Space atmosphere anomaly decorrelation integrity monitoring method

Abstract

The invention provides a space atmosphere anomaly decorrelation integrity monitoring method based on two different frequency point pseudo-range and carrier phase observation signals of the same satellite navigation system. On the basis of the frequency correlation between the ionosphere delay and the troposphere delay, the on-flight decoupling monitoring of the ionosphere anomaly and the troposphere anomaly is realized, the problem that the traditional monitoring method cannot distinguish the reason of the space atmosphere anomaly is solved, and the integrity and availability of the GNSS navigation service are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of GNSS (Global Navigation Satellite Systems) integrity monitoring, and specifically to a method for realizing decorrelation integrity monitoring of two types of space atmospheric anomalies, ionosphere and troposphere, by performing decorrelation analysis on ionosphere anomalies and troposphere anomalies, thereby ensuring the accuracy and reliability of GNSS differential positioning. Background Art

[0002] GNSS differential positioning can provide users with accurate and reliable relative navigation information and is widely used in civil aviation landing guidance services. In the face of different navigation stages, the navigation performance parameters required for landing guidance services have different definitions. In order to meet the accuracy and integrity requirements of high-level landing guidance services, the risk sources of GNSS differential positioning must be properly handled. Among them, the ionosphere and troposphere are two key risk sources faced by GNSS signals in the space atmospheric segment transmission stage. Their delay changes are closely related to atmospheric activities and are difficult to accurately predict and model. When the atmospheric activity is normal, after being eliminated by differential technology, the ionosphere / troposphere delay residual will not pose a threat to the accuracy and integrity of landing guidance services. However, when the atmospheric activity is abnormal, the ionosphere / troposphere spatial gradient is very likely to produce horizontal decorrelation locally, resulting in abnormal differential ionosphere / troposphere delay, which seriously affects the accuracy and integrity of civil aviation landing guidance services [1-2]. Therefore. It is necessary to carry out integrity monitoring of both types of space atmospheric anomalies in the ionosphere / troposphere.

[0003] In the field of civil aviation, a lot of research has been done on the integrity monitoring of space atmosphere anomalies. The mainstream method is to monitor space atmosphere anomalies based on carrier phase difference technology [3-4]. The hardware basis of this method is two reference receivers fixedly deployed on land (baseline length is usually less than 5km). The original observations received by the two receivers are used to construct the double difference observations between the satellite and the receiver, eliminate the satellite and receiver clock errors, use the precise coordinates of the reference receiver antenna to correct the geometric quantities, and use the ambiguity fixed solution to correct the ambiguity terms. At this time, the carrier phase double difference residual only contains the double difference ionospheric delay and tropospheric delay. Using the carrier phase double difference residual to carry out integrity monitoring can effectively detect the presence of anomalies in the ionospheric gradient or tropospheric gradient. However, the limitation of this method is that it is impossible to distinguish the cause of the anomaly, that is, whether the anomaly is caused by the ionospheric gradient or the tropospheric gradient, which makes it difficult to select the corresponding processing strategy for different anomaly types. Specifically, ionospheric anomalies may cause tropospheric anomaly monitor alarms, and similarly, tropospheric anomalies may also cause ionospheric anomaly monitor alarms.

[0004] In addition, with the gradual development of GNSS meteorology, more and more space atmospheric anomalies are observed and recorded. According to the long-term ionospheric gradient observation records published by Stanford University, the probability of ionospheric gradient anomaly is conservatively estimated to be about 10 -3 According to the tropospheric inversion results of the European Center for Medium-Range Weather Forecasts, the probability of tropospheric gradient anomaly in the Asia-Pacific region is conservatively estimated to be about 5.3×10 -3 Based on this, it can be inferred that the probability of simultaneous occurrence of ionospheric anomalies and tropospheric anomalies is about 5.3×10 -6 Considering that the maximum tolerable integrity risk of a civil aviation Category III approach is only 10 -9 , which is much lower than the probability of the simultaneous occurrence of ionospheric and tropospheric anomalies. Therefore, the simultaneous occurrence of ionospheric gradient anomalies and tropospheric gradient anomalies must be considered. In other words, the limitation of the existing method ② is that in extreme cases, that is, when ionospheric and tropospheric anomalies occur simultaneously, the existing method cannot realize the decorrelation monitoring of the two types of space atmospheric anomalies, which leads to potential integrity risks.

