Rapid warm start positioning method and system for GNSS (Global Navigation Satellite System) receiver

Abstract

The invention discloses a GNSS receiver rapid warm start positioning method and system, and relates to the field of satellite radio beacon positioning systems. According to the method, all visible satellite signals are searched in a relatively wide frequency and code phase range; determining a time range according to the ephemeris validity period and the time information stored before the last shutdown; sampling is carried out at regular intervals in the time range to obtain a limited number of time points, and the time points meeting conditions in the time points are found out according to signal features to serve as rough estimation time; iteratively correcting the three-dimensional position of the receiver, the time difference of the GNSS system and the clock skew of the receiver to obtain relatively accurate position and time; and the relatively accurate time is substituted into the local time of the receiver, and accurate positioning calculation is carried out by using a positioning algorithm. According to the GNSS rapid warm start positioning method and system, time assistance and a backup power supply are not needed, the size and energy consumption of a receiver are reduced, and the GNSS rapid warm start positioning method and system are suitable for various GNSS.

Description

Technical Field

[0001] The present invention relates to the field of satellite radio beacon positioning systems, and in particular to a GNSS receiver rapid hot start positioning method and system. Background Art

[0002] The Global Navigation Satellite System (GNSS) plays a vital role in today's navigation and positioning applications. The startup positioning speed of a GNSS receiver is a key performance indicator. Traditional GNSS hot-start technologies typically rely on external time assistance information and a backup power supply to preserve critical data. Time assistance information typically needs to be obtained from external devices such as the network and base stations. This not only increases system complexity and cost, but also makes accurate time assistance information difficult to obtain in remote areas, areas with poor signal coverage, or in interference-prone environments, thus affecting the receiver's startup speed and positioning accuracy. Using a backup power supply (such as a battery) to power static random access memory (SRAM) to store data has numerous drawbacks. The backup power supply has a limited lifespan and requires regular replacement, increasing maintenance costs and inconvenience. Furthermore, the presence of a backup power supply increases the size and weight of the device, hindering its miniaturization and portability. Therefore, developing a GNSS fast hot-start positioning method and system that does not require time assistance and a backup power supply is of great practical significance and meets market demand.

[0003] Chinese Patent Publication No. CN119959983A discloses a hot start method, apparatus, and device for a single Beidou satellite navigation receiver, relating to the field of satellite navigation technology. The method includes obtaining the local real-time clock time, local clock drift value, local approximate position, and the first valid ephemeris of a GEO satellite. If the local real-time clock time is valid, the GEO satellite error is corrected. A first PVT solution is performed based on the correction results using GEO satellites that meet a threshold number of satellites to obtain a two-dimensional positioning result, which is used to correct the local real-time clock time, local clock drift value, and local approximate position. Based on the corrected local real-time clock time, local clock drift value, and local position, visible IGSO and MEO satellite signals are captured and tracked, and a pseudorange equation system is constructed. A second PVT solution is performed on the pseudorange equation system to obtain the receiver's three-dimensional positioning result. However, this method requires the receiver to receive a time assistance signal, which is not conducive to device miniaturization and portability. Summary of the Invention

[0004] The present invention aims to provide a GNSS fast hot start positioning method and system that does not require time assistance and backup power supply, so as to solve the problem that existing GNSS hot start technology relies on time assistance information and backup power supply, realize fast, efficient and accurate hot start positioning, and is applicable to multiple GNSS systems such as Beidou, GPS, GALILEO and GLONASS.

[0005] In order to solve the above technical problems, the technical solutions adopted by the present invention are as follows: A GNSS receiver rapid hot start positioning method comprises the following steps: Step S1: Search for all visible satellite signals within a wide frequency and code phase range; Step S2: Determine a time range based on the validity period of the ephemeris and the time information saved before the last shutdown; Step S3: sampling at regular intervals within the time range to obtain a finite number of time points, and finding a time point that meets the conditions among the time points according to the signal characteristics as a rough estimated time; Step S4: Iteratively correct the five state parameters of the receiver's three-dimensional position, GNSS system time difference, and receiver clock bias to obtain relatively accurate position and time; Step S5: The relatively accurate time is brought into the local time of the receiver, and a positioning algorithm is used to perform accurate positioning calculation.

