CN112526563A - GNSS signal quality monitoring method and system - Google Patents
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Abstract
The invention relates to a GNSS signal quality monitoring method and a GNSS signal quality monitoring system, belongs to the technical field of satellite navigation, and solves the problems that related peak passivation is not considered, observed quantity cannot be fully utilized, and measurement accuracy is low in the prior art. The method comprises the steps of obtaining a relevant peak sampling value of a GNSS signal sent by a receiver; preprocessing the related peak sampling value to obtain a preprocessed related peak sampling value; setting a target function with a symmetry axis, and performing data fitting on the preprocessed related peak sampling value by taking the target function as a fitting target to obtain a related peak curve, wherein the symmetry axis of the curve is observation statistics; based on the satellite elevation angle interval, grouping observation statistics, processing the observation statistics of each elevation angle interval, and obtaining a statistic threshold value of each elevation angle interval; and comparing the observation statistics with the statistic threshold value of the elevation angle interval corresponding to the observation statistics, and judging the quality of the GNSS signal corresponding to the observation statistics, so that the accuracy of GNSS signal quality monitoring is improved.
Description
Technical Field
The invention relates to the technical field of satellite navigation, in particular to a GNSS signal quality monitoring method and a GNSS signal quality monitoring system.
Background
With the rapid development of aerospace and wireless communication technologies, the precision requirement of a satellite navigation system is higher and higher, wherein the quality of a navigation signal determines the innate performance of the navigation system, and when the satellite signal receives interference, a correlation peak generated by a pseudo code correlator of a user receiver generates deviation to cause large errors in positioning and ranging, so that the monitoring of the quality of the GNSS signal refers to the monitoring of the symmetry of the correlation peak of the GNSS signal.
The existing detection method for GNSS signal quality mainly comprises a difference detection method and an expansion method thereof, wherein correlation values of two symmetrical sampling points are used for making a difference, and then whether the symmetry is abnormal or not is judged; and a slope method for judging whether the slopes of the two sides are consistent to judge the abnormal condition of the correlation peak. The traditional methods have low monitoring precision, do not consider the situation of relevant peak passivation, cannot fully utilize observed quantity and have low measurement precision.
In order to solve the problems that the existing detection method does not consider the passivation condition of the related peak, cannot fully utilize the observed quantity and has low measurement accuracy, a GNSS signal quality monitoring method is urgently needed to be found.
Disclosure of Invention
In view of the foregoing analysis, embodiments of the present invention provide a GNSS signal quality monitoring method and system, so as to solve the problems that the passivation of a correlation peak is not considered in the conventional detection method, the observed quantity cannot be fully utilized, and the measurement accuracy is low.
In one aspect, an embodiment of the present invention provides a GNSS signal quality monitoring method, including:
acquiring a related peak sampling value of a GNSS signal sent by a receiver;
preprocessing the relevant peak sampling value to obtain a preprocessed relevant peak sampling value;
setting a target function with a symmetry axis, and performing data fitting on the preprocessed related peak sampling value by taking the target function as a fitting target to obtain a related peak curve, wherein the symmetry axis of the related peak curve is observation statistics;
grouping the observation statistics based on the satellite elevation intervals, and processing the observation statistics of each elevation interval to obtain a statistic threshold value of each elevation interval;
and comparing the observation statistics with a statistic threshold value of an elevation angle interval corresponding to the observation statistics, and judging the quality of the GNSS signal corresponding to the observation statistics.
Further, the method further comprises:
optimizing the observation statistics based on receiver bias and satellite bias to obtain optimized observation statistics;
grouping the optimized observation statistics based on the satellite elevation intervals, and processing the optimized observation statistics of each elevation interval to obtain a statistic threshold value of each elevation interval;
and comparing the optimized observation statistics with the statistic threshold value of the elevation angle interval corresponding to the observation statistics, and judging the quality of the GNSS signal corresponding to the observation statistics.
Further, preprocessing the correlation peak sampling value to obtain a preprocessed correlation peak sampling value includes:
smoothing the correlation peak sampling value to obtain a smoothed correlation peak sampling value;
and carrying out normalization processing on the smoothed correlation peak sampling value to obtain a preprocessed correlation peak sampling value.