[0005] In summary, the existing space atmospheric anomaly integrity monitoring method based on carrier phase differential processing conducts integrity monitoring of two types of space atmospheric anomalies, the ionosphere and the troposphere, based on the same detection statistic, and is unable to perform decorrelation analysis on the two types of space atmospheric anomalies, resulting in the inability to synchronously monitor ionosphere and troposphere anomalies, making it difficult for ground monitoring facilities to timely select the correct anomaly handling strategy and alleviate the impact of space atmospheric anomalies on navigation services.

[0006] References are as follows:

[0007] [1]Wang Z,Wang S,Zhao Y,Xin P.Assessment of Ionospheric GradientImpacts on Ground-Based Augmentation System(GBAS)Data in Guangdong Province,China[J].Sensors,2017,17(10):2313.

[0008] [2]Huang J,Graas FV,Cohenour C.Characterization of troposphericspatial decorrelation errors over a 5-km baseline[J].Navigation,2008,55:39-53.

[0009] [3]Patel J,Khanafseh S,Pervan B.Detecting hazardous spatial gradientsat satellite acquisition in GBAS[J].IEEE Transactions on Aerospace and Electronic Systems,2020,56(4):3214-3230.

[0010] [4] Zhang Y, Wang Z. The impact of tropospheric anomalies on sea-basedJPALS integrity[J]. Sensors, 2018, (8): 2579. Summary of the invention

[0011] The purpose of the present invention is to realize decorrelation integrity monitoring of space atmospheric anomalies, timely identify the causes of anomalies, assist ground monitoring centers in accurately selecting corresponding anomaly processing methods, and reduce the impact of ionospheric or tropospheric anomalies on navigation service accuracy and integrity.

[0012] In order to achieve the above-mentioned object of the invention, the technical solution of the present invention provides a space atmospheric anomaly decorrelation integrity monitoring method, comprising the following steps:

[0013] Step 1: Use the carrier phase and pseudorange observations of different frequencies of the same satellite navigation system to build an inter-satellite-station double-difference observation model, calculate the adaptive smoothing length according to the continuity risk allocation result, perform adaptive smoothing and noise reduction on the double-difference observation model, and then fix the integer ambiguity in the double-difference observation model and verify its fixation correctness;

[0014] Step 2: To avoid the influence of space atmospheric anomalies on cycle slip detection, a geometrically independent and ionospheric cycle slip detection statistic is constructed based on carrier phase and pseudorange observations. The cycle slip detection threshold is selected in combination with the observation data sampling rate, and cycle slip detection is carried out epoch by epoch.

[0015] Step 3: If the cycle slip detection statistic exceeds the cycle slip detection threshold, that is, a cycle slip occurs, the double difference observation model is adaptively smoothed and denoised again, and then the fixed integer ambiguity is tested again; if the cycle slip detection statistic does not exceed the cycle slip detection threshold, that is, no cycle slip occurs, the fixed integer ambiguity is substituted into the double difference observation model in step 1 to eliminate the ambiguity term, and the precise receiver antenna coordinates are used to eliminate the geometric term synchronously to obtain the double difference residual of the carrier phase at different frequency points;

[0016] Step 4: Under the same epoch, select the high-frequency carrier phase double difference residual as the x-axis variable and the low-frequency carrier phase double difference residual as the y-axis variable from the carrier phase double difference residuals at different frequencies, establish a two-dimensional distribution coordinate system, and then obtain the spatial atmospheric anomaly decorrelation detection statistic that obeys the two-dimensional Gaussian distribution, and simultaneously draw the spatial atmospheric anomaly decorrelation analysis diagram;

[0017] Step 5: Calculate the two-dimensional Gaussian distribution detection threshold under different noise levels, select the corresponding two-dimensional Gaussian distribution detection threshold according to the integrity and continuity risk allocation results, and compare the spatial atmospheric anomaly decorrelation detection statistic with the two-dimensional Gaussian distribution detection threshold value;

[0018] Step 6: If in the spatial atmospheric anomaly decorrelation analysis diagram, the spatial atmospheric anomaly decorrelation detection statistics are concentrated on the trend line of the first slope, where the first slope is the ratio of the high-frequency carrier phase wavelength to the low-frequency carrier phase wavelength, and the spatial atmospheric anomaly decorrelation detection statistics exceeds the detection threshold, it indicates that there is an anomaly in the troposphere at this time, and the user should be warned in time and the positioning solution strategy should be adjusted according to the troposphere anomaly;