[0006] Preferably, step S3 includes: for each time point, calculating the pseudorange residuals, Doppler residuals and elevation angles of all satellites based on the ephemeris information stored in the receiver, the historical position of the receiver, and the satellite transmission time, Doppler frequency shift and signal-to-noise ratio captured at startup.

[0007] Preferably, step S3 also includes: for each time point, determining whether the Doppler frequency shift measurement values ​​corresponding to the n satellites with the highest elevation angles at that moment are the smallest n. If their Doppler frequency shift measurement values ​​are not within the smallest n values, it can be considered that the estimation error at that moment is large and is not suitable as a rough estimate of time. Otherwise, it is considered that the time accuracy is relatively accurate and enters the next judgment process.

[0008] Preferably, step S3 also includes: for each time point, calculating the residuals of the Doppler measurement values ​​of all satellites, debiasing the residuals of all Doppler measurement values ​​and then counting their variances; if the variance is greater than a threshold, it means that the current local time accuracy is poor and is not suitable as a rough estimate of time; otherwise, it is considered that the time accuracy is relatively accurate and the next judgment process is entered.

[0009] Preferably, the step S3 further includes: The residuals of all pseudorange measurements are grouped by satellite system. Then, within each satellite system, the common mode deviation of all pseudorange measurement residuals is calculated as the estimated value of the receiver clock error and removed. For the local time ambiguity assumption, the error term associated with the ambiguity in each pseudorange measurement residual is calculated and removed; the variance of all measurement residuals is calculated. If the variance is still greater than a certain threshold, it means that the current local time accuracy is poor and is not suitable for rough time estimation. Otherwise, the time accuracy is considered to be relatively accurate and the next judgment process is entered.

[0010] Preferably, step S3 further includes: comparing, for all time points with relatively accurate time accuracy, the change status of the elevation-Doppler frequency shift value, the variance of the Doppler residual, and the variance value of the pseudorange residual within each time point, and taking the time point at which the change status of the elevation-Doppler frequency shift value best conforms to the monotonically decreasing function and the variance values ​​of the Doppler residual and the pseudorange residual are the smallest as the final rough estimate time of the receiver's local time.

[0011] Preferably, the method for iteratively correcting the three-dimensional position of the receiver, the GNSS system time difference and the receiver clock bias includes: constructing a matrix calculation formula related to the three-dimensional position of the receiver, the GNSS system time difference and the receiver clock bias for the pseudo-range measurement residuals of all satellites, and solving the matrix calculation formula using the least squares method.

[0012] Preferably, the method for iteratively correcting the three-dimensional position of the receiver, the GNSS system time difference and the receiver clock bias includes: constructing a matrix calculation formula related to the three-dimensional position of the receiver, the GNSS system time difference and the receiver clock bias for the pseudo-range measurement residuals of all satellites, and solving the matrix calculation formula using the least squares method.

[0013] A GNSS receiver rapid hot start positioning system comprises: a rapid capture circuit module connected to a data processing module; a storage module connected to the data processing module, and the storage module adopts a non-volatile memory FLASH.

[0014] Preferably, the fast acquisition circuit module includes a GNSS radio frequency chip and a high-performance embedded processor. The radio frequency chip receives satellite signals and down-converts them to intermediate frequency signals. The embedded processor runs an optimized search algorithm to process the intermediate frequency signals.

[0015] Through the above technology, the present invention provides a GNSS fast hot start positioning method and system that does not require time assistance and backup power supply, reduces the size and energy consumption of the receiver, and is adaptable to multiple GNSS. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1This is a flow chart of the local time search of the present invention.

[0017] Figure 2 It is a schematic diagram of the system of the present invention. DETAILED DESCRIPTION

[0018] The following is a specific embodiment of the present invention, and the technical solution of the present invention is described in detail with reference to the accompanying drawings.

[0019] Example 1, the method of the present invention comprises the following steps: Step S1: Search for all visible satellite signals within a wide frequency and code phase range; Step S2: Determine a time range based on the validity period of the ephemeris and the time information saved before the last shutdown; Step S3: sampling at regular intervals within the time range to obtain a finite number of time points, and finding a time point that meets the conditions among the time points according to the signal characteristics as a rough estimated time; Step S4: Iteratively correct the five state parameters of the receiver's three-dimensional position, GNSS system time difference, and receiver clock bias to obtain relatively accurate position and time; Step S5: The relatively accurate time is brought into the local time of the receiver, and a positioning algorithm is used to perform accurate positioning calculation.

