Method and device for receiving Galileo HAS service and evaluating positioning performance

Abstract

The invention discloses a Galileo HAS service receiving and positioning performance evaluation method and device, and belongs to the technical field of satellite positioning and navigation. The method comprises the steps that Galileo E6B frequency band signals are captured through USRP equipment, after radio frequency and direct current signals are separated through a bias device, self-adaptive layering processing is carried out through GNSS-SDR software, and the self-adaptive layering processing comprises dynamic sampling and interference suppression of a radio frequency adaptation layer, double-domain cooperative synchronization and self-adaptive decoding of a baseband intelligent processing layer and self-adaptive decoding of a baseband intelligent processing layer. And carrying out multi-dimensional feature mapping and robust verification on the HAS correction number extraction layer, and finally outputting a standardized HAS correction number. And in combination with a real-time precise single-point positioning technology, centimeter-level dynamic positioning is realized, and the positioning performance is evaluated through comparison with reference station data. According to the method, the robustness and precision of signal receiving and processing are improved, and the method is suitable for high-precision positioning requirements in a complex environment.

Description

Technical Field

[0001] This invention belongs to the field of satellite positioning and navigation technology, specifically relating to a method and apparatus for receiving Galileo HAS services and evaluating positioning performance. Background Technology

[0002] With the continuous development of Global Navigation Satellite Systems (GNSS), the demand for high-precision positioning services in fields such as surveying and mapping, autonomous driving, precision agriculture, and disaster monitoring is becoming increasingly urgent. As one of the four core global navigation systems, the Galileo satellite navigation system provides its High Accuracy Service (HAS) via the E6B signal band, broadcasting real-time orbit, clock bias, and code deviation corrections globally free of charge. This provides users with open high-precision enhancement services, significantly reducing the cost and barriers to achieving centimeter-level positioning accuracy.

[0003] HAS corrections are transmitted in E6B signals using the Reed-Solomon coding scheme, improving the data's error and interference resistance. Precise Point Positioning (PPP) technology can utilize these corrections, combined with multi-frequency carrier phase observations, to achieve high-precision positioning without a ground reference station, making it particularly suitable for remote areas or mobile environments. However, the actual performance of PPP is still constrained by various factors, including ionospheric and tropospheric delays during signal propagation, receiver dynamic stress, multipath effects, and the completeness and timeliness of correction decoding. Currently, a systematic evaluation of the performance of Galileo HAS service in real-world dynamic scenarios, especially its correction reception stability, positioning convergence time, and accuracy availability, is still lacking.

[0004] Therefore, there is an urgent need to develop a dedicated method and device that can reliably receive HAS signals, extract corrections in real time, and perform high-precision PPP calculation and performance evaluation, in order to verify the actual performance of HAS services and promote their large-scale deployment and development in high-precision applications. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method and apparatus for receiving Galileo HAS services and evaluating positioning performance. By receiving Galileo HAS signals and utilizing advanced signal processing algorithms and communication technologies, stable signal reception and accurate signal processing are achieved. Simultaneously, by combining precise point positioning technology and performance evaluation methods, real-time and comprehensive evaluation of PPP performance under Galileo HAS services is performed.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A method for receiving Galileo HAS services and evaluating positioning performance, the method comprising:

[0008] Step 1: Receive and preprocess the E6B band radio frequency signal broadcast by the Galileo satellite using a GNSS active antenna;

[0009] Step 2: Separate the preprocessed E6B RF signal from the DC power supply to obtain a pure E6B RF signal;

[0010] Step 3: Down-convert and sample the pure E6B RF signal to convert it into a digital intermediate frequency (IQ) signal;

[0011] Step 4: The digital intermediate frequency IQ signal is processed using an adaptive hierarchical processing architecture, including dynamic sampling and interference suppression of the radio frequency adaptation layer, dual-domain collaborative synchronization and adaptive decoding of the baseband intelligent processing layer, and multi-dimensional feature mapping and robust verification of the HAS correction extraction layer, and finally outputs the standardized HAS correction.

[0012] Step 5: Perform real-time precise single-point positioning calculation using the standardized HAS corrections and evaluate the positioning accuracy.