[0019] If in the spatial atmospheric anomaly decorrelation analysis diagram, the spatial atmospheric anomaly decorrelation detection statistics are concentrated on the trend line of the second slope, the second slope is the ratio of the low-frequency carrier phase wavelength to the high-frequency carrier phase wavelength, and the spatial atmospheric anomaly decorrelation detection statistics exceeds the detection threshold, it indicates that the ionosphere is abnormal at this time, and the user should be warned in time and the positioning solution strategy should be adjusted according to the ionosphere anomaly;

[0020] Step 7: If in the spatial atmospheric anomaly decorrelation analysis diagram, the spatial atmospheric anomaly decorrelation detection statistics are discretely distributed near the origin of the coordinate system, and the spatial atmospheric anomaly decorrelation detection statistics do not exceed the detection threshold, then the spatial atmospheric activity is normal at this time, and the user can perform normal positioning and solution.

[0021] Preferably, the pseudorange and carrier phase observations of the B1 and B3 frequencies of the Beidou satellite navigation system are selected to carry out space atmospheric anomaly decorrelation integrity monitoring.

[0022] Preferably, the formula of the double difference observation model is as follows:

[0023]

[0024] In the formula, represents the double difference operator, P and φ represent the pseudorange and carrier phase observations respectively, s and s′ represent the visible satellite and reference satellite respectively, a1 represents the visible receiver antenna, a2 represents the reference receiver antenna, b represents the baseline vector, e represents the unit line of sight vector from the user to the satellite, f1 and f3 represent the signal frequencies corresponding to the B1 and B3 frequency points of the Beidou satellite navigation system respectively, λf represents the carrier phase wavelength corresponding to the frequency point f, N represents the integer ambiguity, I and T represent the ionospheric and tropospheric delays respectively.

[0025] Preferably, the calculation formula of the adaptive smoothing length is as follows:

[0026]

[0027] In the formula, CR req To allocate continuity risk requirements, represents the floating point ambiguity, represents the standard deviation of the floating point ambiguity noise after adaptive smoothing, L is the adaptive smoothing length, φ represents the carrier phase observation, λ f Indicates the carrier phase wavelength corresponding to the frequency point f.

[0028] Preferably, the integer ambiguity estimation formula is as follows:

[0029]

[0030] In the formula, represents the double difference operator, argmin(*) represents the value of z when the formula reaches the minimum value, represents the floating point ambiguity, represents the integer ambiguity, and s represents the visible satellite.

[0031] Preferably, the construction formula of the correctness test statistic of the integer ambiguity is as follows:

[0032]

[0033] In the formula, and They represent the optimal and suboptimal solutions obtained by integer estimation respectively, and c represents the speed of light.

[0034] Preferably, the formula for the cycle slip detection statistic is as follows:

[0035]

[0036] γ represents the difference between the previous and next epochs, φ1 represents the carrier phase observation of the B1 frequency point of the Beidou satellite navigation system, φ3 represents the carrier phase observation of the B3 frequency point of the Beidou satellite navigation system, P1 represents the pseudorange of the B1 frequency point of the Beidou satellite navigation system, P3 represents the pseudorange of the B3 frequency point of the Beidou satellite navigation system, and c represents the speed of light.

[0037] Preferably, the formula for the cycle slip detection threshold is as follows:

[0038]

[0039] Where E and S represent the satellite altitude angle and sampling update rate respectively.

[0040] Preferably, the carrier phase double difference residual corresponding to the B1 frequency point and the B3 frequency point, that is, the spatial atmospheric anomaly decorrelation detection statistic that obeys the two-dimensional Gaussian distribution, is as follows:

[0041]

[0042] In the formula, represents the double difference operator, s and s′ represent the visible satellite and the reference satellite respectively, a1 represents the visible receiver antenna, a2 represents the reference receiver antenna, B1 represents the B1 frequency of the BeiDou satellite navigation system, B3 represents the B3 frequency of the BeiDou satellite navigation system, λ1 represents the carrier phase wavelength of the B1 frequency, λ3 represents the carrier phase wavelength of the B3 frequency, q represents the spatial atmospheric anomaly decorrelation detection statistic, I and T represent the ionospheric and tropospheric delays respectively, and Φ represents the carrier phase observation in weeks.