[0020] Next, we will describe step S1 in detail. When the GNSS receiver is powered on, the fast acquisition circuit begins operation. This circuit is optimized for the satellite signal characteristics of various GNSS systems, including Beidou, GPS, GALILEO, and GLONASS. Without relying on external timing information or a priori satellite position predictions, the fast acquisition circuit conducts a comprehensive search for all visible satellite signals within a wide frequency and code phase range. By employing efficient search algorithms such as parallel search and fast Fourier transform (FFT), it can quickly lock onto satellite signals in a short period of time. When the GNSS receiver is powered on, the fast acquisition circuit begins operation. For different GNSS systems, the fast acquisition circuit adjusts search parameters and algorithms based on the signal's center frequency, code rate, modulation scheme, and other characteristics. For example, different frequency search ranges and code phase search step sizes are used for Beidou's B1, B2, and B3 frequency band signals, and GPS's L1 and L2 frequency band signals.

[0021] During the search process, the fast acquisition circuit employs a parallel search algorithm, simultaneously searching for multiple frequency and code phase combinations. Fast Fourier Transform (FFT) technology is used to convert time-domain signals into frequency-domain signals, improving search efficiency. Once a satellite signal is acquired, relevant signal parameters (such as carrier frequency, code phase, and signal strength) are recorded and transmitted to the data processing module.

[0022] Next, we'll detail steps S2 and S3, which read the last saved time information, t_0, from non-volatile memory (e.g., FLASH). Since the validity period of the ephemeris varies across GNSS systems, but is typically several hours, a reasonable search range, T, is set based on this period. If set based on the validity period of GPS satellites, T can be set to 4 hours.

[0023] Within the time range (t0-T, t0+T), a traversal search is performed at regular intervals dt (e.g., 1 minute). Each time point is evaluated based on the characteristics of the captured satellite signal, such as signal strength, Doppler shift, and code phase. By establishing a correlation model between signal characteristics and time, a rough estimate of the current possible time is obtained.

[0024] The following describes how to establish a correlation model between signal characteristics and time. Previously, the search time was the receiver's local time. After acquiring the satellite signal, we can synthesize the satellite signal's transmission time using the code phase. Subtracting the satellite signal's transmission time from the receiver's local time yields the distance the satellite signal traveled, or the pseudorange. We also use the satellite ephemeris information stored in the flash memory and the receiver's local time to calculate the satellite's position. Using the satellite's position and the receiver's position, we can determine the geometric distance between the satellite and receiver. Subtracting the pseudorange from the geometric distance yields the residual of the pseudorange measurement.

[0025] The Doppler measurement residuals are derived from the satellite position and velocity derived from the ephemeris information and satellite launch time, as well as the satellite Doppler shift obtained during satellite signal acquisition. Furthermore, the elevation angles of all currently captured satellites are derived by combining the receiver's position with the satellite's position. First, the pseudorange residuals, Doppler residuals, and elevation angles for all satellites are calculated using the local time to be confirmed, the internally stored ephemeris information, the receiver's historical position, and the satellite launch time, Doppler shift, and signal-to-noise ratio obtained from the acquisition module.

[0026] After obtaining the above information, we begin to determine the signal characteristics based on the relationships between the various pieces of information. First, since there is a functional relationship between the satellite's elevation angle and the Doppler shift (as the elevation angle decreases, the component of the satellite's velocity in the Earth's radial direction increases, and the Doppler shift value increases), the satellite's elevation angle and Doppler shift can be listed and compared. If the Doppler shift value does not exhibit the functional relationship described above with the satellite's elevation angle, the reliability of the current time is reduced. The five satellites with the highest elevation angles can be listed. If their Doppler shift measurements are not within the five smallest values, the current local time accuracy is considered poor and the next search cycle is required. Otherwise, the time accuracy is considered relatively accurate and the next judgment process is carried out.