[0013] On the other hand, the present invention provides a device for receiving Galileo HAS services and evaluating positioning performance, comprising:

[0014] The signal receiving module is used to receive and preprocess E6B band radio frequency signals broadcast by Galileo satellites via a GNSS active antenna.

[0015] The separation module is used to separate the preprocessed E6B RF signal from the DC power supply to obtain a pure E6B RF signal.

[0016] The conversion module is used to downconvert and sample the pure E6B radio frequency signal, converting it into a digital intermediate frequency (IQ) signal.

[0017] The processing module is used to process the digital intermediate frequency IQ signal using an adaptive hierarchical processing architecture, including dynamic sampling and interference suppression of the radio frequency adaptation layer, dual-domain collaborative synchronization and adaptive decoding of the baseband intelligent processing layer, and multi-dimensional feature mapping and robust verification of the HAS correction extraction layer, and finally outputs the standardized HAS correction.

[0018] The output module is used to perform real-time precise single-point positioning calculations using the standardized HAS corrections and to evaluate the positioning accuracy.

[0019] 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 method for receiving Galileo HAS services and evaluating positioning performance.

[0020] 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 method for receiving Galileo HAS services and evaluating positioning performance.

[0021] The beneficial effects of this invention are as follows:

[0022] 1. Significantly improved signal reception quality and robustness of correction data extraction. The system employs dynamic sampling and adaptive interference suppression technology, effectively reducing data redundancy, improving the signal-to-noise ratio, and ensuring stable reception of E6B signals in complex electromagnetic environments. Through dual-domain collaborative synchronization and adaptive demodulation mechanisms, the demodulation success rate of navigation messages is greatly improved, the bit error rate is significantly reduced, and the high availability and integrity of HAS correction data are ensured.

[0023] 2. High-precision dynamic positioning and real-time performance evaluation were achieved. The method integrates observation data from multiple systems and HAS corrections, and relies on advanced PPP solution models and filtering algorithms to achieve centimeter-level real-time positioning in dynamic scenarios. By comparing the true values ​​of the base station in real time, the positioning accuracy in the horizontal and vertical directions can be comprehensively evaluated, enabling users to monitor positioning performance in real time and optimize the system in a timely manner.

[0024] 3. The system has a high degree of integration and wide applicability, providing a complete solution for the engineering application of Galileo HAS services, and effectively promoting the actual deployment and development of high-precision positioning technology in different scenarios. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of a method for receiving Galileo HAS services and evaluating positioning performance according to the present invention.

[0026] Figure 2 This is a schematic diagram of the GNSS-SDR software of this invention. Detailed Implementation

[0027] The following detailed description, in conjunction with the accompanying drawings and embodiments, illustrates the implementation process of this invention for receiving Galileo E6B signals and obtaining HAS corrections using a software-defined receiver (SDR). The technical solution of this embodiment ensures accurate extraction of HAS corrections, providing data support for subsequent high-precision positioning. Specifically, as shown... Figure 1 and Figure 2 As shown, the method includes the following steps:

[0028] Step 1: Reception and preliminary amplification of Galileo E6B radio frequency signals. The E6B radio frequency signals broadcast by the Galileo satellite are received via a GNSS active antenna and preprocessed to provide effective input for subsequent signal processing.

[0029] The GNSS active antenna is deployed in an unobstructed open environment (such as a rooftop or open field). The antenna has a built-in low-noise amplifier (LNA) to suppress the interference of environmental noise on weak satellite signals. At the same time, the antenna is connected to the bias tere via a coaxial cable and is powered by DC bias (5V / 12V) from the back-end USRP equipment to ensure that the antenna's low-noise amplifier works properly.

[0030] • Input: E6B band radio frequency signal transmitted by the Galileo satellite (center frequency 1278.75MHz, including HAS correction).

[0031] • Output: A low-noise amplified E6B RF signal (signal-to-noise ratio ≥35dB), which is transmitted via a coaxial cable to a bias-Tee for subsequent signal processing.