[0043] Preferably, the calculation formula of the two-dimensional Gaussian distribution detection threshold is as follows:

[0044]

[0045] Where P represents pseudorange, q1 represents the spatial atmospheric anomaly decorrelation detection statistic of the B1 frequency point of the BeiDou satellite navigation system, q2 represents the spatial atmospheric anomaly decorrelation detection statistic of the B3 frequency point of the BeiDou satellite navigation system, φ1 represents the carrier phase observation of the B1 frequency point of the BeiDou satellite navigation system, φ3 represents the carrier phase observation of the B3 frequency point of the BeiDou satellite navigation system, represents the double difference operator, represents the standard deviation of floating-point ambiguity noise after adaptive smoothing, and H0 represents the normal assumption of spatial atmospheric activity.

[0046] Preferably, the first slope and the second slope are respectively expressed as and

[0047] The technical solution of the present invention is based on two different frequency pseudorange and carrier phase observation signals of the same satellite navigation system, and proposes a space atmospheric anomaly decorrelation integrity monitoring method. Based on the frequency correlation of ionospheric delay and tropospheric delay, the on-board decoupled monitoring of ionospheric anomalies and tropospheric anomalies is realized, which solves the problem that traditional monitoring methods cannot distinguish the causes of space atmospheric anomalies, and improves the integrity and availability of GNSS navigation services. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 Flow chart of a space atmospheric anomaly decorrelation integrity monitoring method provided by an embodiment of the present invention

[0049] Figure 2 A schematic diagram of space atmosphere anomaly decorrelation analysis of a space atmosphere anomaly decorrelation integrity monitoring method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only intended to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art may make various changes or modifications to the present invention, and these equivalent forms fall within the scope limited by the appended claims of the application equally.

[0051] like Figure 1 As shown, in a space atmosphere anomaly decorrelation integrity monitoring method provided in this embodiment, taking the B1 and B3 frequency points in the Beidou Navigation Satellite System (BDS) as an example, the following steps are included:

[0052] It should be understood that the embodiments of the present invention are also applicable to the Global Positioning System (GPS), the GLONASS satellite navigation system (GLONASS), and the Galileo satellite navigation system (Galileo), as long as the pseudoranges and carrier phase observations of two different frequencies under the same satellite navigation system can be collected. It should be noted that, taking the typical satellite navigation systems GPS and Beidou as examples, GPS publicly provides users with three frequency navigation signals of L1, L2 and L5, and the method described in this article can use the frequency combination of (L1, L2), (L1, L5), (L2, L5); Beidou publicly provides users with three frequency navigation signals of B1, B2 and B3, and the method described in this article can use the frequency combination of (B1, B2), (B1, B3), (B2, B3).

[0053] Step 1: Obtain the carrier phase and pseudorange observations of different frequencies of the same satellite navigation system including GPS, GLONASS, Galileo, and Beidou, and construct a double-difference observation model through inter-satellite-inter-station difference. Considering that the difference in the frequency of the Beidou (B1, B3) frequency signals is large, it is better to use it for decorrelation analysis of space atmospheric anomalies. Therefore, the method described in this paper gives priority to Beidou (B1, B3) frequency points. In the initialization stage of space atmospheric anomaly monitoring, according to the risk allocation results of atmospheric anomaly monitoring continuity and integrity, the noise of the double-difference observation model is substituted into the ambiguity theory success rate calculation formula, and the adaptive smoothing length required to meet the allocation result is calculated. Then, the calculated smoothing length is used to smooth and reduce the noise of the double-difference observation model, and the integer ambiguity in the double-difference observation model is fixed. At the same time, the correctness of the fuzziness fixation value is checked by using the ratio test, and the ratio parameter is set to 1 / 3 to improve the success rate of fuzziness fixation. If the ratio test passes, it is considered that the fuzziness fixation is correct, and then step 2 is executed. Otherwise, smoothing and noise reduction are performed again, and the fuzziness fixation is performed again until the ratio test passes, and then the relevant content of step 2 is executed;

[0054] Step 2: Both ionospheric anomalies and tropospheric anomalies will have an adverse effect on the traditional cycle slip detection method. Therefore, this method will use geometric irrelevant combination to eliminate the influence of tropospheric anomalies, eliminate ionospheric combination to eliminate ionospheric influence, eliminate irrelevant interference items through inter-epoch difference, and set the cycle slip detection threshold in combination with different data sampling rates, and perform cycle slip detection epoch by epoch;

