CN117331106A - High-precision mobile phone positioning method and system based on speed assistance - Google Patents
High-precision mobile phone positioning method and system based on speed assistance Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/40—Correcting position, velocity or attitude
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/52—Determining velocity
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/025—Services making use of location information using location based information parameters
- H04W4/027—Services making use of location information using location based information parameters using movement velocity, acceleration information
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- Position Fixing By Use Of Radio Waves (AREA)
Abstract
The invention discloses a high-precision mobile phone positioning method and a system based on speed assistance, which are used for obtaining high-precision mobile phone speed by utilizing mobile phone Doppler observation values and phase observation values based on least square iteration solution, accurately estimating errors of pseudo-range observation values among epochs through speed information assistance, and providing information for coarse detection and weight determination of the pseudo-range observation values. The invention can improve the stability of the GNSS data quality control of the mobile phone and the reliability of the weight determination of the observed value in the complex environment, and further improve the GNSS positioning precision of the mobile phone.
Description
Technical Field
The invention belongs to the technical field of global navigation satellite system test application, and particularly relates to a high-precision mobile phone positioning method and system based on speed assistance.
Background
Global satellite navigation systems (GNSS) can implement all-weather positioning, navigation and time service functions on a global scale, and thus are widely used in various industries. Along with the popularization of intelligent terminals, the position service greatly promotes the development of industries such as information transmission, traffic logistics, engineering construction and the like, and users are more and more dependent on the position service of the intelligent mobile phone and simultaneously put forward higher requirements on the intelligent mobile phone, so that the GNSS high-precision positioning of the Android intelligent mobile phone becomes a current research hotspot.
GNSS positioning mainly comprises a function model and a random model, wherein the function model describes mathematical relation between observed quantity and unknown parameters, the random model reflects statistical characteristics of the observed quantity, and the positioning performance can be more stable by selecting a proper weighting mode according to the statistical characteristics of the observed quantity. The functional model of the mobile GNSS positioning is the same as that of the high-precision equipment, and the random model mainly depends on the observation quality of the data. Because mobile GNSS data is susceptible to multipath and non-line-of-sight signals in a complex environment, a random model of mobile GNSS positioning can greatly influence mobile positioning accuracy compared with high-accuracy equipment. The mobile GNSS positioning usually determines a random model according to the carrier-to-noise ratio, and can improve positioning performance compared with a random model of a height angle. However, the random model determined according to the carrier-to-noise ratio has a certain relation with the model of the mobile phone, the observation environment and the like, and is difficult to be applied to all mobile phones and practical environments. The smart phone based on the phase observation value can realize high-precision speed measurement, and the speed measurement precision (usually decimeter/second or centimeter/second) is far higher than the precision (usually several meters to tens of meters) of the pseudo-range observation value of the mobile phone GNSS, so that the smart phone can be used for assisting in the data quality control of the pseudo-range observation value and determining a random model of the mobile phone GNSS positioning.
Disclosure of Invention
Aiming at the problems that the GNSS data of the mobile phone is easily affected by multipath and the like in urban environment, so that the observation quality is reduced and the GNSS positioning accuracy is affected, the invention fully utilizes the characteristic of high GNSS speed measurement accuracy of the mobile phone, provides a high-accuracy mobile phone positioning method and system based on speed assistance, can improve the stability of the GNSS data quality control of the mobile phone and the reliability of the fixed weight of the observation value in urban complex environment, and further improves the GNSS positioning accuracy of the mobile phone.
The invention provides a high-precision mobile phone positioning method based on speed assistance, which comprises the following steps:
step 1, calculating satellite positions and speeds at corresponding moments by using nearest broadcast ephemeris according to GNSS observation value time of a mobile phone;
step 2, iteratively solving the speed of the mobile phone by utilizing a least square algorithm according to the position, the speed and the Doppler observation value of the satellite and based on a Doppler observation equation of the satellite to obtain a Doppler velocity measurement result;
step 3, performing weight reduction processing on the phase observation value with cycle slip according to the Doppler velocity measurement result obtained in the step 2, the satellite positions of the two epochs and the position of the mobile phone;
step 4, carrying out iterative computation by using the Doppler velocity measurement result in the step 2 and the phase observation value after the weight reduction processing in the step 3 to obtain the accurate mobile phone movement speed;
step 5, calculating an error value of the GNSS pseudo-range observation value among epochs by using the accurate mobile phone movement speed obtained in the step 4;
step 6, determining weights of pseudo-range observation values of different satellites according to the pseudo-range errors among each satellite epoch obtained in the step 5, and determining a random model;
and 7, according to the random model of the mobile phone GNSS positioning determined in the step 6, carrying out mobile phone GNSS positioning by utilizing least square, and outputting the GNSS positioning result of the mobile phone.