Further, the objective function is a gaussian function or a quadratic function, and the obtaining of the correlation peak curve by performing data fitting on the preprocessed correlation peak sampling value with the objective function as a fitting target includes: and performing data fitting on the preprocessed related peak sampling value by adopting a least square method.
Further, processing the observation statistics of each elevation interval, and obtaining a statistic threshold value of each elevation interval comprises:
obtaining a mean value, a standard deviation and an expansion factor of the observation statistics corresponding to each elevation interval based on the observation statistics of each elevation interval;
and obtaining the statistic threshold value of each elevation angle interval by combining the false alarm probability based on the mean value, the standard deviation and the expansion factor of the observation statistic corresponding to each elevation angle interval.
Further, the comparing the observation statistic with the statistic threshold value of the elevation angle interval corresponding to the observation statistic, and the determining the quality of the GNSS signal corresponding to the observation statistic comprises:
when the observation statistic is smaller than a statistic threshold value in the corresponding elevation angle interval, the GNSS signal corresponding to the observation statistic is a normal signal;
and when the observed quantity is larger than or equal to a statistic threshold value in the corresponding elevation angle interval, the corresponding GNSS signal is an abnormal signal.
In another aspect, an embodiment of the present invention provides a GNSS signal quality monitoring system, including:
the signal receiving module is used for acquiring a related peak sampling value of the GNSS signal sent by the receiver;
the preprocessing module is used for preprocessing the related peak sampling value to obtain a preprocessed related peak sampling value;
the data fitting module is used for setting a target function with a symmetry axis, performing data fitting on the preprocessed related peak sampling value by taking the target function as a fitting target to obtain a related peak curve, and taking the symmetry axis of the related peak curve as observation statistics;
a statistic threshold value obtaining module, configured to group the observation statistic values based on satellite elevation angle intervals, process the observation statistic values of each elevation angle interval, and obtain a statistic threshold value of each elevation angle interval;
and the result analysis module is used for comparing the observation statistic with a statistic threshold value of the elevation angle interval corresponding to the observation statistic, and judging the quality of the GNSS signal corresponding to the observation statistic.
Further, the system also comprises an observation statistic optimization module, which is used for optimizing the observation statistic based on the receiver deviation and the satellite deviation to obtain the optimized observation statistic;
the statistic threshold value obtaining module is used for grouping the optimized observation statistic values based on satellite elevation angle intervals, processing the optimized observation statistic values of each elevation angle interval and obtaining a statistic threshold value of each elevation angle interval;
and the result analysis module compares the optimized observation statistics with the statistic threshold value of the elevation angle interval corresponding to the optimized observation statistics and judges the quality of the GNSS signal corresponding to the optimized observation statistics.
Further, the preprocessing module includes:
the smoothing module is used for smoothing the correlation peak sampling value to obtain a smoothed correlation peak sampling value;
and the normalization module is used for performing normalization processing on the smoothed correlation peak sampling value to obtain a preprocessed correlation peak sampling value.
Further, the statistic threshold value obtaining module includes:
the first calculation module is used for obtaining the mean value, the standard deviation and the expansion factor of the observation statistics corresponding to each elevation angle interval based on the observation statistics of each elevation angle interval;
and the second calculation module is used for obtaining the statistic threshold value of each elevation angle interval by combining the false alarm probability based on the mean value, the standard deviation and the expansion factor of the observation statistic corresponding to each elevation angle interval.
Compared with the prior art, the invention can at least realize the following beneficial effects:
compared with the prior art, the method for monitoring the quality of the GNSS signal, provided by the embodiment, considers the passivation condition of the correlation peak, and fits the correlation peak sampling value by setting the target function to obtain the correlation peak curve, so that the correlation peak sampling value is fully utilized, the symmetric axis of the correlation peak curve is taken as observation statistic, the degree of deviation of the GNSS signal from the standard signal (the signal with the symmetric axis being 0) is reflected, and whether the signal is abnormal or not is judged by combining the statistic threshold value, the accuracy of monitoring the quality of the GNSS signal is effectively improved, and the requirement of civil aviation is fully met.
In the invention, the technical schemes can be combined with each other to realize more preferable combination schemes. Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, wherein like reference numerals are used to designate like parts throughout.
FIG. 1 is a flowchart illustrating a GNSS signal quality monitoring method according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a GNSS signal quality monitoring system according to an embodiment of the present application.