[0055] Step 3: If the cycle slip detection statistic exceeds the detection threshold, that is, a cycle slip occurs, then it is impossible to effectively carry out space atmospheric anomaly integrity monitoring, and it is necessary to re-adaptively smooth and denoise the double-difference observation model to fix the integer ambiguity, that is, re-execute steps 1-2; if the cycle slip detection statistic does not exceed the detection threshold, that is, no cycle slip occurs, then it is considered that the integer ambiguity has been correctly fixed by the previous epoch, and there is no need to repeat the solution. The integer ambiguity after the previous epoch is fixed is directly substituted into the double-difference observation model to eliminate the ambiguity term, and the precise receiver antenna coordinates are used simultaneously to eliminate the geometric term to obtain the carrier phase double-difference residuals at different frequencies. At this time, the carrier phase double-difference residuals only contain the double-difference ionospheric error, the double-difference tropospheric error, and the observation noise;

[0056] Step 4: Under the same epoch, select the high-frequency carrier phase double difference residual from the different frequency carrier phase double difference residuals as the x-axis variable, that is, the B1 frequency carrier phase double difference residual is used as the x-axis variable, and the low-frequency carrier phase double difference residual is used as the y-axis variable, that is, the B3 frequency carrier phase double difference residual is used as the y-axis variable, establish a two-dimensional distribution coordinate system, draw a spatial atmospheric anomaly decorrelation analysis diagram, and simultaneously obtain the spatial atmospheric anomaly decorrelation detection statistic that obeys the two-dimensional Gaussian distribution;

[0057] Step 5: Calculate the two-dimensional Gaussian distribution detection threshold under different noise levels, create a spatial atmospheric anomaly detection threshold distribution table, query and select the corresponding detection threshold according to the real-time distribution results of integrity and continuity risks during the actual monitoring process, and then compare the spatial atmospheric anomaly decorrelation detection statistics with the detection threshold value;

[0058] Step 6: If, in the spatial atmospheric anomaly decorrelation analysis diagram, the spatial atmospheric anomaly decorrelation detection statistic is concentrated on the trend line of the first slope, where the first slope is the ratio of the high-frequency carrier phase wavelength to the low-frequency carrier phase wavelength, i.e., λ1 / λ3, and the spatial atmospheric anomaly decorrelation detection statistic exceeds the detection threshold, it indicates that there is an anomaly in the troposphere at this time, and the user should be warned in time and the positioning solution strategy should be adjusted according to the troposphere anomaly;

[0059] If in the spatial atmospheric anomaly decorrelation analysis diagram, the spatial atmospheric anomaly decorrelation detection statistics are concentrated on the trend line of the second slope, the second slope is the ratio of the low-frequency carrier phase wavelength to the high-frequency carrier phase wavelength, that is, λ3 / λ1, and the spatial atmospheric anomaly decorrelation detection statistics exceeds the detection threshold, it indicates that the ionosphere is abnormal at this time, and the user should be warned in time and the positioning solution strategy should be adjusted according to the ionosphere anomaly;

[0060] Step 7: If in the spatial atmospheric anomaly decorrelation analysis diagram, the spatial atmospheric anomaly decorrelation detection statistic is discretely distributed near the origin of the coordinate system, and the spatial atmospheric anomaly decorrelation detection statistic does not exceed the detection threshold, then the spatial atmospheric activity is normal at this time, and the user can perform normal positioning and solving.

[0061] In step 1, the integer ambiguity resolution of the B1 and B3 frequency points is as follows:

[0062] The minimum smoothing length is calculated based on the continuous risk allocation results. The calculation formula is shown in formula (1):

[0063]

[0064] In the formula, CR req To allocate continuity risk requirements, represents the floating point ambiguity, represents the standard deviation of floating point ambiguity noise after adaptive smoothing, and L is the adaptive smoothing length.

[0065] Then, the double difference observation model of inter-satellite-station carrier phase and pseudo-range at B1 and B3 frequency points is constructed as shown in formula (2):

[0066]

[0067] In the formula, represents the double difference operator, P and φ represent the pseudorange and carrier phase observations respectively, s and s′ represent the visible satellite and reference satellite respectively, a represents the reference receiver antenna, b represents the baseline vector, e represents the unit line of sight vector between the user and the satellite, f1 and f3 represent the signal frequencies corresponding to the B1 and B3 frequency points respectively, and represents λ f represents the carrier phase wavelength corresponding to the frequency point f, N represents the integer ambiguity, I and T represent the ionospheric and tropospheric delays respectively.