Further, it is assumed in the step 2 that the operation speed is v s The satellite transmitting frequency is f, the corresponding wavelength is lambda carrier signal, the running speed of the mobile phone is v, and the Doppler frequency shift of the satellite carrier signal received by the mobile phone is:
wherein f d Indicating Doppler shift of satellite carrier signal received by mobile phone, l s Representing the unit observation vector of the satellite at the handset, calculated from the satellite position and the handset position,indicating the approach distance of the mobile phone to the satelliteRate of change of separation.
Considering the influence of frequency deviation and noise of satellites and mobile phone clocks, a GNSS Doppler observation equation is expressed as follows:
-λf d ＝(v s -v)·l s +f r -f s +ε s (2)
where λ is the wavelength of the carrier signal, f d Indicating Doppler shift, v of satellite carrier signal received by mobile phone s The running speed of the satellite, v is the running speed of the mobile phone, l s Representing unit observation vector of satellite at mobile phone, calculating by satellite position and mobile phone position, f r F is the clock frequency deviation of the mobile phone s For satellite clock frequency drift, ε s Is Doppler observed noise.
After the formula (2) is finished, the following steps are obtained:
v·l s -f r ＝λf d +v s ·l s -f s +ε s (3)
in the formula (3), the parameters to be estimated include the mobile phone speed v and the mobile phone clock frequency deviation f r The Doppler observation values of a plurality of satellites are obtained through least square iteration solution, and the Doppler observation values of the satellites used for least square solution are equal in weight.
Mobile phone speed v and mobile phone clock frequency deviation f r The initial values of (2) are all set to be 0, and new mobile phone speed v and mobile phone clock frequency deviation f are obtained through least square calculation by utilizing Doppler observed values of a plurality of satellites based on formula (3) r The solved mobile phone speed v and mobile phone clock frequency deviation f r Substituting the Doppler observed value of each satellite into the following formula to obtain Doppler speed measurement residual error l of each satellite, namely:
l＝v·l s -f r -λf d -v s ·l s +f s -ε s (4)
in the iteration process, satellite Doppler observation values with rough differences are removed by using a median method, and first, standard deviation std of a plurality of satellite Doppler speed measurement residuals is calculated i Then Doppler speed measurement of each satelliteThe residual errors are sequenced from small to large to obtain a median l M Comparing the difference between the Doppler speed measurement residual error and the median of the Doppler speed measurement residual error of each satellite with N 1 The size of the double standard deviation, if (l i -l M )＞N 1 std i And the Doppler observed value of the satellite i contains a rough difference, and the Doppler observed value is removed from the iterative calculation which does not participate in the next iteration calculation. The newly calculated mobile phone speed v and mobile phone clock frequency deviation f r Substituting into formula (3) to perform iterative calculation until the difference between the two adjacent calculation speeds is smaller than the set threshold gamma 1 And (5) stopping iteration, and taking the last least square calculation to obtain the mobile phone speed v as a final Doppler speed measurement result.
In the step 3, the phase observations of the two epochs t and t-1 are differentiated to obtain:
λ·ΔΦ＝Δρ+c·(Δt r -Δt s )+Δδ trop -Δδ iono (5)
where λ is the wavelength, ΔΦ is the difference between two epoch phase observations, Δρ is the difference between the geometric distances of the two epoch handsets to the satellite, c is the speed of light, Δt r Representing the handset clock difference between two epochs, Δt s Representing satellite clock difference between two epochs, calculated from broadcast ephemeris, delta trop And delta iono Tropospheric and ionospheric errors, respectively.
When the sampling rate is high, the ionospheric delay and the tropospheric delay change are negligible, and the expression (5) is expressed as:
λΔΦ+cΔt s ＝Δρ+cΔt r (6)
the difference Δρ in geometric distance between t and t-1 epochs is expressed as:
Δρ＝e(t)(r s (t)-r u (t))-e(t-1)(r s (t-1)-r u (t-1)) (7)
wherein e is the unit vector of the mobile phone and the satellite, r s 、r u The satellite position and the mobile phone position vector are respectively expressed as the following formula:
r u (t)＝r u (t-1)+v·Δt (8)
where Δt is the time variation between epochs.
Combining equations (6) - (8) and letting Δd=e (t). R s (t)-e(t-1)•r s (t-1)，Δg＝[e(t)-e(t-1)]·r u (t-1), to obtain:
λΔΦ+cΔt s -Δd+Δg＝-e(t)·v·Δt+c·Δt r (9)
in equation (9), the unknown parameters include handset speed v and handset clock difference Δt between epochs r The phase observation value difference values among the plurality of satellite epochs are obtained through least square iteration solution.
