandwidth is only 560 bits; (3) Mismatched data capacity. The 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 performance. Existing encoding and decoding schemes are not optimized for narrow bandwidth, making it difficult to meet the real-time requirements of high-precision positioning.

[0004] The current encoding and decoding schemes for BeiDou short messages have some shortcomings: (1) high data redundancy, no dedicated compression algorithm designed for the characteristics of SSR correction numbers; (2) weak anti-interference ability, insufficient transmission reliability in complex electromagnetic environments; (3) poor scene adaptability, existing PPP technology relies on ground base stations or the Internet, which cannot meet the high-precision positioning needs of areas without network coverage.

[0005] There is an urgent need to develop an innovative SSR encoding and decoding scheme that can: (1) efficiently transmit SSR correction data under a narrow bandwidth of 560 bits; (2) achieve real-time decimeter-level positioning in areas without network coverage; (3) improve anti-interference capabilities in harsh environments; and (4) break through the dependence of traditional PPP technology on ground base stations. Solving the problem of real-time transmission of SSR correction data under low bandwidth conditions is of great value to promoting the application of the BeiDou system in key fields such as ocean navigation, geological exploration, and emergency rescue, and is one of the core challenges in the current development of satellite navigation technology. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides an SSR short message encoding and decoding method and apparatus based on BeiDou GSMC. By utilizing the real-time SSR correction data of the entire BDS-3 GSMC constellation, higher efficiency correction data communication transmission is achieved, thereby improving the reliability and stability of communication.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] A method for encoding and decoding SSR short messages based on BeiDou GSMC, the method comprising:

[0009] Step 1: The server receives multi-source SSR correction data streams in real time via the Internet;

[0010] 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.

[0011] Step 3: The server calculates the satellite line-of-sight vector based on the approximate location, converts the SSR correction data stream into OSR correction data, and compresses the OSR correction data using a dynamic bit-width encoding mechanism and a first-satellite full-data-subsequent-satellite differential layer encoding mechanism before sending it to the user terminal.

[0012] Step 4: The user terminal parses the OSR (Observation Space Representation) correction data, merges GNSS observations with broadcast ephemeris, and achieves real-time precise single-point positioning.

[0013] On the other hand, the present invention provides an SSR short message encoding and decoding device based on BeiDou GSMC, applied to the aforementioned SSR short message encoding and decoding method based on BeiDou GSMC, comprising:

[0014] The receiving module is used to enable the server to receive multi-source SSR correction data streams in real time via the Internet;

[0015] 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.

[0016] 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.

[0017] 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.

[0018] Thirdly, the present invention 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 SSR short message encoding and decoding method based on BeiDou GSMC.

[0019] Fourthly, the present invention provides a computer-readable storage medium storing executable instructions thereon, which, when executed by a processor, enable the processor to implement the aforementioned SSR short message encoding and decoding method based on BeiDou GSMC.

[0020] The beneficial effects of this invention are as follows:

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

[0022] High real-time performance: Utilizing the two-way communication function of BDS-3 GSMC, the user terminal can upload the approximate location in real time, and the server dynamically generates and broadcasts optimized OSR correction data, realizing high-frequency (1-minute interval) real-time data updates to meet the timeliness requirements of high-precision positioning.

[0023] Global coverage and high precision: It eliminates the dependence on the Internet or ground base stations and directly broadcasts correction data through BeiDou short messages, enabling dynamic decimeter-level precise point positioning (PPP) in areas without network coverage such as oceans and remote areas, thus expanding the application scenarios of high-precision navigation.

[0024] High anti-interference and reliability: The optimized encoding and decoding scheme reduces data transmission redundancy while enhancing anti-interference capabilities, ensuring stable reception and parsing of corrected data in complex communication environments. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of a cloud-edge 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] It aggregates SSR corrections broadcast in real time from the International GNSS Service (IGS) and the Multi GNSS Experiment (MGEX) Analysis Center; and integrates and processes key parameters such as orbital error and clock error. Currently, many IGS / MGEX analysis centers (International GNSS Service / Multi-GNSS Experiment) provide real-time SSR RTS corrections (State Space Representation Real-Time Service), such as CAS, CNES, DLR, BKG, WHU, and GMV. The server uses GDDS software with multi-threaded parallel processing capabilities to simultaneously receive SSR RTS corrections broadcast from multiple IGS / MGEX analysis centers and perform SSR synthesis, including a comprehensive evaluation of the stability, completeness, and accuracy of the data stream for each SSR product. This allows for the selection of SSR corrections with high reliability and continuity, preparing the data source for subsequent SSR to OSR conversion. Given the relatively abundant real-time SSR corrections, appropriate strategies are needed for comprehensive utilization. Due to the unavoidable network communication interruptions in internet transmission, some analysis centers may have a significant number of missing SSR products. This invention relates to a multi-analysis center SSR product selection optimization strategy.

