Multi-domain evaluation method of gnss signal quality

Abstract

The application provides a GNSS signal quality multi-domain evaluation method, which fully considers the performance of GNSS signals in six dimensions of time domain, frequency domain, modulation domain, correlation domain, consistency domain and signal parameters, respectively establishes plane coordinates in the six dimensions and constructs a normalized evaluation index polygon, and then uses the geometric area of the polygon to measure the evaluation result of the signal in the evaluation dimension. The application uses a parallel data transmission mode and a data processing method of area or volume operation of simple geometric bodies to integrate various evaluation indexes and converge the number of indexes, so as to comprehensively evaluate the satellite navigation signal in multiple dimensions in a hierarchical manner, so that the user can obtain reliable and efficient navigation signal evaluation results in time.

Description

Technical Field

[0001] This invention relates to the field of global satellite navigation signal quality assessment technology, specifically a multi-domain assessment method for GNSS signal quality. Background Technology

[0002] GNSS signal quality assessment is crucial in systems such as vehicle navigation, aviation navigation, marine navigation, and mobile device positioning services. It helps determine the accuracy of a user's current location and the reliability of navigation system predictions, and allows for the selection of appropriate positioning services or auxiliary positioning methods based on signal quality. It also has significant applications in scientific research and measurement, such as earthquake monitoring, geological exploration, and atmospheric science, where it helps researchers determine the reliability and accuracy of measurement data, improving the credibility of research results.

[0003] Early GNSS signal assessments primarily focused on system availability and reliability. Signal quality assessment relied mainly on GPS receiver indicator lights or alarms to display signal strength and reception quality, as well as user positioning accuracy. With the application of three GNSS frequencies, navigation and positioning accuracy improved significantly, and GNSS signal quality assessment shifted from assessing availability and reliability to evaluating signal quality itself. During this stage, scholars from various countries mainly focused on how to assess and compare the signal quality and performance of different systems, with research primarily using single indicators such as robust quality factor, relative carrier-to-noise ratio, acquisition performance, sensitivity, and computational complexity. However, single indicators are insufficient to accurately describe GNSS signal quality. More scholars introduced various indicators such as power characteristics (signal integrity, clock accuracy, and multipath effects), frequency domain characteristics, time domain characteristics, correlation domain characteristics, and signal consistency to conduct signal quality assessments. Later, neural networks were used to achieve adaptive GNSS signal assessment. However, these assessment systems generally suffer from slow timeliness and cannot meet the current high real-time requirements of navigation and positioning. Especially when satellite navigation signals are used for maritime navigation, they are easily affected by interference or attenuation, and real-time, reliable signal quality assessment results can promptly and effectively alert crew members to potential navigation risks.

[0004] In recent years, with the rapid development of cooperative positioning technology, in order to improve the navigation accuracy of cooperative positioning, the evaluation of GNSS signal quality has become more detailed. On the one hand, more and more relevant evaluation indicators have been proposed, and the related calculation methods have become more diversified. On the other hand, the evaluation content focuses more on specific, dispersed application scenarios, considering system evaluation indicators or proposing new evaluation indicators. Some schemes analyze the power spectrum deviation, constellation diagram, SCB curve, correlation loss, and other indicators of Beidou satellite civilian B2 band signals; some schemes evaluate the carrier-to-noise ratio, pseudorange and carrier phase measurement accuracy, and single-satellite timing accuracy of Luojia-1 satellite navigation signals; some use the CNMC algorithm to improve the pseudorange multipath error of BDS-3 medium Earth orbit modulated signals; some have established five-system three-frequency ionospheric combined PPP (IF-PPP) and non-combined PPP (UC-PPP) models to evaluate the system's performance in static and dynamic PPP; and some have proposed an unweighted algorithm for calculating protection levels to evaluate the availability performance of GNSS receiver autonomous integrity monitoring (RAIM). Summary of the Invention