Handset clock difference delta t between handset speed v and epoch r The initial values of (2) are all set to 0, and new mobile phone speed v and mobile phone clock difference delta t between epochs are obtained by least square calculation by utilizing the phase observation value difference value among multiple satellite epochs based on the formula (9) r Solving the mobile phone speed v and the mobile phone clock difference delta t between epochs r Substituting the phase observation value difference value among the satellites into the following value to obtain the phase observation value velocity measurement residual error l of each satellite * The method comprises the following steps:
l * ＝λΔΦ+cΔt s -Δd+Δg+e(t)·v·Δt-c·Δt r (10)
in the iteration process, satellite phase observation values with coarse differences are removed by using a median method, and first, standard deviations of speed measurement residuals of a plurality of satellite phase observation values are calculatedThen sequencing the phase observation value speed measurement residual errors of all satellites from small to large to obtain a median +.>Comparing the difference between the median of each satellite phase observation value velocity measurement residual and the phase observation value velocity measurement residual with N 2 The size of the multiple standard deviation, if +.>The phase observations of satellite i contain coarse differences which are rejected as not participating in the next iterative computation. The new calculated mobile phone speed v and the new calculated mobile phone speed v are calculatedMobile phone clock difference delta t between calendar elements r Substituting into formula (9) to perform iterative calculation until the difference between the two adjacent calculation speeds is smaller than the set threshold gamma 2 And (5) stopping iteration, and taking the last least square calculation to obtain a speed measurement result with the mobile phone speed v as the final phase observation value.
Moreover, the difference between the pseudoranges in step 5 is expressed as:
ΔP＝Δρ+c·(Δt r -Δt s )+Δδ trop +Δδ iono (11)
wherein ΔP is the difference between the pseudoranges, Δρ is the difference between the geometric distances from the mobile phone to the satellite, c is the speed of light, Δt r Representing the handset clock difference between two epochs, Δt s Representing satellite clock difference, delta, between two epochs trop And delta iono Tropospheric and ionospheric errors, respectively.
When the sampling rate is high, ionospheric delay and tropospheric delay changes are negligible, equations (7) and (8) are substituted into equation (11), and Δd=e (t) ·r s (t)-e(t-1)•r s (t-1)，Δg＝[e(t)-e(t-1)]•r u (t-1) obtaining the pseudo-range error delta between epochs P The expression is:
δ P ＝ΔP-Δd+Δg+e(t)·v·Δt-c·Δt r +c·Δt s (12)
wherein ΔP is the difference between the epochs, e is the unit vector of the mobile phone and the satellite, v is the mobile phone speed, Δt is the time variation between epochs, c is the light speed, Δt r For handset clock difference between epochs, Δt s Is satellite clock error, is calculated by broadcast ephemeris, r s 、r u The satellite position and the mobile phone position vector are respectively, and t-1 represent two epochs.
And (4) obtaining the mobile phone speed v and the mobile phone clock difference delta t between epochs in the step (4) r Substituting the pseudo-range error into the formula (12) to obtain pseudo-range errors among the epochs.
Furthermore, in the step 6, the inter-epoch error delta is determined according to the satellite pseudo-range P And (3) weighting pseudo-range observation values of different satellites, and determining a random model thereof, wherein the specific calculation mode is as follows:
where weight represents the weight of the pseudorange, η 1 And eta 2 For the set threshold value, a and b are weighting coefficients of the pseudo-range observed value, and the weighting coefficients take on values according to eta 1 And eta 2 To ensure that the weighting function is a continuous piecewise function.
When delta P ＞η 1 When the pseudo range is judged to be rough, the weight of the pseudo range is assigned to be 0; when delta P ＜η 2 When it is assigned a weight of 1, when η is 2 ≤δ P ≤η 1 And calculating the weight of the pseudo range according to the residual error size, thereby determining the random model.
The invention also provides a high-precision mobile phone positioning system based on the speed assistance, which is used for realizing the high-precision mobile phone positioning method based on the speed assistance.
And, including processor and memory, the memory is used for storing the program instruction, and the processor is used for calling the program instruction in the memory and carrying out a high accuracy cell-phone positioning method based on speed assistance as above-mentioned.
Or comprises a readable storage medium, wherein the readable storage medium is stored with a computer program, and the computer program realizes the high-precision mobile phone positioning method based on speed assistance when being executed.
Compared with the prior art, the invention has the following advantages:
1) According to the invention, the mobile phone Doppler observation value and the phase observation value are utilized to calculate the mobile phone speed with high precision, the precise pseudo-range inter-epoch error is obtained based on speed assistance, and the coarse difference detection success rate and the reliability of the fixed weight of the mobile phone GNSS pseudo-range observation value are improved, so that the mobile phone GNSS positioning precision in a complex scene is effectively improved.