[0034] Step 2: The user terminal generates a rough location based on pseudorange single point positioning (SPP) technology, encodes it into a BeiDou GSMC short message, and uploads it to the server. Thanks to the bidirectional communication function of the BDS-3 short message service, the user terminal GSMC device of this invention has the functions of collecting BDS / GNSS observations and broadcasting ephemeris, as well as sending information to the server. Therefore, the user's rough location can be sent to the server, preparing the data source for subsequent SSR to OSR conversion, thereby promoting the implementation of an efficient encoding scheme on the server side. Specifically, this includes:

[0035] Step 2.1: The user terminal calculates the approximate location based on BDS / GNSS pseudorange observations using least squares estimation (typical accuracy: 10 meters horizontally and 15 meters vertically).

[0036] Step 2.2: Encode the approximate location into a BeiDou GSMC short message (occupying ≤560 bits), upload it to the server via short message communication, and trigger the server to start the calculation of the user-specific correction number.

[0037] Step 3: The server calculates the satellite line-of-sight vector based on the approximate location, converts the SSR correction stream into OSR corrections, and compresses the OSR correction data using a Dynamic Bit Width Encoding (DBWE) mechanism and a Full-volume of the first satellite - Differential for subsequent satellites Hierarchical Encoding (FDHE) mechanism before sending it to the user. Since the BDS-3 GSMC short message has a communication bandwidth of only 560 bits, data transmission must be compressed for efficient SSR correction transmission. This invention proposes converting large-capacity SSR corrections into small-capacity OSR corrections based on the user's approximate location, and then using a self-developed compact encoding and decoding scheme to encode the OSR corrections into BDS-3 GSMC short messages, which are then broadcast to the user at 1-minute intervals, greatly reducing the dependence on communication bandwidth. Specifically, this includes:

[0038] Step 3.1: The server calculates the satellite line-of-sight vector (LOS) based on the user's approximate location, and projects the SSR orbit / clock error correction into a one-dimensional range domain OSR correction, thereby compressing the data dimension.

[0039] The server calculates the line-of-sight vector (LOS) based on the user's approximate location. Through projection transformation, it merges the SSR format orbital corrections (3D) and clock corrections (1D) into a unified 1D range domain observation-space representation (OSR), realizing data compression from multi-dimensional corrections to single-dimensional data. Among them: Formula (1) defines the projection transformation principle from SSR orbital / clock corrections to OSR; Formula (2) describes the clock compression strategy: extrapolating the clock error change trend based on time domain polynomial fitting (such as second-order polynomial); Formula (3) describes the orbital compression strategy: modeling the spatial distribution characteristics of orbital corrections based on spatial domain polynomial surface fitting.

[0040] Transforming the SSR correction in the state domain into a one-dimensional distance correction (OSR) can significantly reduce data redundancy. Mathematically, this is the projection of the dot product of the LOS vector and the SSR error vector.

[0041] (1)

[0042] In the formula, This represents the one-dimensional distance correction. 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 number 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 blocks in the middle are divided into 4 logical layers according to function: (1) Fixed header area, which includes fields such as signal correction number type, epoch time, number of satellites (N), etc., with a fixed length of 30 bits to ensure fast parsing of basic information. (2) Satellite data dynamic area, full record of the first satellite: including 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); incremental compression of subsequent satellites: only PRN differential value + OSR differential value are retained, the length of each satellite is 8+X bits. The key invention point is that the redundancy of broadcast data is reduced by using the spatiotemporal correlation of correction numbers and calculating differential values. (3) Protocol reserved area, which supports future addition of fields (such as encryption identifier, enhanced service type). (4) CRC (Cyclic Redundancy Check) check area, 24-bit cyclic redundancy check code, covering the entire data block, resisting transmission errors.

[0052] II. First Satellite Full-Subsequent Satellite Differential Layered Coding Mechanism (FDHE). The dynamic area adopts the compression strategy of "first satellite full + subsequent satellite differential", and the total length is defined by the formula: total length = 30 + first satellite (13 + X) + subsequent satellite (N-1) × (8 + X) + reserved length + 24. It has the following technical advantages: (1) Improved spatial efficiency. When the number of satellites (N) increases, subsequent satellites only need 8 + X bits (5 bits less than the first satellite), which can save about 35% of bandwidth in the scenario of 100 satellites. (2) Real-time parsing. The fixed header length (30 bits) enables the receiver to quickly lock the start of the data, and the differential structure reduces the computational complexity of decoding. (3) Flexibility of expansion. X is a variable parameter (such as X=12 representing 0.1mm level precision), which can be adapted to different precision requirements; the reserved area supports backward compatibility of the protocol.