[0027] Second, the residual values ​​of the Doppler measurements from all satellites are combined for analysis.

[0028] Since the Doppler measurement value is not affected by the clock error of each clock system, there should be a common mode deviation between them (that is, the frequency drift of the receiver δf u ). After debiasing the residuals of all Doppler measurements (this common mode deviation is used as δf u The estimated value (needed for the next stage of calculation) is calculated and its variance is calculated. If the variance is greater than a threshold (which can be set to 50 times the Doppler measurement noise), the current local time accuracy is poor and the next round of search is required. Otherwise, the time accuracy is considered to be relatively accurate and the next judgment process is entered.

[0029] Third, after processing the pseudo-range measurements of all satellites, they are combined for analysis. When there is ambiguity in the local time of the receiver, it can be seen from the formula for constructing the pseudo-range measurement residual that the pseudo-range residual contains the receiver clock error. and the local time ambiguity δt local There are two unknown terms. Therefore, the errors caused by these two unknown terms need to be estimated and removed to restore the noise to the maximum extent. First, the residuals of all pseudo-range measurements are grouped according to the satellite system. Then, within each satellite system, the common mode deviation of all pseudo-range measurement residuals is calculated as the receiver clock error. , and remove it.

[0030] Then, assuming the local time ambiguity δt local = 30 seconds, and the error term c·δt associated with the ambiguity in each pseudorange measurement residual is local ·(Δf-δf u ) is calculated and removed.

[0031] Finally, the distribution of all measurement residual sets is counted. If its variance is still greater than a certain threshold If the local time error is large, the next round of search will be entered. Otherwise, the time accuracy is considered to be relatively accurate, and the next judgment process will be entered.

[0032] If all three of the above comparisons meet the criteria, the local time is saved and the next search round continues. After the search is complete, a set of time points that meet the criteria is obtained. The change in elevation-Doppler shift, the variance of the Doppler residual, and the variance of the pseudorange residual at each time point are then compared. The time point where the change in elevation-Doppler shift best fits the monotonically decreasing function and where the variance of the Doppler residual and pseudorange residual is minimized is used as the final estimate of the receiver's local time.

[0033] Next, we will detail step S4, which uses a five-state positioning method to correct the estimated time. This method comprehensively considers five state parameters: the receiver's three-dimensional position (x, y, and z axes of the ECEF coordinate system), the GNSS system time difference, and the receiver clock bias. The receiver's pseudorange residual can be constructed as a function of these five state quantities. By continuously adjusting these five state parameters, the error between the calculated satellite signal observations (such as pseudorange and carrier phase) and the actual captured signal observations is minimized. After multiple iterations, a relatively accurate coarse position and time are determined. The three-dimensional position of the GPS receiver, the absolute time of signal reception, and the common-mode error are taken as unknown parameters. The nonlinear relationship between the pseudorange measurement value and these parameters is constructed and linearized to approximate the solution. The specific process is as follows: first, the pseudorange residual is obtained. Based on the assumption that the difference between the prior estimate and the true value is small, the nonlinear pseudorange model is linearized by the first-order Taylor series expansion, and a linear equation system of the pseudorange residual and the position and time update amount is constructed. The coefficients of the equation system are composed of the partial derivatives of the pseudorange with respect to position and time (reflecting the satellite geometric relationship and the time change rate). The least squares method is used to solve the equation. A program group is formed to obtain the optimal update amount that minimizes the sum of squared residuals. If the prior estimation error is large, the prior value is iteratively updated and the solution is repeated until the residual converges. For scenarios with extremely low prior estimation accuracy, the position space is divided into regular grids and the time is divided into fixed interval segments for traversal search. The significant difference between the correct solution residual (equivalent to the measurement noise) and the incorrect solution residual (up to several thousand meters) is used to screen reasonable results. This modeling method breaks through the traditional GPS's reliance on absolute time, provides constraints through wireless auxiliary information, and achieves robust positioning solutions in scenarios without precise timing.

[0034] Next, we'll detail step S5. After determining the rough position and time, the receiver clock offset calculated by the five-state positioning algorithm is substituted into the receiver's local time to obtain a receiver time accurate enough to meet the requirements of high-precision positioning algorithms. High-precision positioning algorithms, such as Kalman filtering and least squares methods, can then be used to accurately calculate the position by combining all captured satellite signals with accurate satellite ephemeris information.