2) The mobile phone GNSS data quality influences the mobile phone positioning accuracy, the traditional data quality control method is related to the testing environment, the mobile phone model and the like, and is difficult to be suitable for mobile phone positioning of different types and different scenes.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a high-precision mobile phone positioning method based on speed assistance.
Fig. 2 is a diagram showing the improvement of mobile phone positioning accuracy obtained by using the method of the present invention and the carrier-to-noise ratio weighting method.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings and examples of the present invention, and it is apparent that the described examples are some, but not all, examples of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in fig. 1, the embodiment of the invention provides a high-precision mobile phone positioning method based on speed assistance, which comprises the following steps:
and step 1, calculating satellite positions and speeds at corresponding moments by using the nearest broadcast ephemeris according to GNSS observation value time of the mobile phone.
And 2, iteratively solving the speed of the mobile phone by utilizing a least square algorithm according to the position, the speed and the Doppler observation value of the satellite and based on a Doppler observation equation of the satellite to obtain a Doppler velocity measurement result.
Let the running speed be v s Carrier signal with a satellite transmission frequency f and a corresponding wavelength lambdaThe running speed of the mobile phone is v, and the Doppler frequency shift of the satellite carrier signal received by the mobile phone is:
wherein f d Indicating Doppler shift of satellite carrier signal received by mobile phone, l s Representing the unit observation vector of the satellite at the handset, calculated from the satellite position and the handset position,and the change rate of the distance of the mobile phone approaching the satellite is represented.
Considering the influence of satellite and handset clock frequency bias and noise, the GNSS doppler observation equation can be expressed as:
-λf d ＝(v s -v)·l s +f r -f s +ε s (2)
where λ is the wavelength of the carrier signal, f d Indicating Doppler shift, v of satellite carrier signal received by mobile phone s The running speed of the satellite, v is the running speed of the mobile phone, l s Representing unit observation vector of satellite at mobile phone, calculating by satellite position and mobile phone position, f r F is the clock frequency deviation of the mobile phone s For satellite clock frequency drift, ε s Is Doppler observed noise.
After the formula (2) is finished, the following steps are obtained:
v·l s -f r ＝λf d +v s ·l s -f s +ε s (3)
in the formula (3), the parameters to be estimated include the mobile phone speed v and the mobile phone clock frequency deviation f r The mobile phone speed v and the mobile phone clock frequency deviation f can be obtained by the Doppler observation values of a plurality of satellites through least square iteration solution r (the Doppler observations for each satellite used in the least squares solution are weighted equally here). Mobile phone speed v and mobile phone clock frequency deviation f r The initial values of (2) are all set to 0 by least squareCalculating to obtain new mobile phone speed v and mobile phone clock frequency deviation f r The solved mobile phone speed v and mobile phone clock frequency deviation f r Substituting the Doppler observed value of each satellite into the following formula to obtain Doppler speed measurement residual error l of each satellite, namely:
l＝v·l s -f r -λf d -v s ·l s +f s -ε s (4)
in the iteration process, satellite Doppler observation values with rough differences are removed by using a median method, and first, standard deviation std of a plurality of satellite Doppler speed measurement residuals is calculated i Then the Doppler speed measurement residual errors of all satellites are sequenced from small to large to obtain a median l M Comparing the difference between the satellite Doppler velocity measurement residual errors and the median of the Doppler velocity measurement residual errors with the size of N1 times of standard deviation, if (l) i -l M )＞N 1 std i The Doppler observed value of satellite i contains coarse differences, which are removed from the iterative calculation of the next time, N in the embodiment 1 Taking 3.
The newly calculated mobile phone speed v and mobile phone clock frequency deviation f r Substituting into formula (3) to perform iterative calculation until the difference between the two adjacent calculation speeds is smaller than the set threshold gamma 1 (threshold value gamma in this embodiment) 1 Taking 0.01 m/s), stopping iteration, and taking the last least square calculation to obtain the mobile phone speed v as a final Doppler velocity measurement result.
And step 3, preprocessing the phase observation value according to the Doppler velocity measurement result obtained in the step 2, the satellite positions of the two epochs and the position of the mobile phone.
And (3) carrying out weight reduction treatment on the phase observation value with cycle slip according to the Doppler speed measurement result obtained in the step (2), the satellite positions of the two epochs and the position of the mobile phone, wherein the weight is used for giving weight to the phase observation value when the phase observation value is solved for speed measurement in the subsequent step (4) least square iteration.
And step 4, performing iterative computation by using the Doppler velocity measurement result in the step 2 and the phase observation value preprocessed in the step 3 to obtain the accurate mobile phone movement speed.