Detailed Description
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate preferred embodiments of the invention and together with the description, serve to explain the principles of the invention and not to limit the scope of the invention.
In one aspect, the present invention discloses a GNSS signal quality monitoring method, and a flow diagram thereof is shown in fig. 1.
The GNSS signal quality monitoring method comprises the following steps:
step S1: acquiring a related peak sampling value of a GNSS signal sent by a receiver;
specifically, the same receiver may track multiple satellites simultaneously, the same satellite may also be tracked by multiple receivers simultaneously, one channel is determined between one receiver and one satellite, for example, the channel (m, n) represents a channel between the receiver m and the satellite n, each channel of each receiver may provide multiple correlation peak sample values, the number of correlation peak sample values of each channel may be determined according to the actual situation of the receiver process, optionally, the receiver samples the correlation peak of the GNSS signal at a sampling rate of 1HZ, each channel of each receiver may provide 8 correlation peak sample values, and the positions of the sample points corresponding to the sample values are: -0.075, -0.05, -0.025, 0, 0.025, 0.05, 0.075, 0.1 (code offset). In practical cases, the greater the number of sampling points in each channel, the more accurate the fitting of subsequent data, and the higher the monitoring accuracy.
Specifically, the correlation peak sample value in step S1 is a correlation peak sample value of a plurality of channels.
Step S2: preprocessing the relevant peak sampling value to obtain a preprocessed relevant peak sampling value;
step S3: setting a target function with a symmetry axis, and performing data fitting on the preprocessed related peak sampling value by taking the target function as a fitting target to obtain a related peak curve, wherein the symmetry axis of the related peak curve is observation statistics;
step S4: grouping the observation statistics based on the satellite elevation intervals, and processing the observation statistics of each elevation interval to obtain a statistic threshold value of each elevation interval;
step S5: and comparing the observation statistics with a statistic threshold value of an elevation angle interval corresponding to the observation statistics, and judging the quality of the GNSS signal corresponding to the observation statistics.
Compared with the prior art, the method for monitoring the quality of the GNSS signal, provided by the embodiment, considers the passivation condition of the correlation peak, and fits the correlation peak sampling value by setting the target function to obtain the correlation peak curve, so that the correlation peak sampling value is fully utilized, the symmetric axis of the correlation peak curve is taken as observation statistic, the degree of deviation of the GNSS signal from the standard signal (the signal with the symmetric axis being 0) is reflected, and whether the signal is abnormal or not is judged by combining the statistic threshold value, the accuracy of monitoring the quality of the GNSS signal is effectively improved, and the requirement of civil aviation is fully met.
In a specific embodiment, step S2 further includes:
step S21: smoothing the correlation peak sampling value to obtain a smoothed correlation peak sampling value;
specifically, since the signal-related peak sample values actually acquired are susceptible to the influence of multipath signals and random noise, in order to eliminate this influence, the related peak sample values acquired in step S1 are subjected to smoothing processing, and smoothed related peak sample values are obtained. Taking the correlation peak sampling point of the channel (m, n) as an example, the specific way of the smoothing processing is as follows, please refer to formula (1), where formula (1) is expressed as that the correlation peak sampling value at the time k-1 is used to perform smoothing processing on the correlation peak sampling value at the time k, so as to obtain the correlation peak sampling value after the smoothing processing at the time k:
wherein M ism,n(k) Representing the time k, the receiver m tracks the satellite n, namely the correlation function sampling value of the channel (m, n); ms,m,n(k) Representing the sampling value of the correlation peak after the receiver m tracks the satellite n and the channel (m, n) is smoothed at the moment k; ms,m,nAnd (k-1) represents the time of k-1, the receiver m tracks the satellite n, and the correlation peak sampling value after the smoothing processing of the channel (m, n) is a constant, and optionally, the value of H is 100.
Step S22: and carrying out normalization processing on the smoothed correlation peak sampling value to obtain a preprocessed correlation peak sampling value.