[0068] The double-difference observations are smoothed and denoised using the smoothing length calculated according to formula (1), and the integer least squares method is used to estimate the integer solution of the ambiguity, and the ratio test is used to improve the success rate of ambiguity fixation. The double-difference ambiguity formula for fixing the B1 and B3 frequency points using the integer least squares algorithm is shown in (3):

[0069]

[0070] In the formula, argmin(*) represents the value of z when the formula reaches the minimum value. represents the floating point ambiguity, Represents the integer ambiguity.

[0071] After the fuzziness value is fixed by the integer least squares method, the correctness test of the fixed value is carried out using the ratio test method. The statistical construction form of the ratio test is shown in formula (4):

[0072]

[0073] In the formula, and denote the optimal and suboptimal solutions obtained by integer estimation, respectively. Represents the covariance corresponding to the floating-point solution of the ambiguity. After the ratio test, it is considered that the integer ambiguity is fixed correctly. When no cycle slip occurs, the integer ambiguity will remain unchanged. At this time, it is no longer necessary to carry out ambiguity fixation per epoch, which greatly improves efficiency.

[0074] In step 2, the carrier phase and pseudorange observations of the B1 and B3 frequencies are used to construct wide lane and geometry-independent observations and perform differences between the previous and next epochs to construct the cycle slip detection statistic T MW As shown in formula (5):

[0075]

[0076] Where γ represents the difference between the previous and next epochs, φ1 represents the carrier phase observation at the B1 frequency point, φ3 represents the carrier phase observation at the B3 frequency point, P1 represents the pseudorange at the B1 frequency point, P3 represents the pseudorange at the B3 frequency point, and c represents the speed of light.

[0077] The calculation method of the corresponding cycle slip detection threshold is shown in formula (6):

[0078]

[0079] Where E and S represent the satellite elevation angle and the sampling update rate, respectively. If a cycle slip occurs, the integer ambiguity resolution process in step 1 is repeated. If no cycle slip occurs, the B1 and B3 integer ambiguities fixed in step 1 are substituted into the B1 and B3 double-difference carrier phase observations to eliminate the ambiguity terms. The geometric terms in the double-difference carrier phase observations are eliminated using the precise receiver antenna coordinates. To keep the formula simple, the satellite and receiver corner marks are ignored. The carrier phase double-difference residuals corresponding to the B1 and B3 frequency points are the spatial atmospheric anomaly decorrelation detection statistics that obey a two-dimensional Gaussian distribution as shown in formula (7):

[0080]

[0081] In step 4, the double difference residual of the carrier phase at the B1 frequency point is used as the X-axis variable, and the double difference residual of the carrier phase at the B3 frequency point is used as the Y-axis variable to draw the spatial atmospheric anomaly decorrelation analysis diagram as shown in the figure. Figure 2 shown.

[0082] In step 5, the two-dimensional Gaussian distribution detection threshold under different noise levels is calculated to satisfy the requirements of formula (8):

[0083]

[0084] According to the integrity and continuity risk allocation results, the corresponding detection threshold is selected from the two-dimensional Gaussian distribution detection threshold distribution table, and the spatial atmospheric anomaly decorrelation detection statistics are compared with the detection threshold value.

[0085] In step 6, within a period of time, if the spatial atmospheric anomaly decorrelation detection statistic exceeds the limit and is concentrated on the trend line with a slope of λ1 / λ3, then there is an anomaly in the troposphere, and the user should be warned in time and the positioning solution strategy should be adjusted for the anomaly in the troposphere. Similarly, if the spatial atmospheric anomaly decorrelation detection statistic exceeds the limit and is concentrated on the trend line with a slope of λ3 / λ1, then there is an anomaly in the ionosphere, and the user should be warned in time and the positioning solution strategy should be adjusted for the anomaly in the ionosphere;

[0086] In step 7, if in the spatial atmospheric anomaly decorrelation analysis diagram, the spatial atmospheric anomaly decorrelation detection statistic is discretely distributed near the origin of the coordinate system, and the spatial atmospheric anomaly decorrelation detection statistic does not exceed the detection threshold, then the spatial atmospheric activity is normal at this time, and the user can perform normal positioning and solution.