And differentiating the phase observation values of the two epochs of t and t-1 to obtain:
λ·ΔΦ＝Δρ+c·(Δt r -Δt s )+Δδ trop -Δδ iono (5)
where λ is the wavelength, ΔΦ is the difference between two epoch phase observations, Δρ is the difference between the geometric distances of the two epoch handsets to the satellite, c is the speed of light, Δt r Representing the handset clock difference between two epochs, Δt s The satellite clock difference between two epochs can be calculated from the broadcast ephemeris, delta trop And delta iono Tropospheric and ionospheric errors, respectively.
When the sampling rate is high, the ionospheric delay and the tropospheric delay change are negligible, and then equation (5) can be expressed as:
λΔΦ+cΔt s ＝Δρ+cΔt r (6)
the difference in geometric distance between t and t-1 epochs can be expressed as:
Δρ＝e(t)(r s (t)-r u (t))-e(t-1)(r s (t-1)-r u (t-1)) (7)
wherein e is the unit vector of the mobile phone and the satellite, r s 、r u The satellite position and the mobile phone position vector are respectively, and the mobile phone position vector between two epochs can be expressed as the following formula:
r u (t)＝r u (t-1)+v·Δt (8)
where Δt is the time variation between epochs.
Formulae (6) - (8) are combined and for ease of representation, let Δd=e (t) ·r s (t)-e(t-1)·r s (t-1)，Δg＝[e(t)-e(t-1)]·r u (t-1), then it is possible to obtain:
λΔΦ+cΔt s -Δd+Δg＝-e(t)·v·Δt+c·Δt r (9)
in equation (9), the unknown parameters include handset speed v and handset clock difference Δt between epochs r The difference value of the phase observation values among the multiple satellite epochs is solved through least square iteration, so that the mobile phone speed v and the mobile phone clock difference delta t among the epochs can be obtained r . Handset clock difference delta t between handset speed v and epoch r The initial values of (a) are all set to 0, and a new mobile phone speed v and a mobile phone clock difference delta t between epochs are obtained through least square calculation r Solving the mobile phone speed v and the mobile phone clock difference delta t between epochs r Substituting the phase observation value difference value among the satellites into the following value to obtain the phase observation value velocity measurement residual error l of each satellite * The method comprises the following steps:
l * ＝λΔΦ+cΔt s -Δd+Δg+e(t)·v·Δt-c·Δt r (10)
in the iteration process, satellite phase observation values with coarse differences are removed by using a median method, and first, standard deviations of speed measurement residuals of a plurality of satellite phase observation values are calculatedThen sequencing the phase observation value speed measurement residual errors of all satellites from small to large to obtain a median +.>Comparing the difference between the median of each satellite phase observation value velocity measurement residual and the phase observation value velocity measurement residual with N 2 The size of the multiple standard deviation, if +.>The phase observation value of satellite i contains a coarse difference, which is removed from the next iteration calculation, N in this embodiment 2 Taking 3.
The newly calculated mobile phone speed v and the mobile phone clock difference delta t between epochs are calculated r Substituting into formula (9) to perform iterative calculation until the difference between the two adjacent calculation speeds is smaller than the set threshold gamma 2 (threshold value gamma in this embodiment) 2 Taking 0.01 m/s), stopping iteration, and taking the last least square calculation to obtain the speed v of the mobile phone as the final speed measurement result of the phase observation value.
And 5, calculating the error value of the GNSS pseudo-range observation value among epochs by using the phase observation value velocity measurement information obtained in the step 4.
The difference between the pseudoranges over the epochs can be expressed as:
ΔP＝Δρ+c·(Δt r -Δt s )+Δδ trop +Δδ iono (11)
wherein ΔP is the difference between the pseudoranges, Δρ is the difference between the geometric distances from the mobile phone to the satellite, c is the speed of light, Δt r Representing the handset clock difference between two epochs, Δt s Representing satellite clock difference, delta, between two epochs trop And delta iono Tropospheric and ionospheric errors, respectively.
When the sampling rate is high, the ionospheric delay and the tropospheric delay change are negligible, the formulas (7) and (8) are substituted into the formula (11), and Δd=e (t). R s (t)-e(t-1)•r s (t-1)，Δg＝[e(t)-e(t-1)]•r u (t-1) obtaining the pseudo-range error delta between epochs P The method comprises the following steps:
δ P ＝ΔP-Δd+Δg+e(t)·v·Δt-c·Δt r +c·Δt s (12)
wherein ΔP is the difference between the epochs, e is the unit vector of the mobile phone and the satellite, v is the mobile phone speed, Δt is the time variation between epochs, c is the light speed, Δt r For handset clock difference between epochs, Δt s Is satellite clock error, is calculated by broadcast ephemeris, r s 、r u The satellite position and the mobile phone position vector are respectively, and t-1 represent two epochs.