Specifically, because factors such as the position of the receiver, the gain, the antenna height, and the like also affect the power of the satellite signal, even for a signal transmitted by the same satellite, values obtained by different receivers also have a certain difference, and the difference has a certain influence on subsequent signal quality monitoring, so that normalization processing is adopted after smoothing filtering, and amplitude normalization is performed on a sampling value after smoothing processing, specifically as shown in formula (2):
wherein M iss,m,n(k) Representing the smoothed correlation peak sample value, M, of the channel (M, n) at time ks,m,n,max(k) Represents the maximum value, I, of the smoothed correlation peak sample values representing the channel (m, n) at time km,n(k) Represents the normalized correlation peak sample value of the channel (m, n), i.e. the preprocessed correlation peak sample value. Further, the smoothing and normalization processes are performed on the correlation peak sample value corresponding to each channel to obtain the correlation peak sample value after preprocessing, and the preprocessing is performed in each channelThe number of processed correlation peak sample values is the same as the number of correlation peak sample values that have not been preprocessed.
In a specific embodiment, the objective function with a symmetry axis set in step S3 may be a gaussian function or a quadratic function, and the step S3 of performing data fitting on the preprocessed correlated peak sample values with the objective function as a fitting target to obtain a correlated peak curve includes: and performing data fitting on the preprocessed related peak sampling value by adopting a least square method.
Specifically, the symmetry axis of the fitted correlation peak curve is used as the observation statistic, since the correlation peak of the normal signal has symmetry and the symmetry axis is at 0 offset, after the sampling values of the normal signal are fitted into the curve, the symmetry axis of the fitted curve is also at 0 offset, but due to some errors (such as multipath errors, filter influence and the like) in the signal propagation process, even if the symmetry axis of the correlation peak of the normal signal deviates from 0, the symmetry axis is used as the observation statistic, that is, the degree of deviation of the symmetry axis from 0 position is used as the observation statistic, and whether the signal is normal or not can be judged according to whether the deviation degree exceeds the subsequent statistic threshold value.
Taking an example of fitting the data of the preprocessed related peak sampling value into a gaussian function by a least square method and taking a symmetric axis of the gaussian function as an observation statistic, the specific process is shown in formulas (3) to (5):
equation (3) is an objective function (gaussian function) fitted at time k based on the preprocessed correlated peak sample values:
wherein, Im,n(k, x) represents a target function, namely a Gaussian function, which is fitted by using the preprocessed related peak sampling value at the moment k; mu.sm,nThe measured value is taken as a symmetry axis, namely the observed statistic; x represents the position of the sample point, e.g., -0.075, -0.05, -0.025, 0, 0.025, 0.05, 0.075, 0.1 in step S1. if the receiver can provide more sample points, x is takenMore in value; σ is the standard deviation.
The least square method is adopted, and the formula (4) expresses the mean square error:
wherein Q represents the mean square error; x is the number ofiRepresents the ith sample point of channel (m, n); i ism,n,iAnd (3) expressing the normalized correlation peak sampling value corresponding to the ith sampling point in the channel (m, n), namely the preprocessed correlation peak sampling value corresponding to the ith sampling point.
Based on least square method, when the mean square error Q is minimum, the corresponding mum,nNamely, the observation statistics of the channel (m, n), the observation statistics of other rest channels are obtained by the same method, namely, a target function with a symmetry axis is set, data fitting is carried out based on the preprocessed related peak sampling values of each channel, the obtained symmetry axis of a fitting curve is the observation statistics of each channel, and the observation statistics are used for monitoring signals subsequently to judge whether the abnormality occurs.
In a specific embodiment, the GNSS signal quality monitoring method further includes:
optimizing the observation statistics based on receiver bias and satellite bias to obtain optimized observation statistics;
grouping the optimized observation statistics based on the satellite elevation intervals, and processing the optimized observation statistics of each elevation interval to obtain a statistic threshold value of each elevation interval;
and comparing the optimized observation statistics with the statistic threshold value of the elevation angle interval corresponding to the observation statistics, and judging the quality of the GNSS signal corresponding to the observation statistics.
Specifically, based on the observation statistics obtained in step S3, the fixed errors of the receiver and the satellite system are a slow-varying but gradual error, which may be caused by the system operating environment. Optimizing observation statistics based on receiver deviation and satellite deviation to obtain optimized observation statistics, wherein the specific process comprises the following steps:
(1) calculate receiver offset, see equation (5):
wherein R ism(k) Representing the deviation of receiver m at time k, N representing the total number of satellites tracked by receiver m, ScRepresenting the constellation of tracked satellites, mum,j(k) Observation statistics for channel (m, j).
