Method and device for signal quality check using signal quality monitoring

Abstract

The present disclosure provides a method for inspecting signal quality using an integrity check technique, comprising the steps of: acquiring at least one observation signal from a satellite; acquiring a code pseudorange and a carrier phase from at least one observation signal; deriving a divergence phenomenon value of the at least one observation signal based on the acquired code pseudorange and the carrier phase; and determining the quality of the observation signal by comparing the divergence phenomenon value with a divergence threshold value for each satellite elevation angle.

Description

Technology Field

[0001] The present disclosure relates to a method and apparatus for inspecting signal quality based on Signal Quality Monitoring (SQM), which is one of the integrity check methods. Background Technology

[0002] With the continued development of application fields utilizing location and information provided by Global Navigation Satellite Systems (GNSS), the industrial and social influence of GNSS is increasing. In particular, as the importance of securing precise positioning information is emphasized, various studies on integrity check techniques to verify the quality and reliability of information provided by GNSS are actively underway. The problem to be solved

[0003] The present disclosure relates to a method and apparatus for inspecting signal quality based on Signal Quality Monitoring (SQM), which is one of the integrity check methods. means of solving the problem

[0004] According to one aspect of the present disclosure, a method for inspecting signal quality using an integrity check technique may include, wherein each step is performed by a processor, the step of acquiring at least one observation signal from a satellite; the step of acquiring a code pseudorange and a carrier phase from at least one observation signal; the step of deriving a divergence phenomenon value of the at least one observation signal based on the acquired code pseudorange and the carrier phase; and the step of determining the quality of the observation signal by comparing the divergence phenomenon value with a divergence threshold value for each satellite elevation angle.

[0005] Here, prior to the step of determining the quality of the observation signal, the method may further include the step of obtaining broadcast orbit data from at least one observation signal; and the step of deriving a satellite elevation angle based on the obtained broadcast orbit data.

[0006] Here, after the step of acquiring the code pseudorange and carrier phase, the method may further include a step of detecting whether the at least one observed signal has cycle slipped.

[0007] Here, the cycle slip status is determined based on the code pseudorange and the carrier phase, obtained using the Melbourne-Wubena (Melbourne-W) method. It can be determined through the phase change amount of the GF (Geometry-Free) combination obtained based on the ambiguity integer or the carrier phase.

[0008] Here, the above cycle slip is determined when the difference between the Melbourne-Buvénat ambiguous integer value at the current time point and the estimated ambiguous integer value at the previous time point is greater than four standard deviations. It is determined as, and here is the Melbourne-Buivena ambiguous integer at the k-th epoch at the current time, is the estimated Melbourne-Buivena ambiguous integer at the previous time point k-1st epoch, can be the standard deviation at the previous time point k-1 epoch.

[0009] Here, the above cycle slip status is determined if the Melbourne-Bühbena ambiguous integer value shows a difference of 1 or more at consecutive time points k and k-1, It is determined as, and here is the Melbourne-Buivena ambiguous integer at the k-th epoch at the current time, can be a Melbourne-Buvena ambiguous integer at the k-th epoch of the previous time point.

[0010] Here, the cycle slip status is determined when the phase change amount measured in the GF combination is greater than or equal to a set cycle slip threshold, It is determined as, and here is the absolute value of the phase change amount in the GF combination, and can be a cycle slip threshold for GF phase change.

[0011] Here, the cycle slip threshold can be set based on the ROTI (Rate of Total Electron Content Index) value.

[0012] Here, the divergence threshold is obtained through a divergence threshold model and includes an upper limit and a lower limit of the divergence threshold of the divergence threshold model, and the upper limit and the lower limit of the divergence threshold can be determined based on the average value of the divergence phenomenon at a predetermined satellite elevation angle interval and the standard deviation value of the divergence phenomenon at a predetermined satellite elevation angle interval.

[0013] Here, the divergence threshold model is the upper limit of the divergence threshold. and as the lower limit of the above divergence threshold Equipped with , ;, and here is the average value of the divergence phenomenon at 10-degree intervals of satellite elevation angle, and is the standard deviation value of the divergence phenomenon at 10-degree intervals of satellite elevation angle, and is a false detection prevention coefficient and can be a real number.

[0014] According to another aspect of the present disclosure, an apparatus for inspecting signal quality comprises at least one processor, wherein the processor obtains a code pseudorange and a carrier phase from at least one observed signal, derives a divergence phenomenon value of the at least one observed signal based on the obtained code pseudorange and the carrier phase, and determines the quality of the observed signal by comparing the divergence phenomenon value with a divergence threshold value for each satellite elevation angle. Effects of the invention

[0015] A signal quality inspection method based on signal quality monitoring according to one embodiment can secure a data preprocessing function for precise positioning by inspecting the signal quality of a satellite navigation system, determining and removing fault data, and regenerating more reliable observation data.

[0016] In addition, the signal quality inspection method based on signal quality monitoring according to one embodiment allows for more accurate signal analysis by considering cycle slip in greater detail. Brief explanation of the drawing

[0017] FIG. 1a is a block diagram schematically illustrating a signal quality inspection system according to one embodiment. FIG. 1b is a block diagram schematically illustrating a signal quality inspection device within the reference station of FIG. 1a. FIG. 2 is a flowchart illustrating a signal quality inspection method according to one embodiment. Figure 3 is a flowchart illustrating the method for deriving the divergence threshold of Figure 2. Figure 4 is a flowchart illustrating a method for detecting cycle slip of Figure 2. Figure 5 is a flowchart illustrating a method for obtaining the cycle slip threshold model of Figure 4. Figure 6 is a graph showing the test results of the signal quality inspection method according to the embodiment. Specific details for implementing the invention

[0018] The terms used in these embodiments have been selected to be as widely used and general as possible, taking into account the functions within these embodiments; however, these terms may vary depending on the intent of those skilled in the art, case law, the emergence of new technologies, etc. Additionally, in specific cases, the applicant has arbitrarily selected terms, and in such cases, their meanings will be described in detail in the relevant sections. Therefore, the terms used in these embodiments should be defined not merely by their names, but based on their meanings and the content throughout these embodiments.