And (4) obtaining the mobile phone speed v and the mobile phone clock difference delta t between epochs in the step (4) r And substituting the pseudo-range error into the formula (12) to obtain pseudo-range errors among the epochs.
And 6, determining weights of pseudo-range observation values of different satellites according to the pseudo-range errors among each satellite epoch obtained in the step 5, and determining a random model.
The error among the satellite pseudo-range epochs obtained in the step 5 can reflect the precision of the pseudo-range observation value, and the random model determined according to the error fixed weight can better reflect the mobile GNSS data quality, so that the mobile GNSS positioning precision is improved. According to the inter-epoch error delta of satellite pseudo-range P And (3) weighting pseudo-range observation values of different satellites, and determining a random model thereof, wherein the specific calculation mode is as follows:
where weight represents the weight of the pseudorange, η 1 And eta 2 For the set threshold value, a and b are weighting coefficients of the pseudo-range observed value, and the weighting coefficients take on values according to eta 1 And eta 2 Determining to ensure that the weighting function is a continuous piecewise function, η in this embodiment 1 And eta 2 The values of (a) are set to 50 and 3, respectively, thereby determining a asb is->
When delta P >η 1 When the pseudo range is judged to be rough, the weight of the pseudo range is assigned to be 0; when delta P <η 2 When it is assigned a weight of 1, when η is 2 ≤δ P ≤η 1 And calculating the weight of the pseudo range according to the residual error size, thereby determining the random model.
And 7, according to the random model of the mobile phone GNSS positioning determined in the step 6, carrying out mobile phone GNSS positioning by utilizing least square, and outputting the GNSS positioning result of the mobile phone.
Fig. 2 shows the positioning accuracy improvement experimental result of 148 groups of mobile phones based on the method provided by the invention. As can be seen from fig. 2, compared with the carrier-to-noise ratio weighting method, the random model obtained by the weighting method of the present invention can maximally improve the positioning accuracy of the mobile phone GNSS by 4.6 meters, and the average positioning accuracy is improved by about 20%.
Example 2
Based on the same inventive concept, the invention also provides a high-precision mobile phone positioning system based on speed assistance, which comprises a processor and a memory, wherein the memory is used for storing program instructions, and the processor is used for calling the program instructions in the memory to execute the high-precision mobile phone positioning method based on speed assistance.
Example 3
Based on the same inventive concept, the invention also provides a high-precision mobile phone positioning system based on speed assistance, which comprises a readable storage medium, wherein the readable storage medium is stored with a computer program, and the high-precision mobile phone positioning method based on speed assistance is realized when the computer program is executed.
In particular, the method according to the technical solution of the present invention may be implemented by those skilled in the art using computer software technology to implement an automatic operation flow, and a system apparatus for implementing the method, such as a computer readable storage medium storing a corresponding computer program according to the technical solution of the present invention, and a computer device including the operation of the corresponding computer program, should also fall within the protection scope of the present invention.
The specific embodiments described herein are offered by way of example only to illustrate the spirit of the invention. Those skilled in the art may make various modifications or additions to the described embodiments or substitutions thereof without departing from the spirit of the invention or exceeding the scope of the invention as defined in the accompanying claims.
Claims (9)
1. The high-precision mobile phone positioning method based on speed assistance is characterized by comprising the following steps of:
step 1, calculating satellite positions and speeds at corresponding moments by using nearest broadcast ephemeris according to GNSS observation value time of a mobile phone;
step 2, iteratively solving the speed of the mobile phone by utilizing a least square algorithm according to the position, the speed and the Doppler observation value of the satellite and based on a Doppler observation equation of the satellite to obtain a Doppler velocity measurement result;
step 3, performing weight reduction processing on the phase observation value with cycle slip according to the Doppler velocity measurement result obtained in the step 2, the satellite positions of the two epochs and the position of the mobile phone;
step 4, carrying out iterative computation by using the Doppler velocity measurement result in the step 2 and the phase observation value after the weight reduction processing in the step 3 to obtain the accurate mobile phone movement speed;
step 5, calculating an error value of the GNSS pseudo-range observation value among epochs by using the accurate mobile phone movement speed obtained in the step 4;
step 6, determining weights of pseudo-range observation values of different satellites according to the pseudo-range errors among each satellite epoch obtained in the step 5, and determining a random model;
and 7, according to the random model of the mobile phone GNSS positioning determined in the step 6, carrying out mobile phone GNSS positioning by utilizing least square, and outputting the GNSS positioning result of the mobile phone.