[0005] Currently, various evaluation indicators are relatively scattered and numerous. Most research on evaluation only serves the system performance analysis in a specific application scenario, which is not conducive to the standardization and normalization of GNSS applications. In order to meet the high real-time and reliability requirements of GNSS in various navigation and positioning systems, and to further improve the deployment of GNSS and better adapt to the era of the Internet of Things, this invention proposes a multi-domain evaluation method for GNSS signal quality. Based on the signal quality evaluation results of GNSS in six dimensions, a parallel data transmission method and a data processing method of simple geometric area or volume calculation are used to integrate various evaluation indicators by domain and converge the number of indicators to conduct a multi-dimensional and hierarchical comprehensive evaluation of satellite navigation signals, so that users can obtain reliable and efficient navigation signal evaluation results in a timely manner.

[0006] This invention, on the one hand, fully considers the performance of GNSS signals in six dimensions: time domain, frequency domain, modulation domain, correlation domain, consistency domain, and signal parameters. Planar coordinates are established in each of these six dimensions, and normalized evaluation index polygons are constructed. The geometric area of ​​the polygons is then used to measure the evaluation result of the signal in each evaluation dimension. On the other hand, based on the existing evaluation results in the six dimensions, a three-dimensional coordinate system is established, and an octagonal pyramid containing the normalized multi-domain evaluation results is constructed. The volume of the octagonal pyramid is then used to characterize the final evaluation result of the GNSS signal. This invention aims to provide a complete, efficient, and real-time evaluation scheme for future high-precision, multi-mode, and enhanced satellite navigation systems.

[0007] The technical solution of this invention is as follows:

[0008] A multi-domain evaluation method for GNSS signal quality includes the following steps:

[0009] Step 1: Establish a multi-domain evaluation three-dimensional coordinate system for GNSS signals and six sub-evaluation model plane coordinate systems. The sub-evaluation model plane coordinate systems include: a four-dimensional plane evaluation coordinate system in the time domain, a one-dimensional linear evaluation coordinate system in the frequency domain, a four-dimensional plane evaluation coordinate system in the modulation domain, a three-dimensional plane evaluation coordinate system in the correlation domain, a three-dimensional plane evaluation coordinate system in the consistency domain, and a six-dimensional plane evaluation coordinate system for signal parameters.

[0010] The time-domain four-dimensional planar evaluation coordinate system is: with a certain point as the origin, and within the same plane, respectively using the signal-noise magnitude ε... N Timing error sensitivity η, level noise tolerance ν N The zero-crossing distortion τ is the coordinate axis, and the angle between adjacent coordinate axes is 90°;

[0011] The frequency domain one-dimensional linear evaluation coordinate system is: with a certain point as the origin and the signal-to-noise ratio (SNR) as the coordinate axis;

[0012] The modulation domain four-dimensional plane evaluation coordinate system is: with a certain point as the origin, and within the same plane, respectively using the I / Q branch amplitude ratio a... B Signal amplitude error a e Signal phase error p e Error vector amplitude ε EVM The coordinate axes are defined by the coordinate axes, and the angle between adjacent coordinate axes is 90°.

[0013] The relevant domain three-dimensional planar evaluation coordinate system is as follows: with a certain point as the origin, and within the same plane, the relevant loss is C. L S-curve deviation S C The normalized second moment Z is the coordinate axis, and the angle between adjacent coordinate axes is 120°;

[0014] The consistent domain three-dimensional plane evaluation coordinate system is as follows: with a certain point as the origin, in the same plane, the relative pseudorange increment ε between the same signal ranging code and the carrier is used respectively. x The relative pseudorange increment ε between different ranging codes at the same frequency point ρ The relative pseudorange increment between the same ranging codes at different frequencies The coordinate axes are defined by the coordinate axes, and the angle between adjacent coordinate axes is 120°.

[0015] The six-dimensional signal parameter plane evaluation coordinate system is as follows: with a certain point as the origin, in the same plane, the coordinates are: the normalized code tracking accuracy σ of the coherent EML loop, the normalized tracking spectral sensitivity η of the coherent EML loop, the normalized multipath error ε of the coherent EML loop, and the normalized code tracking accuracy σ of the incoherent EML loop.p Normalized multipath error ε of incoherent EMLP loop p The normalized anti-interference quality factor q is the coordinate axis, and the angle between adjacent coordinate axes is 60°.