[0019] Unless otherwise defined, the terms used in these embodiments have the same meaning as generally understood by those skilled in the art to which these embodiments pertain. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in these embodiments.

[0020] The embodiments are subject to various modifications and may take various forms; therefore, some embodiments are illustrated in the drawings and described in detail. However, this is not intended to limit the embodiments to the specific disclosed forms, and it should be understood that all modifications and substitutions fall within the spirit and scope of the embodiments. The terms used herein are for the description of the embodiments only and are not intended to limit the embodiments.

[0021] The following detailed description of the invention refers to the accompanying drawings, which illustrate specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention. It should be understood that various embodiments of the invention are different but need not be mutually exclusive. For example, specific shapes, structures, and characteristics described herein may be modified from one embodiment to another without departing from the spirit and scope of the invention. It should also be understood that the location or arrangement of individual components within each embodiment may be modified without departing from the spirit and scope of the invention. Accordingly, the following detailed description is not meant to be limiting, and the scope of the invention should be understood to encompass the scope claimed by the claims and all equivalents thereof. Similar reference numerals in the drawings indicate identical or similar components across various aspects.

[0022] Additionally, terms including ordinal numbers, such as first, second, etc., may be used to describe various components, but said components are not limited by said terms. These terms are used solely for the purpose of distinguishing one component from another.

[0023] When it is stated that one component is "connected" or "connected" to another component, it should be understood that while it may be directly connected or connected to that other component, there may also be other components in between. On the other hand, when it is stated that one component is "directly connected" or "directly connected" to another component, it should be understood that there are no other components in between.

[0024] Hereinafter, in order to enable a person skilled in the art to easily practice the present invention, various embodiments of the present invention will be described in detail with reference to the attached drawings.

[0025] FIG. 1a is a block diagram schematically illustrating a signal quality inspection system according to one embodiment. FIG. 1b is a block diagram schematically illustrating a signal quality inspection device within a reference station of FIG. 1a.

[0026] Referring to FIG. 1a, the signal quality inspection system may include a reference station (1000) including a signal quality inspection device and a satellite (G).

[0027] The satellite (G) transmits a signal to the reference station (1000). The satellite (G) moves in Earth's orbit at regular intervals and transmits a signal containing data such as position, time, and orbit information. The satellite (G) can transmit the signal using multiple medium waves.

[0028] A reference station (1000) is equipped with at least a GNSS (Global Navigation Satellite System) antenna, a communication unit for connection to the Internet, and a signal quality inspection device (100 in FIG. 1b). The signal quality inspection device (100) receives at least one satellite signal from a satellite using the GNSS antenna to acquire at least one observation signal and determines the quality of at least one acquired observation signal. Each step may be performed by at least one processor. Here, the observation signal refers to data received by the reference station from a signal transmitted from an artificial satellite, and the observation signal may include at least a code pseudorange, carrier phase, propagation time, etc.

[0029] Satellite signals can be affected in terms of signal accuracy and reliability due to divergence. Divergence can mean that the discrepancy between the code pseudorange and the carrier phase gradually increases over time. Since the code pseudorange and the carrier signal are based on the same satellite signal, the difference between the two signals must be constant. However, the value may fluctuate due to external error factors such as atmospheric effects including the ionosphere, multiple warnings, and receiver noise, and divergence may occur. In cases where divergence is severe, there is a problem in that the accuracy of distance measurement of the GNSS signal decreases. Therefore, a signal quality inspection device (100) according to one embodiment can enable precise position calculation by identifying abnormal signals caused by divergence.

[0030] The signal quality inspection device (100) can determine the quality of the observed signal based on Signal Quality Monitoring (SQM), which is one of the integrity check techniques. The signal quality inspection device (100) can determine the quality of the observed signal based on the code carrier divergence test, which is a tool for determining whether there is a divergence phenomenon during Signal Quality Monitoring (SQM).

[0031] The signal quality inspection device (100) may be implemented as an integral part of the reference station, but may also be implemented as a separate device from the reference station. Furthermore, without being limited thereto, the signal quality inspection device (100) may be implemented by being embedded in a user device in the form of a processor, implemented on a recording medium in the form of an application or program, or implemented in the form of a server. The implementation form of the signal quality inspection device (100) is not limited to those mentioned and can be replaced in various ways.

[0032] Referring to FIG. 1b, the signal quality inspection device (100) may include an observation signal acquisition unit (110) that receives at least one satellite signal from a satellite and acquires at least one observation signal, a code pseudorange and carrier phase acquisition unit (120) that acquires a code pseudorange and a carrier phase from at least one observation signal, a divergence phenomenon value derivation unit (130) that derives a divergence phenomenon value of the at least one observation signal based on the acquired code pseudorange and carrier phase, and a signal quality judgment unit (140) that determines the quality of the observation signal by comparing the divergence phenomenon value with a divergence threshold value for each satellite elevation angle and outputs the observation signal of which the quality has been determined.