2. The high-precision mobile phone positioning method based on speed assistance as claimed in claim 1, wherein the method comprises the following steps: step 2 assumes an operating speed v s The satellite transmitting frequency is f, the corresponding wavelength is lambda carrier signal, the running speed of the mobile phone is v, and the Doppler frequency shift of the satellite carrier signal received by the mobile phone is:
wherein f d Indicating Doppler shift of satellite carrier signal received by mobile phone, l s Representing the unit observation vector of the satellite at the handset, calculated from the satellite position and the handset position,the change rate of the distance of the mobile phone approaching the satellite is represented;
considering the influence of frequency deviation and noise of satellites and mobile phone clocks, a GNSS Doppler observation equation is expressed as follows:
-λf d ＝(v s -v)·l s +f r -f s +ε s (2)
where λ is the wavelength of the carrier signal, f d Indicating Doppler shift, v of satellite carrier signal received by mobile phone s The running speed of the satellite, v is the running speed of the mobile phone, l s Representing unit observation vector of satellite at mobile phone, calculating by satellite position and mobile phone position, f r F is the clock frequency deviation of the mobile phone s For satellite clock frequency drift, ε s For Doppler observationNoise;
after the formula (2) is finished, the following steps are obtained:
v·l s -f r ＝λf d +v s ·l s -f s +ε s (3)
in the formula (3), the parameters to be estimated include the mobile phone speed v and the mobile phone clock frequency deviation f r The Doppler observation values of a plurality of satellites are obtained through least square iteration solution, and the Doppler observation values of the satellites used for least square solution are equal in weight.
3. The high-precision mobile phone positioning method based on speed assistance as claimed in claim 2, wherein the method comprises the following steps: the specific operation of iterative solution in the step 2 is as follows: mobile phone speed v and mobile phone clock frequency deviation f r The initial values of (2) are all set to be 0, and new mobile phone speed v and mobile phone clock frequency deviation f are obtained through least square calculation by utilizing Doppler observed values of a plurality of satellites based on formula (3) r The solved mobile phone speed v and mobile phone clock frequency deviation f r Substituting the Doppler observed value of each satellite into the following formula to obtain Doppler speed measurement residual error l of each satellite, namely:
l＝v·l s -f r -λf d -v s ·l s +f s -ε s (4)
in the iteration process, satellite Doppler observation values with rough differences are removed by using a median method, and first, standard deviation std of a plurality of satellite Doppler speed measurement residuals is calculated i Then the Doppler speed measurement residual errors of all satellites are sequenced from small to large to obtain a median l M Comparing the difference between the Doppler speed measurement residual error and the median of the Doppler speed measurement residual error of each satellite with N 1 The size of the double standard deviation, if (l i -l M )＞N 1 std i The Doppler observed value of the satellite i contains coarse differences, and the Doppler observed value is removed from the satellite i and does not participate in the next iterative computation; the newly calculated mobile phone speed v and mobile phone clock frequency deviation f r Substituting into formula (3) to perform iterative calculation until the difference between the two adjacent calculation speeds is smaller than the set threshold gamma 1 Stopping iteration and taking the lastAnd obtaining the mobile phone speed v as a final Doppler speed measurement result by the secondary least square calculation.
4. The high-precision mobile phone positioning method based on speed assistance as claimed in claim 1, wherein the method comprises the following steps: in the step 4, the phase observation values of the two epochs of t and t-1 are differentiated to obtain:
λ·ΔΦ＝Δρ+c·(Δt r -Δt s )+Δδ trop -Δδ iono (5)
where λ is the wavelength, ΔΦ is the difference between two epoch phase observations, Δρ is the difference between the geometric distances of the two epoch handsets to the satellite, c is the speed of light, Δt r Representing the handset clock difference between two epochs, Δt s Representing satellite clock difference between two epochs, calculated from broadcast ephemeris, delta trop And delta iono Troposphere and ionosphere errors, respectively;
when the sampling rate is high, the ionospheric delay and the tropospheric delay change are negligible, and the expression (5) is expressed as:
λΔΦ+cΔt s ＝Δρ+cΔt r (6)
the difference Δρ in geometric distance between t and t-1 epochs is expressed as:
Δρ＝e(t)(r s (t)-r u (t))-e(t-1)(r s (t-1)-r u (t-1)) (7)
wherein e is the unit vector of the mobile phone and the satellite, r s 、r u The satellite position and the mobile phone position vector are respectively expressed as the following formula:
r u (t)＝r u (t-1)+v·Δt (8)
wherein Δt is the time variation between epochs;
combining equations (6) - (8) and letting Δd=e (t). R s (t)-e(t-1)•r s (t-1)，Δg＝[e(t)-e(t-1)]·r u (t-1), to obtain:
λΔΦ+cΔt s -Δd+Δg＝-e(t)·v·Δt+c·Δt r (9)
in equation (9), the unknown parameters include handset speed v and handset clock bias between epochsΔt r The phase observation value difference values among the plurality of satellite epochs are obtained through least square iteration solution.