(2) Remove the receiver bias and subtract the receiver bias based on the observation statistics as shown in equation (6):
μc1,m,n(k)＝μm,n(k)-Rμm(k) (6)
wherein, muc1,m,n(k) Representing the observation statistics at time k, after receiver bias cancellation for channel (m, n).
(3) Calculate satellite bias, see equation (7):
wherein, S mun(k) Denotes the deviation of the satellite n at time k, M denotes the number of receivers tracking the satellite n, μc1,i,n(k) Representing the observed statistics after receiver bias cancellation for channel (i, n) correspondence.
(4) Remove satellite bias and subtract satellite bias based on the observation statistics after receiver bias cancellation, as shown in equation (8):
μc,m,n＝μc1,m,n(k)-Sμn(k) (8)
wherein, muc,m,nRepresents the observation statistics after the receiver bias and satellite bias are removed, i.e., the optimized observation statistics.
And eliminating receiver deviation and satellite deviation to obtain optimized observation statistics, so that the subsequent judgment result of the signal quality is more accurate.
In a specific embodiment, grouping the observation statistics based on satellite elevation intervals, and processing the observation statistics for each of the elevation intervals to obtain a statistic threshold value for each elevation interval includes:
obtaining a mean value, a standard deviation and an expansion factor of the observation statistics corresponding to each elevation interval based on the observation statistics of each elevation interval;
and obtaining the statistic threshold value of each elevation angle interval by combining the false alarm probability based on the mean value, the standard deviation and the expansion factor of the observation statistic corresponding to each elevation angle interval.
Specifically, after the above steps are completed, observation statistics of each channel between the satellite and the receiver are obtained, and the observation statistics are processed to obtain a statistic threshold value, which includes the following steps:
(1) the satellite elevation angle interval is divided according to the satellite elevation angle, specifically, 10 degrees is generally adopted as one interval to be divided, so as to obtain the satellite elevation angle interval.
(2) According to the satellite elevation angle interval, the observation statistics corresponding to each channel are grouped, and the mean value mu of the observation statistics of each group (namely, each satellite elevation angle interval) is calculatediAnd standard deviation σiWhere i is the ith elevation interval.
(3) Calculating the expansion factor: the probability distribution of observation statistics and the Gaussian distribution of the ith elevation interval are processed simultaneously, so that the Gaussian distribution Gi～(0,fi 2) Just wrap the two sides of the probability distribution of observation statistics in the ith elevation interval, fiIs the dilation factor for that elevation interval.
(4) Calculating a statistic threshold value of each elevation angle interval: determining a mean value mu of observation statistics for each elevation intervaliAnd standard deviation σiAnd a swelling factor fiSetting false alarm probability to obtain fraction bit alpha corresponding to the false alarm probability according to Zi＝μi+α*σi*fiObtaining a statistic threshold value of the ith elevation angle interval, wherein ZiIs the statistic threshold value of the ith elevation angle interval. Specifically, the false alarm probability may be set according to actual conditions, which is not limited in the present application.
In a specific embodiment, comparing the observation statistic with a statistic threshold value of an elevation angle interval corresponding to the observation statistic, and determining the quality of the GNSS signal corresponding to the observation statistic comprises:
when the observation statistic is smaller than a statistic threshold value in the corresponding elevation angle interval, the GNSS signal corresponding to the observation statistic is a normal signal;
and when the observed quantity is larger than or equal to a statistic threshold value in the corresponding elevation angle interval, the corresponding GNSS signal is an abnormal signal.
Specifically, each elevation angle interval has a statistic threshold value, all observation statistics in the elevation angle interval are compared with the corresponding statistic threshold value, and if the observation statistics are smaller than the statistic threshold value, the GNSS signal of the channel corresponding to the observation statistics is a normal signal; and if the observation statistic is larger than the statistic threshold value, the GNSS signal of the channel corresponding to the observation statistic is an abnormal signal.
Based on the method, the observation statistics and the statistic threshold value are updated at each moment, and the signal quality of each channel at each moment can be monitored.