[0032] Step 2: Separation of RF signal and DC power supply. A bias-Tee is used to separate the preprocessed E6B RF signal from the DC power supply, resulting in a clean E6B RF signal. The core function is to separate the superimposed "RF signal" and "DC power supply" in the coaxial cable, avoiding interference from the power supply signal to the RF signal, while ensuring the continuity of the antenna power supply link.

[0033] The bias unit employs a high-frequency choke and capacitor coupling structure, where the capacitor allows the radio frequency signal (AC) to pass through, and the choke allows the DC power supply (DC) to pass through. The input of the bias unit receives a mixed signal of "radio frequency signal + DC power supply" from the GNSS active antenna, as well as the DC bias power supply from the USRP device. Through the above structure, it outputs a pure radio frequency signal and an independent power supply signal, respectively.

[0034] • Inputs: ① Mixed signal of “E6B RF signal + DC power supply” output from GNSS active antenna; ② 5V / 12V DC bias power supply output from USRP device.

[0035] • Output: ① Separated pure E6B RF signal (transmitted to USRP device); ② Independent DC power supply signal (retransmitted back to GNSS active antenna to power antenna LNA).

[0036] Step 3, Digital Conversion of RF Signal. The pure E6B RF signal is down-converted and sampled by the USRP device, converted into a digital intermediate frequency (IQ) signal, completing the conversion from analog RF signal to digital IQ signal. This is the hardware component of the SDR architecture.

[0037] The USRP device receives a clean E6B RF signal from the bias converter. First, it down-converts the E6B RF signal to an intermediate frequency (e.g., 10MHz) through its internal RF front-end (including mixer and filter). Then, it samples the intermediate frequency signal through a 12-bit high-speed analog-to-digital converter (ADC) with a sampling rate configured at 10MS / s (to match the bandwidth requirements of the E6B signal). Simultaneously, the USRP device connects to a computer via a USB 3.0 interface to receive configuration instructions from the GNSS-SDR software (including parameters such as center frequency 1278.75MHz, sampling rate 10MS / s, and RF gain 40dB) to ensure parameter matching during the digitization process.

[0038] • Inputs: ① Pure E6B RF signal output from the bias converter; ② Hardware configuration instructions (center frequency, sampling rate, gain) output from the GNSS-SDR software.

[0039] • Output: A digitized intermediate frequency IQ quadrature signal (in 16-bit binary format, containing I-channel in-phase components and Q-channel quadrature components), which is transmitted to a computer in real time via a USB 3.0 interface.

[0040] Step 4: The digital intermediate frequency (IF) IQ signal is processed using an adaptive hierarchical processing architecture, including dynamic sampling and interference suppression in the RF adaptation layer, dual-domain collaborative synchronization and adaptive decoding in the baseband intelligent processing layer, and multi-dimensional feature mapping and robust verification in the HAS correction extraction layer. Finally, a standardized HAS correction is output, which solves the problems of sampling redundancy, low synchronization accuracy, and poor extraction robustness in traditional SDR processing.

[0041] First layer: Radio frequency adaptation layer - dynamic sampling and interference suppression (preprocessing innovation).

[0042] After receiving the digital intermediate frequency (IF) IQ signal transmitted by the USRP device, the ADC equivalent sampling rate is first dynamically adjusted based on the real-time bandwidth of the Galileo E6B signal. Redundant data is eliminated through adaptive sampling rate matching (reducing storage and computation overhead by 30%). Bandwidth self-adaptation and buffer management are performed based on instantaneous spectral energy. When bandwidth redundancy occurs, downsampling or resampling is performed. At the same time, an adaptive notch filter algorithm is used to detect narrowband interference (such as adjacent-channel electromagnetic noise and co-channel interference signals) in real time. By dynamically suppressing the interference frequency, the signal-to-noise ratio is improved by ≥5dB, and a pre-processed IQ signal with no redundancy and low interference is output.

[0043] • Input: ① Digital intermediate frequency IQ signal output by USRP device; ② Parameter file of GNSS-SDR software pre-configured on computer (including dynamic sampling rate threshold and interference detection threshold).

[0044] • Output: Preprocessed, low-interference, bandwidth-adapted digital intermediate frequency (IF) IQ signal.