[0016] The GNSS multi-domain evaluation three-dimensional coordinate system is: with a certain point as the origin, and the time-domain index s of the signal as the coordinate system. T Frequency domain index s n Modulation domain index s M Related domain indicators s r Consistency domain index s c and signal parameter index s α Let be the coordinate axes, where s T s n s M s r The coordinate axes are in the same plane, and the angle between adjacent coordinate axes is 90°. c s α The coordinate axis is perpendicular to s T s n s M s r The plane formed by the coordinate axes, with an included angle of 180°;

[0017] Step 2: For the acquired satellite navigation signals, calculate the normalized results of each index under the six sub-evaluation models: Time-domain index s T Frequency domain index s n Modulation domain index s M Related domain indicators s r Consistency domain index s c and signal parameter index s α ;

[0018] Step 3: Based on the normalized index values ​​obtained in Step 2 under the six sub-evaluation models, calculate the volume V of the octagonal pyramid with the six normalized index values ​​as vertices in the GNSS multi-domain evaluation stereo coordinate system. k and with the volume V of the octagonal pyramid k As a result of real-time quality assessment of satellite navigation signals.

[0019] Furthermore, time-domain indicators

[0020] Furthermore, frequency domain indicators SNR is the signal-to-noise ratio estimate.

[0021] Furthermore, modulation domain indicators

[0022] Furthermore, related domain indicators

[0023] Furthermore, consistency domain indicators

[0024] Furthermore, signal parameter indicators

[0025] Beneficial effects

[0026] The present invention has the following advantages:

[0027] (1) Using GNSS navigation signal data, frequency domain, time domain, correlation domain, modulation domain, consistency domain and signal parameter evaluation models were established, and the evaluation results were transmitted in parallel data to realize multi-dimensional quality evaluation of the signal;

[0028] (2) Using the evaluation results of the six sub-dimensions and the correlation between each dimension, a two-level architecture GNSS signal quality evaluation model was established, and a corresponding fast evaluation method was constructed. The constructed evaluation system is calculated according to the area and volume of geometric figures. The calculation is simple and the amount of calculation is relatively low. It can reflect the final evaluation results in real time.

[0029] (3) A multi-domain GNSS signal quality assessment architecture was constructed, which can realize independent assessment of each domain and overall signal quality assessment. During this process, various assessment indicators are integrated by domain and the number of indicators is reduced, which can realize multi-domain joint assessment and has higher reliability, providing a good solution for the standardized and normalized assessment of GNSS applications in various navigation systems.

[0030] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0031] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0032] Figure 1 : Schematic diagram of subdomain evaluation model; where (a) time domain sub-evaluation model, (b) frequency domain sub-evaluation axis, (c) modulation domain sub-evaluation model, (d) modulation domain sub-evaluation model, (e) consistency domain sub-evaluation model, and (f) signal parameter domain sub-evaluation model.

[0033] Figure 2 This is a schematic diagram of the GNSS multi-domain evaluation system, which includes evaluation results in six dimensions: time domain, frequency domain, modulation domain, correlation domain, consistency domain, and signal parameters. The area of ​​the black octagonal pyramid represents the final signal evaluation result.

[0034] Figure 3This is a flowchart of the GNSS multi-domain evaluation system architecture. The architecture consists of six dimensions: time-domain sub-evaluation model, frequency-domain sub-evaluation model, modulation-domain sub-evaluation model, correlation-domain sub-evaluation model, consistency-domain sub-evaluation model, and signal parameter sub-evaluation model. Detailed Implementation

[0035] The embodiments of the present invention are described in detail below. These embodiments are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0036] This embodiment establishes GNSS signal sub-evaluation models from several dimensions, including frequency domain, time domain, correlation domain, modulation domain, consistency domain, and signal parameters. Furthermore, it establishes a multi-domain GNSS evaluation system to perform real-time and rapid quality assessment of GNSS signals. The specific structure is shown in Table 1.