[0035] Example 2, as Figure 2 The system part of the present invention includes a fast capture circuit module, a storage module, a data processing module, and a satellite signal receiving module.

[0036] The fast acquisition circuit module, based on a dedicated hardware circuit design, features high-speed signal processing capabilities and search algorithms optimized for multiple GNSS systems. Upon receiver startup, it can rapidly perform blind searches for satellite signals from systems such as Beidou, GPS, GALILEO, and GLONASS. The fast acquisition circuit module utilizes a dedicated GNSS RF chip and a high-performance embedded processor. The RF chip receives satellite signals and down-converts them to an intermediate frequency (IF) signal. The embedded processor runs an optimized search algorithm to process the IF signal, enabling rapid blind searches. The RF chip features multi-band reception capabilities for different GNSS systems, enabling simultaneous reception of signals from multiple GNSS systems. The search algorithm in the embedded processor is optimized based on the signal characteristics of each system, improving search efficiency and accuracy.

[0037] The storage module uses non-volatile FLASH memory to store critical information such as the receiver's location, time, and satellite ephemeris. This non-volatile memory retains data even after a power outage without requiring a backup power source, ensuring data security and reliability. The storage module uses non-volatile FLASH memory. The data processing module interacts with the non-volatile memory via interfaces such as SPI and I2C, saving critical information such as the receiver's location, time, and satellite ephemeris to the memory. The non-volatile FLASH memory offers large capacity, high reliability, and low power consumption, meeting the needs of long-term data storage. Furthermore, its ability to maintain data integrity during power outages ensures data security and integrity even after the receiver loses power.

[0038] The data processing module is responsible for executing algorithms such as coarse time estimation, coarse position and time confirmation, and positioning solution. This functionality is achieved using a high-performance embedded processor running corresponding software programs. The software programs include parameter configuration and algorithm optimization specific to different GNSS systems. The data processing module is implemented using a high-performance embedded processor. The software programs in the data processing module include parameter configuration and algorithm optimization specific to different GNSS systems. By analyzing the signal characteristics and positioning requirements of different systems, algorithm parameters and processes are adjusted to improve system compatibility and positioning performance.

[0039] The satellite signal reception module includes a multi-system compatible antenna and RF front-end circuitry. It can receive satellite signals from multiple GNSS systems, including Beidou, GPS, GALILEO, and GLONASS, and convert them into digital signals for subsequent processing. The RF front-end circuitry amplifies, filters, and downconverts the received signals to improve signal quality and stability. The satellite signal reception module includes a multi-system compatible antenna and RF front-end circuitry. The antenna utilizes a multi-band, multi-system compatible design, capable of simultaneously receiving satellite signals from multiple GNSS systems, including Beidou, GPS, GALILEO, and GLONASS.

[0040] The RF front-end circuit amplifies, filters, and down-converts the received signal to improve signal quality and stability. By using circuit components such as low-noise amplifiers (LNAs), bandpass filters, and mixers, it reduces noise interference and improves the signal-to-noise ratio.

[0041] When the GNSS receiver is powered on, the fast acquisition circuit module begins operating. This module uses a dedicated GNSS RF chip and a high-performance embedded processor to adjust search parameters and algorithms based on the satellite signal characteristics of various GNSS systems, including Beidou, GPS, GALILEO, and GLONASS. For example, different frequency search ranges and code phase search steps are set for the B1, B2, and B3 frequency band signals of the Beidou system and the L1 and L2 frequency band signals of GPS. The fast acquisition circuit uses a parallel search algorithm combined with fast Fourier transform (FFT) technology to perform a comprehensive blind search for all visible satellite signals within a wide frequency and code phase range. Once a satellite signal is captured, relevant parameters such as carrier frequency, code phase, and signal strength are immediately recorded and passed to the data processing module.