5. The high-precision mobile phone positioning method based on speed assistance as claimed in claim 4, wherein the method comprises the following steps: the specific operation of iterative solution in the step 4 is as follows: handset clock difference delta t between handset speed v and epoch r The initial values of (2) are all set to 0, and new mobile phone speed v and mobile phone clock difference delta t between epochs are obtained by least square calculation by utilizing the phase observation value difference value among multiple satellite epochs based on the formula (9) r Solving the mobile phone speed v and the mobile phone clock difference delta t between epochs r Substituting the phase observation value difference value among the satellites into the following value to obtain the phase observation value velocity measurement residual error l of each satellite * The method comprises the following steps:
l * ＝λΔΦ+cΔt s -Δd+Δg+e(t)·v·Δt-c·Δt r (10)
in the iteration process, satellite phase observation values with coarse differences are removed by using a median method, and first, standard deviations of speed measurement residuals of a plurality of satellite phase observation values are calculatedThen sequencing the phase observation value speed measurement residual errors of all satellites from small to large to obtain a median +.>Comparing the difference between the median of each satellite phase observation value velocity measurement residual and the phase observation value velocity measurement residual with N 2 The size of the multiple standard deviation, if +.>The phase observation value of the satellite i contains coarse differences, and the satellite i is removed from the iteration calculation which does not participate in the next time; the newly calculated mobile phone speed v and the mobile phone clock difference delta t between epochs are calculated r Substituting into formula (9) to perform iterative calculation until the difference between the two adjacent calculation speeds is smaller than the set threshold gamma 2 Stopping iteration, and obtaining the final least square calculationThe mobile phone speed v is the final speed measurement result of the phase observation value.
6. The high-precision mobile phone positioning method based on speed assistance as claimed in claim 4, wherein the method comprises the following steps: the difference between the pseudoranges in step 5 is expressed as:
ΔP＝Δρ+c·(Δt r -Δt s )+Δδ trop +Δδ iono (11)
wherein ΔP is the difference between the pseudoranges, Δρ is the difference between the geometric distances from the mobile phone to the satellite, c is the speed of light, Δt r Representing the handset clock difference between two epochs, Δt s Representing satellite clock difference, delta, between two epochs trop And delta iono Troposphere and ionosphere errors, respectively;
when the sampling rate is high, ionospheric delay and tropospheric delay changes are negligible, equations (7) and (8) are substituted into equation (11), and Δd=e (t) ·r s (t)-e(t-1)·r s (t-1)，Δg＝[e(t)-e(t-1)]•r u (t-1) obtaining the pseudo-range error delta between epochs P The expression is:
δ P ＝ΔP-Δd+Δg+e(t)·v·Δt-c·Δt r +c·Δt s (12)
wherein ΔP is the difference between the epochs, e is the unit vector of the mobile phone and the satellite, v is the mobile phone speed, Δt is the time variation between epochs, c is the light speed, Δt r For handset clock difference between epochs, Δt s Is satellite clock error, is calculated by broadcast ephemeris, r s 、r u The satellite position and the mobile phone position vector are respectively, and t-1 represent two epochs;
and (4) obtaining the mobile phone speed v and the mobile phone clock difference delta t between epochs in the step (4) r Substituting the pseudo-range error into the formula (12) to obtain pseudo-range errors among the epochs.
7. The high-precision mobile phone positioning method based on speed assistance as claimed in claim 1, wherein the method comprises the following steps: in step 6, according to the inter-epoch error delta of the satellite pseudo-range P The pseudo-range observation values of different satellites are weighted, and the randomness of the pseudo-range observation values is determinedThe model is specifically calculated as follows:
where weight represents the weight of the pseudorange, η 1 And eta 2 For the set threshold value, a and b are weighting coefficients of the pseudo-range observed value, and the weighting coefficients take on values according to eta 1 And eta 2 Determining to ensure that the weighting function is a continuous piecewise function;
when delta P ＞η 1 When the pseudo range is judged to be rough, the weight of the pseudo range is assigned to be 0; when delta P ＜η 2 When it is assigned a weight of 1, when η is 2 ≤δ P ≤η 1 And calculating the weight of the pseudo range according to the residual error size, thereby determining the random model.
8. A speed-assisted high-precision mobile phone positioning system, comprising a processor and a memory, wherein the memory is used for storing program instructions, and the processor is used for calling the program instructions in the memory to execute the speed-assisted high-precision mobile phone positioning method according to any one of claims 1-7.
9. A high-precision mobile phone positioning system based on speed assistance, characterized by comprising a readable storage medium, wherein a computer program is stored on the readable storage medium, and the computer program realizes the high-precision mobile phone positioning method based on speed assistance according to any one of claims 1-7 when executed.
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