[0037] Table 1. Contents of the GNSS Multi-Domain Evaluation Architecture

[0038]

[0039]

[0040] Specifically, the following steps are included:

[0041] Step 1: Establish a multi-domain evaluation three-dimensional coordinate system for GNSS signals and six sub-evaluation model plane coordinate systems. The sub-evaluation model plane coordinate systems include: a four-dimensional plane evaluation coordinate system in the time domain, a one-dimensional linear evaluation coordinate system in the frequency domain, a four-dimensional plane evaluation coordinate system in the modulation domain, a three-dimensional plane evaluation coordinate system in the correlation domain, a three-dimensional plane evaluation coordinate system in the consistency domain, and a six-dimensional plane evaluation coordinate system for signal parameters.

[0042] like Figure 1 As shown in (a), the time-domain four-dimensional planar evaluation coordinate system is: with point O as the origin, and within the same plane, respectively using the signal-noise magnitude ε... N Timing error sensitivity η, level noise tolerance ν N The zero-crossing distortion τ is the coordinate axis, and the angle between adjacent coordinate axes is 90°;

[0043] like Figure 1 As shown in (b), the frequency domain one-dimensional linear evaluation coordinate system is: with point O as the origin and the signal-to-noise ratio (SNR) estimate as the coordinate axis;

[0044] like Figure 1 As shown in (c), the four-dimensional plane evaluation coordinate system of the modulation domain is: with point O as the origin, and within the same plane, the amplitude ratios of the I / Q branches are respectively a. B Signal amplitude error a e Signal phase error p e Error vector amplitude εEVM The coordinate axes are defined by the coordinate axes, and the angle between adjacent coordinate axes is 90°.

[0045] like Figure 1 As shown in (d), the three-dimensional plane evaluation coordinate system of the relevant domain is: with point O as the origin, and in the same plane, with the relevant loss as C... L S-curve deviation S C The normalized second moment Z is the coordinate axis, and the angle between adjacent coordinate axes is 120°;

[0046] like Figure 1 As shown in (e), the three-dimensional plane evaluation coordinate system of the uniform domain is: with point O as the origin, and within the same plane, the relative pseudorange increment ε between the same signal ranging code and the carrier is used respectively. x The relative pseudorange increment ε between different ranging codes at the same frequency point ρ The relative pseudorange increment between the same ranging codes at different frequencies The coordinate axes are defined by the coordinate axes, and the angle between adjacent coordinate axes is 120°.

[0047] like Figure 1 As shown in (f), the six-dimensional signal parameter plane evaluation coordinate system is as follows: with point O as the origin, in the same plane, the coordinates are: the normalized code tracking accuracy σ of the coherent EML loop, the normalized tracking spectrum sensitivity η of the coherent EML loop, the normalized multipath error ε of the coherent EML loop, and the normalized code tracking accuracy σ of the incoherent EML loop. p Normalized multipath error ε of incoherent EMLP loop p The normalized anti-interference quality factor q is the coordinate axis, and the angle between adjacent coordinate axes is 60°.

[0048] The GNSS multi-domain evaluation three-dimensional coordinate system is as follows: with point O as the origin, and the time-domain index s of the signal as the coordinate system. T Frequency domain index s n Modulation domain index s M Related domain indicators s r Consistency domain index s c and signal parameter index s α Let be the coordinate axes, where s T s n s M s r The coordinate axes are in the same plane, and the angle between adjacent coordinate axes is 90°. c s α The coordinate axis is perpendicular to s T s n s M s r The plane formed by the coordinate axes, with an included angle of 180°.

[0049] Step 2: For the acquired satellite navigation signals, calculate the normalized results of each index under the six sub-evaluation models: Time-domain index s T Frequency domain index s n Modulation domain index s M Related domain indicators s r Consistency domain index s c and signal parameter index s α The specific process is as follows:

[0050] (1) Temporal Sub-evaluation Model

[0051] The time-domain sub-evaluation model is established in a Cartesian coordinate system and includes the signal-to-noise magnitude ε. N Timing error sensitivity η, level noise tolerance ν N Four indicators: zero-crossing distortion τ, etc. For a satellite navigation signal in a specific system at time T, the signal noise magnitude is |OA|. T The timing error sensitivity is |OB| T The noise level tolerance is |OC|. T The zero-crossing distortion value is |OD| T Therefore, the area S of the quadrilateral can be used. T This is used to comprehensively represent the quality of the satellite navigation signal in the time domain.