[0033] The signal quality inspection device (100) includes at least one processor (150), and the processor (150) controls the overall operation of the signal quality inspection device (100). The processor (150) may be implemented using at least one of ASICs (application specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs (field programmable gate arrays), controllers, microcontrollers, microprocessors, and other electrical units for performing functions.

[0034] Meanwhile, although only components related to the embodiment are shown in FIG. 1b, the signal quality inspection device (100) may include other general-purpose components in addition to the shown components. For example, the signal quality inspection device (100) may further include a communication unit, a DB, etc.

[0035] FIG. 2 is a flowchart illustrating a signal quality inspection method according to one embodiment. FIG. 3 is a flowchart illustrating a method for deriving the divergence threshold of FIG. 2.

[0036] Referring to FIG. 2, in step 210, the signal quality inspection device (100) (hereinafter referred to as the device) obtains at least one observation signal by receiving at least one satellite signal from the satellite.

[0037] In step 220, the device acquires a target signal by combining at least one observation signal and obtains a code pseudorange and carrier phase from the acquired target signal. At least one observation signal may include signals of various frequencies, such as L1, L2, L5, etc. The device may combine two observation signals (e.g., L1 observation signal and L2 observation signal) to acquire a target signal which is an ionosphere-free (IF) signal. Here, the L1 observation signal refers to a frequency signal of approximately 1575.42 MHz (GPS reference), and the L2 observation signal refers to a frequency signal of approximately 1227.60 MHz (GPS reference).

[0038] The device uses the code pseudorange and frequency of the observed signal to determine the code pseudorange of the target signal as in Equation 1 ( You can obtain ). Here, is the frequency of the L1 observed signal, and is the frequency of the L2 observed signal, and is the code pseudorange of the L1 observation signal, and is the code pseudorange of the L2 observation signal.

[0039]

[0040] The device uses the carrier phase and frequency of the observed signal to determine the carrier phase of the target signal as shown in Equation 2 ( You can obtain ). Here, is the frequency of the L1 observed signal, and is the frequency of the L2 observed signal, and is the carrier phase of the L1 observation signal, and is the carrier phase of the L2 observed signal.

[0041]

[0042] In step 230a, the device detects whether the target signal has cycle slip. If cycle slip is detected in the target signal, the device ignores the divergence value of the target signal and tests the next observation to derive the divergence value of the next target signal.

[0043] Divergence is significantly affected by cycle slip. Cycle slip refers to signal discontinuity in GNSS caused by the temporary interruption or distortion of the carrier phase. For example, cycle slip can occur when the signal between the satellite and the receiver is blocked by buildings, or when the signal is weakened by bad weather, sudden changes in the ionosphere, or multipath. As the continuity of the carrier phase is broken by cycle slip, problems may arise where distance calculations become inaccurate.

[0044] Meanwhile, the ionospheric effect refers to the phenomena of ionospheric delay and ionospheric refraction that occur when GNSS signals pass through the ionosphere—an atmospheric layer densely packed with particles ionized by solar radiation 50 to 1,000 km above the Earth—where the speed and path of the signal are affected. The ionospheric effect can slow down the signal speed, causing errors in received time information, and the refraction of the signal as it passes through the ionosphere can result in a difference between the signal's actual path and the calculated path. The ionospheric effect can be a cause of cycle slip.

[0045] Therefore, by the device detecting cycle slip and ignoring the target signal where the cycle slip was detected, errors can be eliminated where a non-divergence phenomenon appears as a divergence phenomenon due to cycle slip.

[0046] The device can detect cycle slip using a technique that combines the TurboEdit Method (Blewitt, 1990) and Geometry-Free (GF) (Luo et al. 2022). In particular, when the device detects cycle slip using the GF combination, in order to detect cycle slip more precisely and accurately by minimizing the reflection of ionospheric influence, the device can generate a cycle slip judgment threshold model based on the rate of change of total electron count index (ROTI). Specific details regarding how the device detects cycle slip will be described later with reference to FIG. 4.

[0047] In step 240a, the device derives the divergence value of the target signal. Based on the code-carrier divergence test, the device can monitor divergence and ionospheric effects by calculating the rate of change of code and carrier data for the target signal over a continuous observation period.

[0048] The device can derive the divergence phenomenon value as shown in Equation 3 based on the code pseudorange and carrier phase of the target signal. Here, k represents the k-th epoch, k-1 represents the k-1th epoch, and is the divergence phenomenon value of the target signal, R is the code pseudorange of the target signal, and represents the carrier phase of the target signal. Meanwhile, is a time constant that serves to set weights between the previous and current observations, and is the sampling period, which is the time interval between consecutive observation times. These are variables that adjust the sensitivity of divergence detection by considering the temporal continuity and rate of change of the target signal. The divergence value is a value that quantitatively represents the degree of divergence based on the difference between the code pseudorange and the carrier phase. The divergence value is a real number and can be expressed in units of length or phase difference; the closer it is to 0, the less difference there is between the code pseudorange and the carrier phase.

[0049]

[0050] Meanwhile, in step 220b, the device obtains broadcast ephemeris from at least one observation signal. Broadcast ephemeris is data transmitted by a GNSS satellite included in a signal, providing immediate position, velocity, and time information of the satellite.

[0051] Additionally, in step 230b, the device derives the satellite elevation angle through the acquired broadcast orbital eq. The satellite elevation angle refers to the angle between the direction from the observation point to the satellite and the horizontal plane (horizon). The device can obtain the satellite elevation angle by calculating the receiver position, calculating the satellite position, and then deriving the satellite elevation angle.