[0042] The data processing module reads the last saved time information, t0, from the non-volatile memory FLASH. Based on the validity period of the GPS satellite ephemeris, it sets the time search range, T, to 4 hours. With t0 as the center, it performs a traversal search within the range (t0-T, t0+T) at 1-minute intervals, dt. At each time point, the module calculates the satellite's pseudorange residual, Doppler residual, and elevation angle using information such as the carrier-to-noise ratio, Doppler shift, and code phase of the captured satellite signal. First, compare the Doppler shift measurements of the five satellites with the highest elevation angles. If they are not within the minimum five values, the current time reliability is low and the next round of search begins. Otherwise, calculate the common-mode deviation of the Doppler measurement residuals of all satellites and debias them. Count the variance after debiasing. If the variance is greater than 50 times the Doppler measurement noise threshold, the time accuracy is poor and the next round of search begins. Otherwise, group the pseudorange measurement residuals by satellite system, calculate and remove the common-mode deviation (receiver clock error estimate) and local time ambiguity (assuming 30 seconds) related error terms, count the variance after debiasing, and if the variance is greater than the threshold Tρ 2 , the time accuracy is poor and the next search round begins. If all three of the above conditions are met, the local time is saved. After the search is completed, the time point where the elevation-Doppler shift value change best conforms to the monotonically decreasing function and the variance of the Doppler residual and pseudorange residual is minimized is selected from the set of qualified time points as the final estimate of the receiver's local time.

[0043] Next, the data processing module uses a five-state positioning method, comprehensively considering the five state parameters of the receiver's three-dimensional position (x, y, and z axes of the ECEF coordinate system), GNSS system time difference, and receiver clock bias. Based on the preliminary estimated rough time and the captured satellite signal, a mathematical model is established, and the least squares method is used for iterative calculation. The five state parameters are continuously adjusted to minimize the error between the calculated satellite signal observation values ​​(such as pseudorange, carrier phase, etc.) and the actual captured signal observation values. After multiple iterations, a relatively accurate coarse position and time are determined.

[0044] After determining the rough position and time, the data processing module calculates the δt obtained by the 5-state positioning algorithm. local Substituting this into the receiver's local time yields the receiver time that meets the requirements of the high-precision positioning algorithm. High-precision positioning algorithms such as the Kalman filter and least squares method are then used, combining all captured satellite signals with accurate satellite ephemeris information. Various error factors, such as ionospheric and tropospheric delays, are considered and corrected for, resulting in a precise positioning solution.

[0045] Throughout the system, the storage module uses non-volatile FLASH memory to store key information such as the receiver's position, time, and satellite ephemeris. This data is retained even after a power outage without requiring a backup power source. The satellite signal reception module includes a multi-band, multi-system compatible antenna and RF front-end circuitry. The antenna is capable of simultaneously receiving satellite signals from multiple GNSS systems, and the RF front-end circuitry amplifies, filters, and down-converts the received signals to improve signal quality and stability. The data processing module utilizes a high-performance embedded processor, running the corresponding software program. It configures parameters and optimizes algorithms for different GNSS systems, enabling functions such as coarse time estimation, coarse position and time confirmation, and positioning solutions.

[0046] The present invention produces the following beneficial effects through the above technology: No need for time assistance and backup power: Fast acquisition circuitry enables blind signal search, eliminating reliance on external time assistance information. Non-volatile memory is used to store data, eliminating the need for a backup power supply, reducing system cost and complexity, size and weight, and improving reliability and portability. Fast hot start positioning: Optimized positioning steps and efficient search algorithms can achieve hot start positioning of the receiver in a short time, greatly shortening the positioning time and improving positioning efficiency; Multi-system compatibility: The present invention is applicable to multiple GNSS systems such as BeiDou, GPS, GALILEO and GLONASS, and has wide applicability and versatility, and can meet the needs of different users and application scenarios; High-precision positioning: The 5-state positioning method and high-precision positioning algorithm, combined with error correction and optimization, can obtain accurate positioning results, improving positioning accuracy and reliability.

[0047] The above description is only a specific embodiment of the present application. Those skilled in the art will clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the scope of protection of the present application.