In another aspect, the present application provides a GNSS signal quality monitoring system, including:
the signal receiving module is used for acquiring a related peak sampling value of the GNSS signal sent by the receiver;
the preprocessing module is used for preprocessing the related peak sampling value to obtain a preprocessed related peak sampling value;
the data fitting module is used for setting a target function with a symmetry axis, performing data fitting on the preprocessed related peak sampling value by taking the target function as a fitting target to obtain a related peak curve, and taking the symmetry axis of the related peak curve as observation statistics;
a statistic threshold value obtaining module, configured to group the observation statistic values based on satellite elevation angle intervals, process the observation statistic values of each elevation angle interval, and obtain a statistic threshold value of each elevation angle interval;
and the result analysis module is used for comparing the observation statistic with a statistic threshold value of the elevation angle interval corresponding to the observation statistic, and judging the quality of the GNSS signal corresponding to the observation statistic.
According to the method, the target function is set through the GNSS signal quality monitoring system, the relevant peak sampling value is fitted to obtain the relevant peak curve, the relevant peak sampling value is fully utilized, the symmetric axis of the relevant peak curve is used as observation statistics, the degree of deviation of the GNSS signal from a standard signal (the signal with the symmetric axis being 0) is reflected, and whether the signal is abnormal or not is judged by combining the statistic threshold value, so that the accuracy of GNSS signal quality monitoring is effectively improved, and the requirement of civil aviation is fully met.
In a specific embodiment, the system further comprises an observation statistic optimization module for optimizing the observation statistics based on the receiver bias and the satellite bias to obtain optimized observation statistics;
the statistic threshold value obtaining module is used for grouping the optimized observation statistic values based on satellite elevation angle intervals, processing the optimized observation statistic values of each elevation angle interval and obtaining a statistic threshold value of each elevation angle interval;
and the result analysis module compares the optimized observation statistics with the statistic threshold value of the elevation angle interval corresponding to the optimized observation statistics and judges the quality of the GNSS signal corresponding to the optimized observation statistics.
Specifically, the observation statistic optimization module can optimize the observation statistic through the above formulas (5) to (8), and eliminate the influence of the receiver deviation and the satellite deviation on the observation statistic to obtain the optimized observation statistic.
In a specific embodiment, the preprocessing module includes:
the smoothing module is used for smoothing the correlation peak sampling value to obtain a smoothed correlation peak sampling value;
and the normalization module is used for performing normalization processing on the smoothed correlation peak sampling value to obtain a preprocessed correlation peak sampling value.
Specifically, the preprocessing module may preprocess the correlation peak sampling value by using a formula (1) and a formula (2) to obtain the preprocessed correlation peak sampling value.
In a specific embodiment, the statistic threshold obtaining module includes:
the first calculation module is used for obtaining the mean value, the standard deviation and the expansion factor of the observation statistics corresponding to each elevation angle interval based on the observation statistics of each elevation angle interval;
and the second calculation module is used for obtaining the statistic threshold value of each elevation angle interval by combining the false alarm probability based on the mean value, the standard deviation and the expansion factor of the observation statistic corresponding to each elevation angle interval.
The method embodiment and the system embodiment are realized based on the same principle, the related expenses can be referred to each other, and the same technical effect can be achieved.
Those skilled in the art will appreciate that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program, which is stored in a computer readable storage medium, to instruct related hardware. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (10)
1. A GNSS signal quality monitoring method is characterized by comprising the following steps:
acquiring a related peak sampling value of a GNSS signal sent by a receiver;
preprocessing the relevant peak sampling value to obtain a preprocessed relevant peak sampling value;
setting a target function with a symmetry axis, and performing data fitting on the preprocessed related peak sampling value by taking the target function as a fitting target to obtain a related peak curve, wherein the symmetry axis of the related peak curve is observation statistics;
grouping the observation statistics based on the satellite elevation intervals, and processing the observation statistics of each elevation interval to obtain a statistic threshold value of each elevation interval;
and comparing the observation statistics with a statistic threshold value of an elevation angle interval corresponding to the observation statistics, and judging the quality of the GNSS signal corresponding to the observation statistics.
2. The GNSS signal quality monitoring method of claim 1, further comprising:
optimizing the observation statistics based on receiver bias and satellite bias to obtain optimized observation statistics;
grouping the optimized observation statistics based on the satellite elevation intervals, and processing the optimized observation statistics of each elevation interval to obtain a statistic threshold value of each elevation interval;
and comparing the optimized observation statistics with the statistic threshold value of the elevation angle interval corresponding to the observation statistics, and judging the quality of the GNSS signal corresponding to the observation statistics.