[0087] The beneficial effects of a space atmosphere anomaly decorrelation integrity monitoring method provided by an embodiment of the present invention are:

[0088] Space atmospheric anomalies are a key risk source that affects the accuracy and integrity of GNSS differential positioning and must be effectively monitored. The present invention cleverly utilizes the frequency-dependent characteristics of ionospheric delay and the frequency-independent characteristics of tropospheric delay to construct a space atmospheric anomaly detection statistic that is sensitive to signal frequency, realizes decorrelation analysis of ionospheric and tropospheric anomalies, and assists ground monitoring facilities in realizing rapid identification of the causes of space atmospheric anomalies, thereby accurately selecting the corresponding navigation algorithm to alleviate the impact of ionospheric / tropospheric anomalies on differential positioning accuracy and integrity.

Claims

1. A space atmosphere anomaly decorrelation integrity monitoring method, characterized in that: The following steps are involved: Step 1: Use the carrier phase and pseudorange observations of different frequencies of the same satellite navigation system to build an inter-satellite-station double-difference observation model, calculate the adaptive smoothing length according to the continuity risk allocation result, perform adaptive smoothing and noise reduction on the double-difference observation model, and then fix the integer ambiguity in the double-difference observation model and verify its fixation correctness; Step 2: To avoid the influence of space atmospheric anomalies on cycle slip detection, a geometrically independent and ionospheric cycle slip detection statistic is constructed based on carrier phase and pseudorange observations. The cycle slip detection threshold is selected in combination with the observation data sampling rate, and cycle slip detection is carried out epoch by epoch. Step 3: If the cycle slip detection statistic exceeds the cycle slip detection threshold, that is, a cycle slip occurs, the double difference observation model is adaptively smoothed and denoised again, and then the integer ambiguity is fixed and tested again; If the cycle slip detection statistic does not exceed the cycle slip detection threshold, that is, no cycle slip occurs, the fixed integer ambiguity is substituted into the double difference observation model in step 1 to eliminate the ambiguity term, and the precise receiver antenna coordinates are used to eliminate the geometric term to obtain the double difference residual of the carrier phase at different frequency points; Step 4: Under the same epoch, select the high-frequency carrier phase double difference residual as the x-axis variable and the low-frequency carrier phase double difference residual as the y-axis variable from the carrier phase double difference residuals at different frequencies, establish a two-dimensional distribution coordinate system, and then obtain the spatial atmospheric anomaly decorrelation detection statistic that obeys the two-dimensional Gaussian distribution, and simultaneously draw the spatial atmospheric anomaly decorrelation analysis diagram; Step 5: Calculate the two-dimensional Gaussian distribution detection threshold under different noise levels, select the corresponding two-dimensional Gaussian distribution detection threshold according to the integrity and continuity risk allocation results, and compare the spatial atmospheric anomaly decorrelation detection statistic with the two-dimensional Gaussian distribution detection threshold value; Step 6: If in the spatial atmospheric anomaly decorrelation analysis diagram, the spatial atmospheric anomaly decorrelation detection statistics are concentrated on the trend line of the first slope, where the first slope is the ratio of the high-frequency carrier phase wavelength to the low-frequency carrier phase wavelength, and the spatial atmospheric anomaly decorrelation detection statistics exceeds the detection threshold, it indicates that there is an anomaly in the troposphere at this time, and the user should be warned in time and the positioning solution strategy should be adjusted according to the troposphere anomaly; If in the spatial atmospheric anomaly decorrelation analysis diagram, the spatial atmospheric anomaly decorrelation detection statistics are concentrated on the trend line of the second slope, the second slope is the ratio of the low-frequency carrier phase wavelength to the high-frequency carrier phase wavelength, and the spatial atmospheric anomaly decorrelation detection statistics exceeds the detection threshold, it indicates that the ionosphere is abnormal at this time, and the user should be warned in time and the positioning solution strategy should be adjusted according to the ionosphere anomaly; Step 7: If in the spatial atmospheric anomaly decorrelation analysis diagram, the spatial atmospheric anomaly decorrelation detection statistics are discretely distributed near the origin of the coordinate system, and the spatial atmospheric anomaly decorrelation detection statistics do not exceed the detection threshold, then the spatial atmospheric activity is normal at this time, and the user can perform normal positioning and solution.