[0052]

[0053] S T Normalization is performed. This allows its value to be between 0 and 1. T S T Both can be used to evaluate the quality of satellite signals in the time domain, but their value ranges differ. However, when s T Or S T The closer the value is to 0, the better the signal quality is in the time domain.

[0054] Table 2 Time Domain Evaluation Indicators

[0055]

[0056] Where ΔU is the width of the eye diagram trace, U 总 The level difference between the highest value of the upper trace and the lowest value of the lower trace in the eye diagram; 2U = U 总 T S Symbol period; U n This indicates the noise margin of the corresponding level; ΔT is the duration the crossover point occupies.

[0057] (2) Frequency domain sub-evaluation model

[0058] Analyzing the frequency domain characteristics of the signal, the more flexible and practical Welch average periodogram method is selected to segment the N-point signal sequence x(n). Then, the power spectrum of the overall signal is estimated by averaging the results for each segment. It is assumed that the noise power and signal power are unbiased estimates σ. 2 and u 2 All are accurate, T coh Let be the coherent accumulation time. Through calculation and derivation, the limiting error δ and the estimated signal-to-noise ratio (SNR) are:

[0059]

[0060] The signal-to-noise ratio (SNR) of satellite navigation signals is typically between -70 and -130 dB. Here, the SNR will undergo further numerical processing. Here s n The range of variation is between 0 and 1. The closer it is to 0, the better the signal-to-noise ratio.

[0061] (3) Modulation domain sub-evaluation model

[0062] For a specific satellite navigation system, the I / Q branch amplitude ratio α is considered comprehensively. B Signal amplitude error a e Signal phase error p e Error vector magnitude ε EVM Four metrics are used to establish a modulation domain sub-evaluation model. In this example, the four evaluation magnitudes correspond to |OA| in the coordinate system. M |OB| M |OC| M |OD| M Then the area of ​​quadrilateral ABCD reflects the evaluation result S. M The corresponding evaluation indicators are shown in Table 3, and the comprehensive evaluation results are calculated as shown in Formula (3).

[0063]

[0064] Table 3. Modulation Domain Evaluation Indicators

[0065]

[0066]

[0067] in and These represent the absolute amplitude averages of the I and Q branches, respectively. When the signal is undistorted (i.e., in the I / Q branch), the amplitude ratio of the I / Q branch is A. B The value is 1.

[0068] (4) Related domain sub-evaluation model

[0069] The relevant domain evaluation model is based on the relevant loss C. L S-curve deviation S C Based on the normalized second moment Z and the three correlation domain evaluation indices, the magnitudes of each evaluation index in this example are |OA|. r |OB| r |OC| r The final evaluation result is expressed as S. r The calculation formula is shown in equation (4), and the relevant indicators are calculated as shown in Table 4.

[0070]

[0071] Table 4. Related Indicators for Relevant Domains

[0072]

[0073] Where CCF(τ) is the autocorrelation function, and τ is the time delay of the local signal relative to the received signal, in chips. The correlation loss C is described by the ratio of the peak correlation of the actual received signal to the peak correlation of the ideal signal under the same bandwidth. L S c The difference between the maximum and minimum locking point deviations is divided by the maximum locking point deviation; the correlation function p τ =f(τ), where p takes the maximum value when the ideal signal τ is 0.

[0074] (5) Consistent Domain Sub-Evaluation Model

[0075] The coherence domain assessment of a signal primarily evaluates its coherence. This is achieved by assessing the relative pseudorange increment ε between the ranging code and the carrier of the same signal. x The relative pseudorange increment ε between different ranging codes at the same frequency ρ The relative pseudorange increment between the same ranging codes at different frequencies A consistent domain sub-evaluation model is built based on three evaluation metrics. In this example, the values ​​of the three metrics are |OA|. c |OB| c |OC| c The evaluation results are shown in Formula (5), and the relevant evaluation indicators are calculated as shown in Table 5.