[0045] The second layer: Baseband intelligent processing layer – dual-domain collaborative synchronization and adaptive decoding (core innovation).

[0046] Dual-domain cooperative synchronization: Based on the time-frequency dual-domain cooperative synchronization mechanism, firstly, in the frequency domain, the code phase and carrier frequency offset (±5kHz range) of the Galileo E6B signal are traversed through the FFT-based parallel acquisition algorithm to lock the coarse synchronization parameters. The received signal is correlated with the local pseudocode or impulse response (mathematically equivalent to convolution or frequency domain multiplication) to achieve code phase and frame synchronization. Then, in the time domain, a state-space model of the carrier and code is constructed. Kalman filtering or extended Kalman filtering is used to jointly estimate the PLL (Phase-Locked Loop) and DLL (Delay-Locked Loop) to compensate for Doppler frequency shift and code phase drift caused by satellite motion in real time. The synchronization accuracy is improved by 10% compared with the traditional single-domain synchronization.

[0047] Adaptive Decoding: The demodulation algorithm is dynamically selected based on the baseband signal-to-noise ratio (SNR)—efficient QPSK hard-decision demodulation is used when SNR ≥ 30dB, and soft-decision demodulation (combined with channel estimation compensation) is initiated when SNR < 30dB. This ensures that the demodulation success rate of Galileo E6B navigation messages (including the original data block of HAS corrections) is ≥ 99.5%. Obvious erroneous messages are eliminated through preliminary CRC check. After frame synchronization and symbol decision, the bit stream is deinterleaved (if applicable), and the FEC decoding process is performed: if convolutional codes exist, soft-decision decoding such as Viterbi / BCJR is used, followed by block-level error correction (e.g., Reed-Solomon). Finally, the frame integrity is checked with CRC (Cyclic Redundancy Check) to recover the HAS message.

[0048] • Input: Preprocessed IQ signal output from the RF adapter layer.

[0049] • Output: Galileo E6B navigation message after preliminary verification (including raw data of HAS corrections).

[0050] The third layer: HAS correction extraction layer - multidimensional feature mapping and robust verification (application layer innovation).

[0051] Multidimensional feature mapping: The navigation message after preliminary verification is used to establish a multidimensional feature mapping table according to "satellite PRN number - orbit deviation (radial / tangential / normal) - satellite clock error - ranging code deviation", and associate it with the data fields in the Galileo HAS interface specification to quickly match and extract the target correction parameters;

[0052] Robust verification: Employs a two-level mechanism of "CRC double check + multi-frame redundancy cross-check"—first, confirm the integrity of the single-frame correction number through CRC check, and then cross-check the redundant fields of three consecutive frames of data to correct occasional bit errors (bit error rate ≤ 10%). -6 );

[0053] • Input: Navigation message after preliminary verification output from the baseband intelligent processing layer.

[0054] • Output: Standardized HAS correction data file (including satellite orbital deviation, clock error, and ranging code deviation; data format is binary or text).

[0055] Step 5: Using the standardized HAS corrections and multi-system observation data, perform real-time precise point positioning (PPP) calculations, and evaluate the positioning accuracy by comparing it with the true values ​​from the base station. The real-time Galileo / GPS dynamic PPP positioning experiment based on HAS corrections utilizes HAS corrections combined with Galileo / GPS dual-system observation data to complete precise point positioning (PPP) in dynamic scenarios, verifying the application effect of HAS corrections. Specifically, it includes:

[0056] Data preparation and synchronization: Obtain the standardized HAS correction file output from step 4, and Galileo / GPS observation data (Galileo E1 / E5a, GPS L1 / L2 pseudorange / carrier phase), align the two types of data using UTC timestamps (accuracy ≤1ms), and remove outlier data;

[0057] PPP solution model configuration: Enable "non-difference non-combination model" in the dual-system PPP solution module, input HAS correction, and set the initial parameters of Kalman filter (process noise covariance, observation noise covariance).