[0052] Specifically, to calculate the satellite elevation angle relative to the reference station, the device uses the reference station's Earth-Centered Earth-Fixed (ECEF) position coordinates , latitude of the reference country ( ), longitude of the reference country ( ) and satellite's ECEF coordinate system position coordinates ( Acquires ).

[0053] Specifically, the device can obtain the reference station ECEF position coordinates from the observation signal through the triangulation technique. The device [can] obtain the reference station's latitude ( ), longitude of the reference country ( ) can be obtained from the reference station ECEF position coordinates. In addition, the device obtains the satellite's ECEF coordinate system position coordinates (pre-estimated prior to satellite elevation angle calculation) The geographical coordinates of the satellite can be obtained by Equation 4. Here, N represents the radius of curvature in the prime vertical, a represents the semi-major axis of the Earth ellipsoid, and b represents the semi-minor axis of the Earth ellipsoid. Also, is the latitude of the reference station on the Earth's ellipsoid, ε₀ represents the longitude of the reference station on the Earth ellipsoid, and h represents the ellipsoidal elevation, which is the altitude indicating how far the reference station is from the surface of the Earth ellipsoid. According to Equation 4, the device [describes] the position of the reference station in the ECEF coordinate system position coordinates. It can be converted from to the geographical coordinates (latitude, longitude, altitude) of the reference country.

[0054]

[0055] Next, the device can calculate the position of the satellite according to the selected satellite constellation using the provided broadcast ephemeris, and then calculate the latitude and longitude of the satellite.

[0056] In detail, the device is the ECEF coordinate system position coordinate of the reference station according to Equation 5. Hardness from ( Calculate.

[0057]

[0058] And the device is the ECEF coordinate system position coordinate of the reference station according to Equation 6. Calculate p, the horizontal distance corresponding to the equatorial plane, from it.

[0059]

[0060] In addition, the device sets the initial value of the ellipsoid height h to 0 according to Equation 7, and then the horizontal distance and the ECEF coordinate system position coordinates of the reference station Latitude approximation based on Calculate . Here, e represents eccentricity.

[0061]

[0062] The device also has an approximation of latitude Based on the radius of the major axis (a) and the radius of the minor axis (b) of the Earth ellipsoid, the approximate radius of curvature N0 of the ellipsoidal line is calculated by Equation 8.

[0063]

[0064] In addition, the device updates the ellipsoid height h by Equation 9 based on the approximate radius of curvature N0 and horizontal distance (p).

[0065]

[0066] And the device has the approximate radius of curvature of the yaw line N0, the elliptical height value h, the horizontal distance (p), and the ECEF coordinate system position coordinates of the reference station Based on, the latitude of the reference station (by mathematical formula 10) Calculate.

[0067]

[0068] Meanwhile, the device is the latitude of the calculated reference station and the approximate latitude of the reference country, the latitude of the reference country If the difference is within the desired margin of error, the iterative calculation is stopped, and the latitude and longitude of the reference station are determined. However, the calculated latitude of the reference station and the latitude of the reference country for the approximate latitude If the difference is not within the desired margin of error, the device, from the step of calculating the approximate radius of curvature N0 of the yaw line, the latitude of the reference station By repeating the step of calculating, the accurate latitude of the reference station can be obtained.

[0069] Next, the device acquires the satellite elevation angle based on the latitude and longitude of the acquired reference station.

[0070] In detail, the device is a position vector between the satellite and the reference station ( Calculate ) as in Equation 11. Here ( ) is the satellite's ECEF coordinate system position coordinate, and ) is the ECEF coordinate system position coordinate of the reference station obtained earlier.

[0071]

[0072] Then, the device converts the position vector into a terrain coordinate system as in Equation 12, and then obtains the satellite elevation angle (el) based on the acquired terrain coordinate system using Equation 13.

[0073]

[0074]

[0075] Next, in step 250, the device determines the quality of the target signal by comparing the derived divergence phenomenon value with the divergence threshold value for each satellite elevation angle. The determination of signal quality may involve the device detecting abnormal data by comparing the target signal with the divergence threshold value. Here, the divergence threshold value may be derived for each predetermined elevation angle of a predetermined divergence interval. Here, the predetermined elevation angle may be 10 degrees, but this is an example, and the elevation angle may vary according to the user's designation, such as 5 degrees, 15 degrees, etc.

[0076] The divergence threshold is determined based on the average value of the divergence phenomenon and the standard deviation value of the divergence phenomenon. The divergence threshold may include an upper limit and a lower limit. Specifically, the upper limit and the lower limit of the divergence threshold may be determined based on the average value of the divergence phenomenon at 10-degree intervals of satellite elevation angle and the standard deviation value of the divergence phenomenon at 10-degree intervals of satellite elevation angle.

[0077] For example, the divergence threshold model is the divergence threshold upper limit Equipped with, as a lower limit of the divergence threshold , is equipped with. Here is the average value of the divergence phenomenon at 10-degree intervals of satellite elevation angle, and is the standard deviation value of the divergence phenomenon at 10-degree intervals of satellite elevation angle, and is a false detection prevention factor and is a real number. The false detection prevention factor can be changed according to the user's selection, and the precision of signal quality judgment can be adjusted according to the false detection prevention factor.

[0078] The method by which the device implements the divergence threshold model is explained with reference to Fig. 3.