[0053] Step 3.3: Encapsulate the OSR data of 12 satellites plus check bits (total ≤ 560 bits) and send it to the user terminal in a single frame via GSMC short message. A single transmission of OSR data of 12 satellites requires only 546 bits (including check bits), which is 91.7% compressed compared to the 6628 bits of the RTCM-SSR format, and is fully compatible with the 560-bit short message capacity of BeiDou GSMC.

[0054] Step 4: The user terminal parses the OSR correction values, fuses GNSS observations and broadcast ephemeris, and achieves real-time precise point positioning (RT-PPP). The user receives observations and broadcast ephemeris from BDS / GNSS satellites, as well as OSR correction values ​​from the server, to perform real-time precise point positioning, thereby obtaining dynamic decimeter-level positioning accuracy globally based on a single receiver (without the need for a ground reference station). Specifically, this includes:

[0055] 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;

[0056] Step 4.2: The user's position is calculated in real time using a robust Kalman filter, outputting decimeter-level positioning results. PPP technology employs the mature robust Kalman filter algorithm as its parameter estimation method. By dynamically fusing multi-frequency BDS / GNSS satellite observations (pseudorange, carrier phase) with external precision products (such as satellite orbit / clock bias), it estimates receiver position, velocity, clock bias, and atmospheric delay parameters in real time. Its advantages lie in effectively suppressing observation noise, solving the problem of positioning continuity in dynamic environments, and maintaining positioning accuracy during brief satellite signal interruptions through a state prediction model, providing PPP with highly robust real-time positioning capabilities. For detailed principles, please refer to relevant literature.

[0057] On the other hand, the present invention also relates to an SSR short message encoding and decoding device based on BeiDou GSMC, wherein the various parts of the device are capable of implementing the various steps of the aforementioned method, specifically including:

[0058] The receiving module is used to enable the server to receive multi-source SSR correction data streams in real time via the Internet;

[0059] 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.

[0060] 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.

[0061] 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.

[0062] Example:

[0063] A single BeiDou PPP simulated dynamic positioning experiment was conducted, using observations from six globally distributed IGS stations over one week (cumulative days 152-158 of 2025). Real-time simulated dynamic BDS PPP experiments were performed on both the proposed coding scheme and the original RTCM-SSR scheme. Taking station MAL2 as an example, single BeiDou real-time simulated dynamic PPP experiments were conducted using both the proposed GSMC coding scheme and the original RTCM-SSR coding scheme. The time series of positioning errors is shown below. Figure 4 As shown; Figure 5 The horizontal and vertical accuracy of each station using the two coding methods was statistically analyzed. Table 1 shows the 7-day average horizontal and vertical accuracy of each station using the two coding methods.

[0064] Table 1

[0065]

[0066] PPP experiments show that the average positioning accuracy is 0.089m horizontally and 0.103m vertically. The maximum RMS in the horizontal and vertical directions are 0.129m and 0.126m, respectively. The average convergence time is 29.6 minutes. Therefore, based on the proposed GSMC coding method, decimeter-level positioning accuracy can be achieved globally.

[0067] Thirdly, the present invention 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 SSR short message encoding and decoding method and apparatus based on BeiDou GSMC.

[0068] Fourthly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned SSR short message encoding and decoding method and apparatus based on BeiDou GSMC.

[0069] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

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, including satellite orbit, clock bias, and code offset parameters; Step 2: Based on BDS / GNSS pseudorange observations, the user terminal calculates the approximate location using least squares estimation, encodes the approximate location into a BeiDou GSMC short message, and uploads it to the server via short message communication, triggering the server to start the calculation of user-specific corrections. Step 3: The server calculates the satellite line-of-sight vector based on the approximate location, converts the SSR correction data stream into the observation space representation OSR correction data, and compresses the OSR correction data using a dynamic bit-width encoding mechanism and a first-satellite full-data-subsequent-satellite differential layered encoding mechanism. This data is then sent to the user terminal via a single frame of BeiDou GSMC short message. The dynamic bit-width encoding mechanism dynamically adjusts the data bit width using variable parameters. The first-satellite full-data-subsequent-satellite differential layered encoding mechanism includes transmitting the full data for the first satellite and transmitting the differential data corresponding to the first satellite for subsequent satellites. Step 4: The user terminal parses the OSR correction data, integrates BDS / GNSS carrier phase and pseudorange observations and broadcast ephemeris, constructs a dual-frequency ionospheric-free combined observation model, and calculates the position in real time through robust Kalman filtering, outputting decimeter-level positioning results.

2. 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; 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.

3. The SSR short message encoding and decoding method based on BeiDou GSMC according to claim 2, 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.

4. The SSR short message encoding and decoding method based on BeiDou GSMC according to claim 2, 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.

5. 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 1-4, 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.

6. 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 1-4.

7. 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 1-4.

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