[0058] Dynamic positioning execution: Set the test scenario to dynamic mode (e.g., vehicle-mounted, speed ≤60km / h), receive synchronized data in real time, and recursively calculate the receiver's real-time position (latitude, longitude, and elevation) through the dual-system PPP solution module. The positioning update rate is 1Hz, and the positioning result at each moment is recorded.

[0059] Positioning accuracy verification: Import the known true coordinate values ​​of the DGPS base station (accuracy ≤ 5cm) through the positioning accuracy verification module, compare the output dynamic positioning results at each moment, calculate the RMS in the horizontal direction (east and north) and the RMS in the vertical direction (elevation), and generate a positioning performance evaluation report with HAS correction (including accuracy data, convergence time, and accuracy comparison with no HAS correction).

[0060] On the other hand, the present invention provides a device for receiving Galileo HAS services and evaluating positioning performance, the various modules of which can implement the various steps of the aforementioned method, specifically including:

[0061] The signal receiving module is used to receive and preprocess E6B band radio frequency signals broadcast by Galileo satellites via a GNSS active antenna.

[0062] The separation module is used to separate the preprocessed E6B RF signal from the DC power supply to obtain a pure E6B RF signal.

[0063] The conversion module is used to downconvert and sample the pure E6B radio frequency signal, converting it into a digital intermediate frequency (IQ) signal.

[0064] The processing module is used to process the digital intermediate frequency IQ signal using an adaptive hierarchical processing architecture, including dynamic sampling and interference suppression of the radio frequency adaptation layer, dual-domain collaborative synchronization and adaptive decoding of the baseband intelligent processing layer, and multi-dimensional feature mapping and robust verification of the HAS correction extraction layer, and finally outputs the standardized HAS correction.

[0065] The output module is used to perform real-time precise single-point positioning calculations using the standardized HAS corrections and to evaluate the positioning accuracy.

[0066] 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 method for receiving Galileo HAS services and evaluating positioning performance.

[0067] 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 method for receiving Galileo HAS services and evaluating positioning performance.

[0068] In summary, this invention mainly realizes a method and apparatus for receiving Galileo HAS services and evaluating positioning performance. Through a specially designed receiving module, it stably receives E6B signals from the Galileo satellite, and then uses signal processing technology to analyze and obtain HAS corrections. Based on this, the apparatus uses the RTPPP algorithm to achieve fast and accurate precise point positioning. Simultaneously, the apparatus is also equipped with a performance evaluation module, which can monitor and evaluate positioning performance in real time, ensuring the stability and reliability of service quality. This provides users with a new high-precision positioning solution, not only improving positioning accuracy and efficiency, but also ensuring high-quality service output through real-time performance evaluation. It not only helps promote the application and development of the Galileo system in the field of high-precision positioning, but also provides useful reference and guidance for research and practice in related fields. Through in-depth evaluation of the Galileo HAS service and its real-time PPP performance, positioning accuracy and reliability can be further improved, meeting various high-precision positioning needs and promoting the widespread application and continuous development of Galileo HAS technology.

[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 receiving Galileo HAS services and evaluating positioning performance, characterized in that, The method includes: Step 1: Receive the E6B band radio frequency signal broadcast by the Galileo satellite through the GNSS active antenna and preprocess it to obtain the preprocessed E6B radio frequency signal; Step 2: Separate the preprocessed E6B RF signal from the DC power supply to obtain a pure E6B RF signal; Step 3: Down-convert and sample the pure E6B RF signal to convert it into a digital intermediate frequency (IQ) signal; Step 4: The digital intermediate frequency IQ signal is processed using an adaptive hierarchical processing architecture, including dynamic sampling and interference suppression of the radio frequency adaptation layer, dual-domain collaborative synchronization and adaptive decoding of the baseband intelligent processing layer, and multi-dimensional feature mapping and robust verification of the HAS correction extraction layer, and finally outputs the standardized HAS correction. Step 5: Perform real-time precise single-point positioning calculation using the standardized HAS corrections and evaluate the positioning accuracy.

2. The method for receiving Galileo HAS service and evaluating positioning performance according to claim 1, characterized in that, In step 1, the preprocessing includes: amplifying the E6B radio frequency signal through the low-noise amplifier built into the GNSS active antenna, suppressing ambient noise, and outputting an amplified signal with a signal-to-noise ratio of not less than 35dB.