[0079] Referring to FIG. 3, the divergence threshold can be obtained through a divergence threshold model for elevation angle ranges using observation data from a specific period. Here, the observation data from a specific period is referred to as the learning signal. The device can implement the divergence threshold model through the method of FIG. 3.

[0080] In step 310, the device obtains at least a plurality of learning signals by receiving a plurality of satellite signals from a satellite.

[0081] In step 320, the device obtains a learning signal by combining a plurality of learning signals, and obtains a code pseudorange and a carrier phase from the combined learning signal. Since the process of obtaining the code pseudorange and a carrier phase from the combined learning signal is the same as in step 220, a redundant description is omitted.

[0082] In step 330a, the device detects whether the combined learning signal has cycle slip. The device can detect cycle slip using a technique that combines the TurboEdit Method and Geometry-Free (GF). Since the process of detecting cycle slip is the same as in step 230a, except that the learning signal is used instead of the detection signal, a redundant description is omitted.

[0083] In step 340a, the device derives the divergence value of the combined learning signal. The device can monitor divergence and ionospheric effects by calculating the rate of change of code and carrier data for the target signal over a continuous observation time based on a code-carrier divergence test, and since the process of deriving the divergence value of the combined learning signal is the same as in step 240a, a redundant explanation is omitted.

[0084] Meanwhile, in step 320b, the device obtains broadcast ephemeris from a plurality of learning signals, and in step 330b, the device derives the satellite elevation angle through the obtained broadcast ephemeris. Since the process by which the device derives the satellite elevation angle is identical to steps 220b and 230b, a redundant explanation is omitted.

[0085] In step 350, the device derives a divergence threshold for each satellite elevation angle of the combined learning signal. The device derives the divergence threshold based on the average value of the divergence phenomenon and the standard deviation value of the divergence phenomenon by the divergence model. Here, since the average value of the divergence phenomenon represents the average of the divergence values ​​for each satellite elevation angle, it can be obtained based on the divergence values ​​of the combined learning signals derived within a given elevation angle range. Here, the standard deviation value of the divergence phenomenon indicates how irregularly the divergence values ​​of the data are distributed by elevation angle; it can be derived by calculating the deviation of each data point relative to the average value of the divergence phenomenon and taking the average of the squared deviations. Here, data may refer to the values ​​of the learning signal. The divergence threshold derived by the divergence model may include an upper limit and a lower limit of the divergence threshold.

[0086] Specifically, as shown in Equation 14, the upper limit of the divergence threshold and the lower limit of the divergence threshold are the average values ​​of the divergence phenomenon at a predetermined satellite elevation angle interval ( ) and the standard deviation value of the divergence phenomenon of a predetermined satellite elevation angle interval ( It can be determined based on [this]. Here, the predetermined satellite elevation angle interval may be 10 degrees, but is not limited thereto. Meanwhile, here is a false detection prevention factor, is a real number, and can be selected according to user specifications. The precision of signal quality judgment can be adjusted according to the false detection prevention factor.

[0087]

[0088] Referring again to FIG. 2, in step 250, the device determines the quality of the target signal by comparing the divergence threshold value with the divergence phenomenon value of the target signal. The device determines whether the absolute value of the divergence phenomenon value is greater than the divergence threshold value. That is, if the divergence phenomenon value is within the range of the upper and lower limits of the divergence threshold value, the device determines the observed signal to be of high quality (S250a). However, if the divergence phenomenon value is not within the range of the upper and lower limits of the divergence threshold value, the device determines the observed signal to be of low quality (S250b). By marking or removing the observed signal determined to be of low quality as an error (S251b), the device improves the GNSS signal quality and ultimately enhances the accuracy and reliability of the position calculation. In this way, by marking or removing the error of the low-quality signal, data that is likely to cause errors in the signal set used for position calculation can be excluded, thereby preventing errors in the final position calculation result.

[0089] Figure 4 is a flowchart illustrating a method for detecting cycle slip of Figure 2.

[0090] Referring to FIG. 4, in step 220a-1, the device for at least one observed signal is Melbourne-Weuvena (Melbourne-W Obtain ambiguous integers and GF (Geometry-Free) combinations.

[0091] The device can determine whether cycle slip occurs through at least one of the Melbourne-Buivena homos constant obtained based on the code pseudorange and carrier phase, and the phase change amount of the GF combination obtained based on the carrier phase. To this end, the device can first obtain the Melbourne-Buivena homos constant and the GF combination.

[0092] In detail, the device is a Melbourne-Buvena ambiguous integer ( can be obtained from the carrier phase, frequency, and code pseudorange of each of the two observed signals. The device uses the Melbourne-Buivenar ambiguity integer (by Equation 15) You can obtain, and here, is the carrier phase of the L1 observed signal, is the carrier phase of the L2 observed signal, is the frequency of the L1 observed signal, and is the frequency of the L2 observed signal, and is the code pseudorange of the L1 observation signal, and is the code pseudorange of the L2 observation signal. Also, here ε is the Melbourne-Buivena wavelength determined by the frequency of the observed signals, and c is the speed of light constant.

[0093]

[0094] In addition, the device (estimated Melbourne-Buvena ambiguous integers) ) is the previously determined Melbourne-Buvena ambiguous integer ( It can be obtained from. The device uses the Melbourne-Buivena ambiguous integer estimated by Equation 16 ( ) can be obtained, where k represents the k-th epoch and k-1 represents the k-1st epoch.