2. A space atmosphere anomaly decorrelation integrity monitoring method as claimed in claim 1, characterized in that: The formula of the double difference observation model is as follows: In the formula, represents the double difference operator, P and φ represent the pseudorange and carrier phase observations respectively, s and s′ represent the visible satellite and reference satellite respectively, a1 represents the visible receiver antenna, a2 represents the reference receiver antenna, b represents the baseline vector, e represents the unit line of sight vector from the user to the satellite, f1 and f3 represent the signal frequencies corresponding to the B1 and B3 frequency points of the Beidou satellite navigation system respectively, λ f represents the carrier phase wavelength corresponding to the frequency point f, N represents the integer ambiguity, I and T represent the ionospheric and tropospheric delays respectively.

3. A space atmosphere anomaly decorrelation integrity monitoring method as claimed in claim 1, characterized in that: The calculation formula of the adaptive smoothing length is as follows: In the formula, CR req To allocate continuity risk requirements, represents the floating point ambiguity, represents the standard deviation of the floating point ambiguity noise after adaptive smoothing, L is the adaptive smoothing length, φ represents the carrier phase observation, λ f Indicates the carrier phase wavelength corresponding to the frequency point f.

4. A space atmosphere anomaly decorrelation integrity monitoring method as claimed in claim 1, characterized in that: The estimation formula of the integer ambiguity is as follows: In the formula, represents the double difference operator, argmin(*) represents the value of z when the formula reaches the minimum value, represents the floating point ambiguity, represents the integer ambiguity, and s represents the visible satellite.

5. The method for monitoring the integrity of space atmospheric anomaly decorrelation according to claim 1, characterized in that: The construction formula of the correctness test statistic of the integer ambiguity is as follows: In the formula, and They represent the optimal and suboptimal solutions obtained by integer estimation respectively, and c represents the speed of light.

6. A space atmosphere anomaly decorrelation integrity monitoring method according to claim 1, characterized in that: The formula for the cycle slip detection statistic is as follows: γ represents the difference between the previous and next epochs, φ1 represents the carrier phase observation of the B1 frequency point of the Beidou satellite navigation system, φ3 represents the carrier phase observation of the B3 frequency point of the Beidou satellite navigation system, P1 represents the pseudorange of the B1 frequency point of the Beidou satellite navigation system, P3 represents the pseudorange of the B3 frequency point of the Beidou satellite navigation system, and c represents the speed of light.

7. A space atmosphere anomaly decorrelation integrity monitoring method as claimed in claim 1, characterized in that: The formula for the cycle slip detection threshold is as follows: Where E and S represent the satellite altitude angle and sampling update rate respectively.

8. A space atmosphere anomaly decorrelation integrity monitoring method as claimed in claim 1, characterized in that: The formula of the spatial atmospheric anomaly decorrelation detection statistic is as follows: In the formula, represents the double difference operator, s and s′ represent the visible satellite and the reference satellite respectively, a1 represents the visible receiver antenna, a2 represents the reference receiver antenna, B1 represents the B1 frequency of the Beidou satellite navigation system, B3 represents the B3 frequency of the Beidou satellite navigation system, λ1 represents the carrier phase wavelength of the B1 frequency, λ3 represents the carrier phase wavelength of the B3 frequency, q represents the spatial atmospheric anomaly decorrelation detection statistic, I and T represent the ionospheric and tropospheric delays respectively, and φ represents the carrier phase observation.

9. A space atmosphere anomaly decorrelation integrity monitoring method as claimed in claim 1, characterized in that: The calculation formula of the two-dimensional Gaussian distribution detection threshold is as follows: Where P represents pseudorange, q1 represents the spatial atmospheric anomaly decorrelation detection statistic of the B1 frequency point of the BeiDou satellite navigation system, q2 represents the spatial atmospheric anomaly decorrelation detection statistic of the B3 frequency point of the BeiDou satellite navigation system, φ1 represents the carrier phase observation of the B1 frequency point of the BeiDou satellite navigation system, φ3 represents the carrier phase observation of the B3 frequency point of the BeiDou satellite navigation system, represents the double difference operator, represents the standard deviation of floating-point ambiguity noise after adaptive smoothing, and H0 represents the normal assumption of spatial atmospheric activity.

10. A space atmosphere anomaly decorrelation integrity monitoring method according to claim 1, characterized in that: The first slope and the second slope are respectively expressed as and

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