3. The method for receiving Galileo HAS service and evaluating positioning performance according to claim 1, characterized in that, In step 2, based on the biasing device using a high-frequency choke and capacitor coupling structure, the preprocessed E6B RF signal is separated from the DC power supply to obtain a pure E6B RF signal.

4. The method for receiving Galileo HAS service and evaluating positioning performance according to claim 1, characterized in that, In step 3, the downconversion process downconverts the pure E6B RF signal to a 10MHz intermediate frequency and samples it at a sampling rate of 10MS / s through a 12-bit analog-to-digital converter to generate a 16-bit binary format I and Q quadrature signal.

5. The method for receiving Galileo HAS service and evaluating positioning performance according to claim 1, characterized in that, In step 4, the dynamic sampling and interference suppression of the RF adaptation layer specifically includes: dynamically adjusting the ADC equivalent sampling rate based on the real-time bandwidth of the E6B RF signal, and using an adaptive notch filter algorithm to detect and suppress narrowband interference in real time; the dual-domain collaborative synchronization and adaptive decoding of the baseband intelligent processing layer specifically includes: in the frequency domain, using an FFT-based parallel acquisition algorithm to traverse the code phase and carrier frequency offset within a range of ±5kHz to achieve coarse synchronization; in the time domain, using Kalman filtering to optimize the bandwidth parameters of the carrier tracking loop and code tracking loop in real time to compensate for the Doppler frequency shift and code phase drift caused by satellite motion to achieve fine synchronization; real-time monitoring of the baseband signal-to-noise ratio, using QPSK hard decision demodulation when SNR≥30dB, and starting soft decision demodulation combined with channel estimation compensation when SNR<30dB, and eliminating erroneous messages through preliminary CRC check.

6. The method for receiving Galileo HAS service and evaluating positioning performance according to claim 5, characterized in that, In step 4, the multidimensional feature mapping and robust verification of the HAS correction extraction layer specifically includes: establishing a multidimensional feature mapping table for the navigation message after preliminary verification according to the satellite PRN number, radial / tangential / normal orbit deviation, satellite clock error and ranging code deviation, associating it with the data fields in the Galileo HAS interface specification, quickly matching and extracting the target correction parameters; using CRC secondary verification to confirm the integrity of the single frame correction, and then performing cross-verification through the redundant fields of three consecutive frames of data to correct occasional bit errors.

7. The method for receiving Galileo HAS service and evaluating positioning performance according to claim 1, characterized in that, Step 5 includes: aligning the HAS correction with the multi-system observation data using UTC timestamps, performing dynamic precise single-point positioning using a non-differential non-combined PPP model and Kalman filtering, calculating the RMS accuracy indices in the east, north, and elevation directions, and generating a positioning performance evaluation report.

8. A device for receiving Galileo HAS services and evaluating positioning performance, characterized in that, include: The signal receiving module is used to receive the E6B band radio frequency signal broadcast by the Galileo satellite through the GNSS active antenna and perform preprocessing to obtain the preprocessed E6B radio frequency signal; The separation module is used to separate the preprocessed E6B RF signal from the DC power supply to obtain a pure E6B RF signal. The conversion module is used to downconvert and sample the pure E6B radio frequency signal, converting it into a digital intermediate frequency (IQ) signal. The processing module is used to process the digital intermediate frequency IQ signal using an adaptive hierarchical processing architecture, including dynamic sampling and interference suppression of the radio frequency adaptation layer, dual-domain collaborative synchronization and adaptive decoding of the baseband intelligent processing layer, and multi-dimensional feature mapping and robust verification of the HAS correction extraction layer, and finally outputs the standardized HAS correction. The output module is used to perform real-time precise single-point positioning calculations using the standardized HAS corrections and to evaluate the positioning accuracy.

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 method for receiving Galileo HAS services and evaluating positioning performance as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores executable instructions that, when executed by a processor, enable the processor to implement the method for receiving Galileo HAS services and evaluating positioning performance as described in any one of claims 1-7.

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