[0095]

[0096] In addition, the device is a Melbourne-Buvena ambiguous integer ( and estimated Melbourne-Buvena ambiguous integers ( ) and standard deviation at the k-1th epoch Based on , the standard deviation at the k-th epoch The device can obtain the standard deviation at the k-th epoch according to Equation 17. You can obtain.

[0097]

[0098] Meanwhile, the device combines GF based on the carrier phase ( ) can be obtained. The device can obtain the GF combination (by mathematical formula 18) You can obtain ). Here is the wavelength of the L1 observed signal frequency, and is the wavelength of the L2 observed signal frequency, and is the carrier phase of the L1 observation signal, and is the carrier phase of the L2 observed signal.

[0099]

[0100] Meanwhile, the device is of the GF combination ( ) The phase change amount over time or the GF combination as a single difference with respect to time can be derived by mathematical equation 19. Here, is the GF combination at the k-1th epoch, and is the GF combination at the k-th epoch. In a normal signal When the value generally remains constant but cycle slip occurs It fluctuates rapidly.

[0101]

[0102] Next, in step 220a-2, the device determines whether cycle slips based on the code pseudorange and carrier phase, the Melbourne-Buivenar ambiguity integer ( and the phase change of the GF combination obtained based on the carrier phase It can be determined through at least one of them.

[0103] In the first embodiment, the device can determine whether cycle slip has occurred from the Melbourne-Buibén ambiguity integer obtained based on the code pseudorange and carrier phase.

[0104] In this case, the presence of cycle slip can be determined by Equation 20, which is when the difference between the Melbourne-Beuvena ambiguous integer value at the current time point and the estimated ambiguous integer value at the previous time point is four standard deviations or more. Here is the Melbourne-Buivena ambiguous integer at the k-th epoch at the current time, is the estimated Melbourne-Buivena ambiguous integer at the previous time point k-1st epoch, is the standard deviation at the previous time point k-1 epoch.

[0105]

[0106] That is, if the difference between the Melbourne-Buibén ambiguity integer value at the current time point and the estimated ambiguity integer value at the previous time point is greater than or equal to four standard deviations, the device determines that cycle slip has occurred in the target signal. If the difference between the Melbourne-Buibén ambiguity integer value at the current time point and the estimated ambiguity integer value at the previous time point is less than four standard deviations, the device determines that cycle slip has not occurred in the target signal.

[0107] In a second embodiment, the device can also determine whether cycle slip has occurred from the Melbourne-Buibén ambiguity integer obtained based on the code pseudorange and carrier phase.

[0108] In this case, the presence of a cycle slip can be determined by Equation 21, which is when the Melbourne-Beuve or ambiguous integer values ​​at consecutive time points k and k-1 show a difference of 1 or more. Here is the Melbourne-Buivena ambiguous integer at the k-th epoch at the current time, is a Melbourne-Buvena ambiguous integer at the k-th epoch of the previous time point.

[0109]

[0110] That is, the device determines that a cycle slip has occurred in the target signal if the Melbourne-Beuvena ambiguous integer value shows a difference of 1 or more at consecutive time points k and k-1. Additionally, the device determines that a cycle slip has not occurred in the target signal if the Melbourne-Beuvena ambiguous integer value shows a difference of less than 1 at consecutive time points k and k-1.

[0111] In a third embodiment, the device can determine whether cycle slip occurs based on a GF combination obtained based on the carrier phase.

[0112] In this case, the presence of cycle slip can be determined by Equation 22, which is when the phase change amount measured in the GF combination is greater than or equal to the set cycle slip threshold. Here is the absolute value of the phase change amount in the GF combination, and is a cycle slip threshold, which can be a threshold for GF phase change.

[0113]

[0114] In other words, the device can determine that cycle slip has occurred in the target signal if the amount of phase change in the GF combination is greater than or equal to a threshold value. A specific method for deriving the cycle slip threshold value will be explained later with reference to Fig. 5.

[0115] In step 220a-3, if cycle slip is not detected in the target signal, the device derives the divergence phenomenon value of the target signal by step 240a of FIG. 2.

[0116] In step 220a-4, if the device detects a cycle slip in the target signal, it ignores the divergence value of the target signal and tests the next observation. That is, the divergence value of the current target signal is initialized to 0, and the device determines whether the next target signal has a cycle slip. In other words, by the device detecting a cycle slip and ignoring the target signal in which the cycle slip was detected, it can exclude errors where a non-divergence phenomenon appears as a divergence phenomenon due to the cycle slip.

[0117] Figure 5 is a flowchart illustrating a method for obtaining the cycle slip threshold model of Figure 4.

[0118] Referring to Fig. 5, the device can generate a cycle slip threshold model based on the rate of change of total electron count index (ROTI).

[0119] The Rate of Change in Total Electron Content (ROTI) is an indicator representing how quickly the Total Electron Content (TEC) of the ionosphere changes over time. Total Electron Content (TEC) can be the sum of the electron densities in the ionosphere that affect the speed and path of a GNSS signal as it passes through the ionosphere. The Rate of Change in Total Electron Content (ROT) is the rate of change of the total electron content at a specific point in time.

[0120] In step 510, the device acquires at least a plurality of learning signals by receiving a plurality of satellite signals from a satellite. Step 510 may be the same as step 310.

[0121] In step 520, the device obtains a GF combination for a plurality of learning signals. Here, the learning signal may be an L1 learning signal or an L2 learning signal. The GF combination can be obtained based on the respective carrier phases for the plurality of learning signals. Since the process of obtaining the GF combination is identical to the aforementioned Equation 18, a redundant explanation is omitted.