Claims

1. A GNSS receiver rapid hot start positioning method, characterized in that: The following steps are involved: Step S1: Search for all visible satellite signals within a wide frequency and code phase range; Step S2: Determine a time range based on the validity period of the ephemeris and the time information saved before the last shutdown; Step S3: sampling at regular intervals within the time range to obtain a finite number of time points, and finding a time point that meets the conditions among the time points according to the signal characteristics as a rough estimated time; Step S4: Iteratively correct the receiver's three-dimensional position, GNSS system time difference, and receiver clock bias to obtain relatively accurate position and time; Step S5: The relatively accurate time is brought into the local time of the receiver, and a positioning algorithm is used to perform accurate positioning calculation.

2. A GNSS receiver rapid hot start positioning method according to claim 1, characterized in that: Step S3 includes: for each time point, calculating the pseudorange residuals, Doppler residuals and elevation angles of all satellites based on the ephemeris information stored in the receiver, the receiver's historical position, and the satellite launch time, Doppler frequency shift and signal-to-noise ratio captured at startup.

3. A GNSS receiver rapid hot start positioning method according to claim 1 or 2, characterized in that: Step S3 also includes: for each time point, determining whether the Doppler shift measurement values ​​corresponding to the n satellites with the highest elevation angles at that moment are the smallest n values. If their Doppler shift measurement values ​​are not within the smallest n values, it can be considered that the estimation error at that moment is large and is not suitable for rough estimation of time. Otherwise, it is considered that the time accuracy is relatively accurate and enters the next judgment process.

4. A GNSS receiver rapid hot start positioning method according to claim 1 or 2, characterized in that: Step S3 further includes: calculating the residuals of the Doppler measurement values ​​of all satellites at each time point, debiasing the residuals of all Doppler measurement values ​​and then calculating their variances. If the variance is greater than a threshold, it means that the current local time accuracy is poor and is not suitable for rough estimation of time. Otherwise, it is considered that the time accuracy is relatively accurate and the next judgment process is entered.

5. A GNSS receiver rapid hot start positioning method according to claim 1 or 2, characterized in that: The step S3 further includes: The residuals of all pseudorange measurements are grouped by satellite system. Then, within each satellite system, the common mode deviation of all pseudorange measurement residuals is calculated as the estimated value of the receiver clock error and removed. For the local time ambiguity assumption, calculate the error term associated with the ambiguity in each pseudorange measurement residual and remove it; The variance of all measurement residuals is calculated. If the variance is still greater than a certain threshold, it means that the current local time accuracy is poor and is not suitable for rough estimation. Otherwise, the time accuracy is considered to be relatively accurate and the next judgment process is entered.

6. A GNSS receiver rapid hot start positioning method according to claim 1 or 2, characterized in that: The step S3 further comprises: comparing the change of the elevation angle-Doppler frequency shift value, the variance of the Doppler residual and the variance of the pseudorange residual within each time point for all time points with relatively accurate time precision, The time point at which the variation of the elevation angle-Doppler frequency shift value best conforms to the monotonically decreasing function and the variance of the Doppler residual and pseudorange residual is the smallest is taken as the final rough estimate time of the receiver's local time.

7. The GNSS receiver rapid hot start positioning method according to claim 1, characterized in that: The method for iteratively correcting the three-dimensional position of the receiver, the GNSS system time difference and the receiver clock bias includes: constructing a matrix calculation formula related to the three-dimensional position of the receiver, the GNSS system time difference and the receiver clock bias for the pseudo-range measurement residuals of all satellites, and solving the matrix calculation formula using the least squares method.

8. The GNSS receiver rapid hot start positioning method according to claim 1, characterized in that: The step S1 adopts a parallel search algorithm to search for multiple frequency and code phase combinations at the same time, converts the time domain signal into the frequency domain signal using fast Fourier transform, and immediately records the relevant parameters of the signal once the satellite signal is captured.

9. A GNSS receiver rapid hot start positioning system, executing a GNSS receiver rapid hot start positioning method according to any one of claims 1 to 8, characterized in that: include: The fast capture circuit module is connected to the data processing module; The storage module is connected to the data processing module, and the storage module adopts non-volatile memory FLASH.

10. The GNSS receiver rapid hot start positioning system according to claim 9, characterized in that: The fast acquisition circuit module includes a GNSS radio frequency chip and a high-performance embedded processor. The radio frequency chip receives satellite signals and down-converts them to intermediate frequency signals. The embedded processor runs an optimized search algorithm to process the intermediate frequency signals.

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