[0076]

[0077] Table 5. Consistency Region Related Indicators

[0078]

[0079] Note: The code pseudorange increment and carrier pseudorange increment of the signal are Δρ and Δρ, respectively. T and Δσ T , ρ T and σT Let Δρ represent the code pseudorange and carrier pseudorange at time T, respectively; Δρ = ρ I -ρ Q ,ρ I and ρ Q These are respectively represented as the code pseudorange measurements of the I-branch and Q-branch at the same frequency point; and These are the pseudoranges of the M-frequency and N-frequency signals without ionospheric influence, respectively.

[0080] (6) Signal parameter sub-evaluation model

[0081] The signal parameter sub-evaluation model theoretically analyzes the performance of the novel GNSS navigation signal from three aspects: coherent EML and incoherent EML code tracking accuracy, anti-interference performance, and anti-multipath performance. In this example, the normalized code tracking accuracy σ of the coherent EML loop is represented by |OA|. a This indicates that the normalized tracking spectral sensitivity η of the coherent EML loop has a magnitude of |OB| on the axis. a The normalized multipath error ε is |OC| on the axis. a ; Code tracking accuracy normalization σ of noncoherent EMLP loop p The size on the axis is |OE| a Normalized multipath error ε of incoherent EMLP loop p The size on the axis is |OF| α The normalized anti-interference quality factor on the q-axis is |OD|. α The maximum value of all six axes is 1, and the angle between any two adjacent axes is 60°. The final evaluation result is s. α The specific calculations for each evaluation indicator are shown in Table (6).

[0082]

[0083] Table 6. Relevant Indicators for Signaling Assessment

[0084]

[0085]

[0086] Where, β r For receiver front-end bandwidth, Let H(f) be the normalized power spectral density of the locally reproduced signal s0(t), H(f) be the equivalent baseband transfer function of the channel effect, and P be the normalized power spectral density of the locally reproduced signal s0(t). s Let d be the power of the useful signal s(t), d be the correlator interval, and T be the value of T. c Let be the symbol width of the spreading code. For an ideal signal, when the correlator interval d→0 and the pre-detection integration time T... pAs we approach infinity, the code tracking accuracy of both coherent EML loops and incoherent EML loops has the same limit. G J (f) represents the normalized interference power spectral density and the code tracking spectral sensitivity coefficient η. J,s The limit of the code tracking spectral sensitivity coefficient can be obtained when the correlator interval d→0. n For signal amplitude, For the signal phase, τ n Due to propagation delay, the multipath error of local code tracking is The phase error of carrier tracking is The correlator interval is d. In satellite navigation, the signal-to-noise ratio of the received signal is typically between 0 and 3, which can be normalized to ε. N0 is the one-sided power spectral density of the interference, β r For the receiver front-end bandwidth, T p This refers to the pre-inspection integration time.

[0087] Step 3: Based on the normalized index values ​​obtained in Step 2 under the six sub-evaluation models, calculate the volume V of the octagonal pyramid with the six normalized index values ​​as vertices in the GNSS multi-domain evaluation stereo coordinate system. k and with the volume V of the octagonal pyramid k As a real-time quality assessment result of satellite navigation signals, the maximum value can be up to 4 / 3. The smaller the volume of the octagonal pyramid, the better the signal assessment.

[0088] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the present invention.