[0122] In step 530, the device obtains a ROT value based on the acquired GF combination. The Rate of Change in Total Electron Count (ROT) is the rate of change in the total number of electrons at a specific time and is derived based on the temporal change of the GF combination value of the GNSS signal. Therefore, the Rate of Change in Total Electron Count (ROT) can be derived by calculating the ionospheric effect using the temporal change of the GF combination value and the frequency characteristics of the L1 and L2 frequency signals, as shown in Equation 23. Here is a constant that defines the relationship between the total number of electrons in the ionosphere and GNSS signals, and represents the time interval between k-1 and k epochs.

[0123]

[0124] In step 540, the device obtains the ROTI value based on the acquired ROT value. ROTI is an indicator that evaluates the severity of ionospheric fluctuations by calculating the standard deviation of the ROT value over a specific time interval N. As shown in Equation 24, ROTI is the ROT average value ( It is calculated through volatility using the sum of values ​​regarding how much it deviates from ). Here, is the ROT average value, and N represents a specific time interval.

[0125]

[0126] In step 550, the device obtains a cycle slip threshold based on the range of the acquired ROTI value. The cycle slip threshold is dynamically set based on the ROTI value. If ROTI is large, the ionosphere is in a state of severe fluctuation, and if ROTI is small, the ionosphere is in a stable state. That is, the cycle slip model sets a large threshold because cycle slip detection is difficult when the ionosphere effect is strong, and sets a small threshold because cycle slip detection is relatively easy when the ionosphere effect is small.

[0127] For example, as shown in Equation 25, the cycle slip model If the first value is set, ionospheric fluctuations are small and stable, allowing a fixed low threshold to be set. Accordingly, sensitivity can be increased in that range to strictly evaluate signal quality. Here, the first value may be 0.5, but it is not limited to this and can be changed according to the requirements of the GNSS application, the state of the ionosphere, location, and time of day; for example, 0.3, 0.8, etc., can be specified. In addition, the low threshold is This may be the case, but this is exemplary, and a lower threshold can be optionally set depending on the measurement environment.

[0128] In addition, as shown in Equation 25, the cycle slip model In this case, the threshold can be set to increase as the ROTI value increases at an intermediate level of ionospheric variation. For example, the cycle slip model can set the threshold as a quadratic function of the ROTI value. However, this is merely an example, and the cycle slip model may also set the threshold as a linear function of the ROTI value, an exponential function of the ROTI value, a logarithmic function of the ROTI value, or a combination of one or more of these. Meanwhile, the second value here may be 3, but is not limited thereto; it can be changed according to the requirements of the GNSS application, the state of the ionosphere, location, and time zone, and values ​​such as 1 or 5 can be specified. Accordingly, the threshold can be dynamically adjusted to reflect ionospheric variability in the corresponding range.

[0129] In addition, as shown in Equation 25, the cycle slip model In this case, a high threshold can be set to indicate a state of severe ionospheric fluctuation. Accordingly, the threshold can be raised in that range to prevent unnecessary false positives or false detections. The high threshold is This may be the case, but this is exemplary, and a lower threshold can be optionally set depending on the measurement environment.

[0130]

[0131] The device can utilize the cycle slip threshold obtained from the cycle slip threshold model in step 550 to determine the cycle slip of the target signal in relation to the third embodiment of step 220a-2 of FIG. 4. In this way, by detecting the cycle slip and ignoring the target signal in which the cycle slip has been detected, the device can exclude errors in which a non-divergence phenomenon appears as a divergence phenomenon due to the cycle slip. Additionally, by detecting whether the target signal is in cycle slip by considering ROTI during cycle slip detection, the sensitivity of cycle slip detection can be dynamically adjusted according to the ionospheric fluctuation state, thereby preventing errors in cycle slip detection. Accordingly, the device has the effect of maintaining the precision of position calculation in high-precision GNSS applications.

[0132] Figure 6 is a graph showing the test results of the signal quality inspection method according to the embodiment.

[0133] The test in Fig. 6 was conducted by performing a signal quality inspection on the satellite signal of Satellite No. 23 on January 1, 2004 (the first day of year, DOY001) at the reference station (DAEJ) located in Daejeon, South Korea, which includes fault data known to the user. Fig. 6 shows the results of comparing the fault data detected by the device with the actual fault data, based on data observed during a total of 337 epochs from 18:30:30 to 21:19. The x-axis of Fig. 6 represents the satellite elevation angle, and the y-axis represents the divergence phenomenon values ​​for the phase elevation angle at 10-degree intervals.

[0134] As can be seen in Fig. 6, the black dots outside the upper threshold and lower threshold regions of the divergence threshold, indicated by straight lines in the test results, are confirmed to have caused divergence. Therefore, it can be confirmed that fault data detection by the signal quality inspection method and device according to the embodiment of the present invention is accurately performed.

[0135] Table 1 shows the false detection prevention coefficient included in the divergence phenomenon threshold of Equation 14 in relation to the test of Fig. 6 ( This shows the results of changing ) to various values.

[0136] 1.5156 1.0 0.5 0.1 Number of detected failures 243 250 261 298 Accuracy 72.11% 74.18% 77.45% 88.43%

[0137] Referring to Table 1, the false detection prevention coefficient ( It can be confirmed that the accuracy and precision of actual fault detection change depending on ). False detection prevention coefficient ( ) controls the range of the threshold when combining the mean value and standard deviation of divergence phenomena. High (large) false detection prevention coefficient ( ) widens the range of the threshold and enhances the accuracy of false positive prevention. On the other hand, a low (small) false positive prevention coefficient ( ) narrows the range of the threshold and enhances the false detection prevention sensitivity. Therefore, the device has a false detection prevention coefficient ( By adjusting the size of ), the accuracy or sensitivity of preventing false detection can be controlled.