3. The GNSS signal quality monitoring method according to claim 1 or 2, wherein the preprocessing the correlation peak sample value to obtain a preprocessed correlation peak sample value includes:
smoothing the correlation peak sampling value to obtain a smoothed correlation peak sampling value;
and carrying out normalization processing on the smoothed correlation peak sampling value to obtain a preprocessed correlation peak sampling value.
4. The GNSS signal quality monitoring method according to claim 3, wherein the objective function is a Gaussian function or a quadratic function, and the data fitting of the preprocessed correlation peak sampling values with the objective function as a fitting target to obtain a correlation peak curve comprises: and performing data fitting on the preprocessed related peak sampling value by adopting a least square method.
5. The GNSS signal quality monitoring method of claim 4, wherein processing the observation statistics for each of the elevation intervals to obtain a statistic threshold value for each elevation interval comprises:
obtaining a mean value, a standard deviation and an expansion factor of the observation statistics corresponding to each elevation interval based on the observation statistics of each elevation interval;
and obtaining the statistic threshold value of each elevation angle interval by combining the false alarm probability based on the mean value, the standard deviation and the expansion factor of the observation statistic corresponding to each elevation angle interval.
6. The GNSS signal quality monitoring method of claim 5, wherein the comparing the observation statistic with a statistic threshold value of the elevation interval corresponding thereto, and the determining the quality of the GNSS signal corresponding thereto comprises:
when the observation statistic is smaller than a statistic threshold value in the corresponding elevation angle interval, the GNSS signal corresponding to the observation statistic is a normal signal;
and when the observed quantity is larger than or equal to a statistic threshold value in the corresponding elevation angle interval, the corresponding GNSS signal is an abnormal signal.
7. A GNSS signal quality monitoring system, comprising:
the signal receiving module is used for acquiring a related peak sampling value of the GNSS signal sent by the receiver;
the preprocessing module is used for preprocessing the related peak sampling value to obtain a preprocessed related peak sampling value;
the data fitting module is used for setting a target function with a symmetry axis, performing data fitting on the preprocessed related peak sampling value by taking the target function as a fitting target to obtain a related peak curve, and taking the symmetry axis of the related peak curve as observation statistics;
a statistic threshold value obtaining module, configured to group the observation statistic values based on satellite elevation angle intervals, process the observation statistic values of each elevation angle interval, and obtain a statistic threshold value of each elevation angle interval;
and the result analysis module is used for comparing the observation statistic with a statistic threshold value of the elevation angle interval corresponding to the observation statistic, and judging the quality of the GNSS signal corresponding to the observation statistic.
8. The GNSS signal quality monitoring system of claim 7 further comprising an observation statistic optimization module for optimizing the observation statistics based on receiver bias and satellite bias to obtain optimized observation statistics;
the statistic threshold value obtaining module is used for grouping the optimized observation statistic values based on satellite elevation angle intervals, processing the optimized observation statistic values of each elevation angle interval and obtaining a statistic threshold value of each elevation angle interval;
and the result analysis module compares the optimized observation statistics with the statistic threshold value of the elevation angle interval corresponding to the optimized observation statistics and judges the quality of the GNSS signal corresponding to the optimized observation statistics.
9. The GNSS signal quality monitoring system of claim 7 or 8, wherein the preprocessing module comprises:
the smoothing module is used for smoothing the correlation peak sampling value to obtain a smoothed correlation peak sampling value;
and the normalization module is used for performing normalization processing on the smoothed correlation peak sampling value to obtain a preprocessed correlation peak sampling value.
10. The GNSS signal quality monitoring system of claim 9 wherein the statistics threshold acquisition module comprises:
the first calculation module is used for obtaining the mean value, the standard deviation and the expansion factor of the observation statistics corresponding to each elevation angle interval based on the observation statistics of each elevation angle interval;
and the second calculation module is used for obtaining the statistic threshold value of each elevation angle interval by combining the false alarm probability based on the mean value, the standard deviation and the expansion factor of the observation statistic corresponding to each elevation angle interval.
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| CN116626716B (en) * | 2023-07-21 | 2023-09-29 | 齐鲁空天信息研究院 | Beidou signal tracking and monitoring method |
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