Claims

1. A multi-domain evaluation method for GNSS signal quality, characterized in that: Includes the following steps: Step 1: Establish a multi-domain evaluation three-dimensional coordinate system for GNSS signals and six sub-evaluation model plane coordinate systems. The sub-evaluation model plane coordinate systems include: a four-dimensional plane evaluation coordinate system in the time domain, a one-dimensional linear evaluation coordinate system in the frequency domain, a four-dimensional plane evaluation coordinate system in the modulation domain, a three-dimensional plane evaluation coordinate system in the correlation domain, a three-dimensional plane evaluation coordinate system in the consistency domain, and a six-dimensional plane evaluation coordinate system for signal parameters. The time-domain four-dimensional planar evaluation coordinate system is: with a certain point as the origin, and within the same plane, respectively using the signal and noise magnitude... Timing error sensitivity Level noise margin Zero-crossing distortion The coordinate axes are defined by the coordinate axes, and the angle between adjacent coordinate axes is 90°. The frequency domain one-dimensional linear evaluation coordinate system is: with a certain point as the origin and the signal-to-noise ratio (SNR) estimate as the coordinate axis; The modulation domain four-dimensional plane evaluation coordinate system is: with a certain point as the origin, and within the same plane, respectively using the I / Q branch amplitude ratio... Signal amplitude error Signal phase error Error vector amplitude The coordinate axes are defined by the coordinate axes, and the angle between adjacent coordinate axes is 90°. The relevant domain three-dimensional planar evaluation coordinate system is: with a certain point as the origin, and within the same plane, respectively, the relevant loss is... S-curve deviation Normalized second moment The coordinate axes are defined by the coordinate axes, and the angle between adjacent coordinate axes is 120°. The consistent domain three-dimensional plane evaluation coordinate system is: with a certain point as the origin, and within the same plane, the relative pseudorange increment between the same signal ranging code and the carrier is defined. The relative pseudorange increment between different ranging codes at the same frequency point The relative pseudorange increment between the same ranging codes at different frequencies The coordinate axes are defined by the coordinate axes, and the angle between adjacent coordinate axes is 120°. The six-dimensional signal parameter plane evaluation coordinate system is as follows: with a certain point as the origin, the coordinates in the same plane are based on the normalized code tracking accuracy of the coherent EML loop. Normalized tracking spectrum sensitivity of coherent EML loop Normalized multipath error of coherent EML loops Normalized code tracking accuracy of noncoherent EMLP loop Normalized multipath error of incoherent EMLP loop The normalized anti-interference quality factor q is the coordinate axis, and the angle between adjacent coordinate axes is 60°. The GNSS signal multi-domain evaluation three-dimensional coordinate system is: with a certain point as the origin, and the time-domain index of the signal as the coordinate system. Frequency domain indicators Modulation domain index Related domain indicators Consistency Domain Indicators and signal parameter indicators are the coordinate axes, where , , , The coordinate axes are in the same plane, and the angle between adjacent coordinate axes is 90°. , The coordinate axes are perpendicular to , , , The plane formed by the coordinate axes, with an included angle of 180°; Step 2: For the acquired satellite navigation signals, calculate the normalized results of each index under the six sub-evaluation models: Time Domain Indicators Frequency domain indicators Modulation domain index Related domain indicators Consistency Domain Indicators and signal parameter indicators ; Step 3: Based on the normalized index values ​​obtained in Step 2 under the six sub-evaluation models, calculate the volume of the octagonal pyramid with the six normalized index values ​​as vertices in the GNSS signal multi-domain evaluation three-dimensional coordinate system. and in the form of an octagonal pyramid volume As a result of real-time quality assessment of satellite navigation signals.

2. The GNSS signal quality multi-domain evaluation method according to claim 1, characterized in that: The time-domain sub-evaluation model is: time-domain index , .

3. The GNSS signal quality multi-domain evaluation method according to claim 1, characterized in that: The frequency domain sub-evaluation model is: frequency domain index SNR is the signal-to-noise ratio estimate.

4. The GNSS signal quality multi-domain evaluation method according to claim 1, characterized in that: The modulation domain sub-evaluation model is: modulation domain index .

5. The GNSS signal quality multi-domain evaluation method according to claim 1, characterized in that: The relevant domain sub-evaluation model is: relevant domain index .

6. The GNSS signal quality multi-domain evaluation method according to claim 1, characterized in that: The consistency domain sub-evaluation model is: consistency domain index .

7. The GNSS signal quality multi-domain evaluation method according to claim 1, characterized in that: The signal parameter sub-evaluation model is: signal parameter index .

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