[0138] A signal quality inspection device and a signal quality inspection method according to one embodiment of the present invention can verify the accurate identification of abnormal signals caused by divergence phenomena, and by marking or removing the identified abnormal signals as errors, more reliable observation data can be regenerated, and consequently, a data preprocessing function for precise positioning can be secured. Accordingly, according to one embodiment of the present invention, precise position calculation for GNSS signals can be enabled.

[0139] In addition, the signal quality inspection device and signal quality inspection method according to one embodiment of the present invention have the advantage of enabling accurate signal analysis and facilitating the identification of abnormal signals by considering cycle slip more specifically.

[0140] The embodiments according to the present invention described above may be implemented in the form of a computer program that can be executed through various components on a computer, and such a computer program may be recorded on a computer-readable medium. In this case, the medium may include a magnetic medium such as a hard disk, a floppy disk, and a magnetic tape, an optical recording medium such as a CD-ROM and a DVD, a magneto-optical medium such as a floptical disk, and a hardware device specifically configured to store and execute program instructions, such as a ROM, RAM, or flash memory.

[0141] Meanwhile, the above-mentioned computer program may be one specifically designed and configured for the present invention, or one known and available to those skilled in the art of computer software. Examples of computer programs may include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc.

[0142] In the specification of the present invention (particularly in the claims), the use of the term "above" and similar descriptive terms may be in both singular and plural. Furthermore, where a range is described in the present invention, it is to include an invention to which individual values ​​belonging to said range are applied (unless otherwise stated), and this is equivalent to describing each individual value constituting said range in the detailed description of the invention.

[0143] Unless explicitly stated or contrary to the order of the steps constituting the method according to the present invention, said steps may be performed in a suitable order. The present invention is not necessarily limited by the order in which said steps are described. The use of all examples or exemplary terms (e.g., etc.) in the present invention is merely for the purpose of describing the present invention in detail, and the scope of the present invention is not limited by said examples or exemplary terms unless limited by the claims. Furthermore, those skilled in the art will understand that various modifications, combinations, and changes may be made according to design conditions and factors within the scope of the claims or equivalents to which they are added.

[0144] Accordingly, the scope of the present invention should not be limited to the embodiments described above, and all scopes equivalent to or equivalently modified from the claims set forth below, as well as the claims set forth below, shall be considered to fall within the scope of the concept of the present invention. Explanation of the symbols

[0145] 1000 base country G satellite 100 Signal Quality Judgment Device

Claims

Claim 1 A method for inspecting signal quality using an integrity check technique, wherein each step is performed by a processor, comprising: a step of acquiring at least one observation signal from a satellite; a step of acquiring a code pseudorange and a carrier phase from at least one observation signal; a step of determining whether a cycle slip has occurred in the at least one observation signal by comparing the phase change amount of a Geometry-Free (GF) combination obtained based on the carrier phase with a cycle slip threshold; a step of deriving a divergence phenomenon value of the at least one observation signal based on the code pseudorange and the carrier phase based on the result of the determination; and a step of determining the quality of the observation signal by comparing the divergence phenomenon value with a divergence threshold for each satellite elevation angle; wherein the cycle slip threshold is dynamically set according to a Rate of Total Electron Content Index (ROTI) value calculated based on a GF combination for a plurality of observation signals. Claim 2 The method of claim 1 further comprises, prior to the step of determining the quality of the observation signal, a step of obtaining broadcast orbit data from at least one observation signal; and a step of deriving a satellite elevation angle based on the obtained broadcast orbit data. Claim 3 delete Claim 4 delete Claim 5 delete Claim 6 delete Claim 7 A method according to claim 1, wherein the determining step comprises the step of determining that the cycle slip has occurred when the phase change amount is greater than or equal to the cycle slip threshold. Claim 8 delete Claim 9 A method according to claim 1, wherein the divergence threshold is obtained through a divergence threshold model, and includes an upper limit and a lower limit of the divergence threshold of the divergence threshold model, wherein the upper limit and the lower limit of the divergence threshold are determined based on the average value of the divergence phenomenon of a predetermined satellite elevation angle interval and the standard deviation value of the divergence phenomenon of a predetermined satellite elevation angle interval. Claim 10 In paragraph 9, the above divergence threshold model is the above divergence threshold upper limit and as the lower limit of the above divergence threshold Equipped with , ;, and here is the average value of the divergence phenomenon at 10-degree intervals of satellite elevation angle, and is the standard deviation value of the divergence phenomenon at 10-degree intervals of satellite elevation angle, and is a false detection prevention coefficient and is a real number, method. Claim 11 A device for inspecting signal quality, comprising at least one processor; wherein the processor obtains a code pseudorange and a carrier phase from at least one observation signal, determines whether a cycle slip has occurred in the at least one observation signal by comparing the phase change amount of a Geometry-Free (GF) combination obtained based on the carrier phase with a cycle slip threshold, derives a divergence phenomenon value of the at least one observation signal based on the code pseudorange and the carrier phase based on the result of the determination, determines the quality of the observation signal by comparing the divergence phenomenon value with a divergence threshold for each satellite elevation angle, and the cycle slip threshold is dynamically set according to a Rate of Total Electron Content Index (ROTI) value calculated based on a GF combination for a plurality of observation signals.

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