CN109699007B - Indoor and outdoor seamless gradual change navigation transition method - Google Patents

Indoor and outdoor seamless gradual change navigation transition method Download PDF

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CN109699007B
CN109699007B CN201811644756.4A CN201811644756A CN109699007B CN 109699007 B CN109699007 B CN 109699007B CN 201811644756 A CN201811644756 A CN 201811644756A CN 109699007 B CN109699007 B CN 109699007B
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state
value
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navigation
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施浒立
李芳�
庞鹏翔
程涛
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Suzhou Diehui Intelligent Technology Co.,Ltd.
Suzhou Innovation Research Institute of Beijing University of Aeronautics and Astronautics
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Suzhou Innovation Research Institute Of Beijing University Of Aeronautics And Astronautics
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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
    • H04W4/024—Guidance services
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/16—Performing reselection for specific purposes
    • H04W36/18—Performing reselection for specific purposes for allowing seamless reselection, e.g. soft reselection
    • 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
    • H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/33—Services specially adapted for particular environments, situations or purposes for indoor environments, e.g. buildings
    • 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
    • H04W64/003—Locating users or terminals or network equipment for network management purposes, e.g. mobility management locating network equipment

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Abstract

The invention relates to the field of navigation positioning, in particular to an indoor and outdoor seamless gradual-change navigation transition method, which comprises the following steps: step 1, constructing a coordinate reference frame; and 2, performing indoor and outdoor seamless gradual change navigation transition. The indoor and outdoor seamless gradual change navigation transition method does not adopt switching at a certain point, but gradually changes in a section of area, and can realize smooth transition of indoor and outdoor navigation positioning, so that the position track has no break point and is continuous and smooth; by adopting the same resolving method, the resolving problem of the seamless navigation and positioning of the indoor and outdoor signal coverage overlapping area can be solved.

Description

Indoor and outdoor seamless gradual change navigation transition method
Technical Field
The invention relates to the field of navigation positioning, in particular to an indoor and outdoor seamless gradual-change navigation transition method.
Background
A classical processing method in transition and connection between outdoor navigation positioning and indoor navigation positioning is a handover method. The U.S. apple company filed a patent in 2012, namely a seamless switching patent between outdoor navigation positioning and indoor navigation positioning, which means that a switching method is adopted when switching from one navigation system to another navigation system to achieve the purpose of seamless transition continuous navigation. This patent was later approved by the U.S. patent office for authorization. The patent is issued in advance, and aims to kill the indoor and outdoor continuous navigation switching method which can be widely applied. The switching method described in the patent is not considered to be the best seamless transition continuous navigation solution. Because the switching of the navigation system is mainly the conversion of navigation signals, the coverage boundary lines between two or more navigation systems are mutually staggered, so that the signals are very fuzzy and generally have no definite boundary, so that a proper switching point is difficult to find, and the switching method generates time delay, so that the position of a positioning solution is easy to jump, the switching position is easy to be discontinuous and difficult to be connected seamlessly, and finally the phenomena of discontinuous, sudden jump and the like of the position track of navigation positioning are caused.
For example, the Chinese patent application number is: the patent of CN201210290358.3 discloses a seamless handover method of indoor wireless positioning and outdoor wireless positioning based on cost function, which relates to a seamless handover method of indoor wireless positioning and outdoor wireless positioning, in particular to a seamless handover method of indoor wireless positioning and outdoor wireless positioning based on cost function, in order to solve the problem that the existing indoor wireless positioning and outdoor wireless positioning can not be seamlessly switched, the method comprises the following specific steps: step one, setting an overlapping area; step two, selecting parameters: selecting different parameters to participate in cost function operation according to different positioning systems; setting weight; step four, determining a threshold or a residence time; and step five, comparing the cost functions.
The patent and the apple patent are different in place, an overlapped space is set, different parameters and weights are selected for different positioning systems to form a cost function, the parameters participating in operation are fixed values, the weight coefficients are variables, the corresponding relation is built between the cost function and the space positions, the weight coefficients are changed, and the cost function has better distinguishing capacity at the edge of each positioning coefficient service area. And when the difference between the cost function of the target system and the cost function value of the current system is higher than a certain threshold, switching. The essence of the patent is still the switching problem among various heterogeneous positioning systems, and the physical quantity for distinguishing the indoor environment and the outdoor environment mainly refers to GNSS satellite signal strength, the number of GNSS visible satellites, indoor positioning node signal strength, Euclidean distance between a test vector and a fingerprint map and the like. The patent judges to which positioning system the positioning service is switched by comparing cost function values of all systems. The switching means is still used and the weights need to be selected with a ping-pong effect.
Also, for example, the Chinese patent application number is: the patent of CN201510273112.9 discloses an indoor and outdoor seamless positioning system integrating satellite navigation and bluetooth technology and a method thereof, and an application terminal device used in the patent is composed of an outdoor satellite positioning module, an indoor bluetooth positioning module, an indoor and outdoor positioning fusion switching module and an electronic map display module. The navigation positioning area is divided into three types of areas: the indoor signal working area is used for receiving the indoor signal, and the outdoor signal working area is used for receiving the indoor signal. Only in the coexistence region of the two signals, the Kalman filtering method is adopted for data processing. This method of separating into three types of regions is an ideal dividing method. The terminal that the patent pointed to can only receive two kinds of signals, receives satellite navigation signal outdoors promptly, and indoor only has bluetooth signal, and the current trend's use scheme is multisource integration navigation location in fact, is not accorded with reality.
Again, as with chinese patent application No.: the invention of CN201810813783.3 provides an indoor and outdoor navigation seamless switching method and a control system, the application terminal equipment used by the invention comprises a scene perception module, a scene change analysis module and a method switching module, and in the running process, analysis and judgment are repeatedly carried out, so that a very uncomplicated process is complicated.
Disclosure of Invention
The invention aims to provide an indoor and outdoor seamless gradual change navigation transition method aiming at the defects of the prior art, and meets the indoor and outdoor seamless navigation positioning requirements.
The indoor and outdoor seamless gradual change navigation transition method comprises the following steps:
step 1, constructing a coordinate reference frame:
on the basis of adopting a geocentric geostationary coordinate system frame, simultaneously adopting a building local coordinate system frame and a station center coordinate system frame, positioning by adopting terminal equipment, and correcting by a nearby base station;
step 2, indoor and outdoor seamless gradual change navigation transition:
1) arranging an overlapping signal coverage area at an indoor and outdoor junction, wherein the overlapping range is 20-50 m;
2) drawing a two-dimensional map of an overlapping signal coverage area at an indoor and outdoor junction, and connecting the indoor map and the outdoor map;
3) acquiring positioning information, gradually giving up satellite navigation signals and gradually increasing indoor navigation signals in transitional navigation from outdoor to indoor; in the transitional navigation from indoor to outdoor, gradually abandoning indoor navigation signals and gradually increasing satellite navigation signals; listing indoor and outdoor navigation positioning measurement models used for resolving;
4) and processing the information in the overlapping signal coverage area by adopting a generalized data fusion algorithm to obtain an optimized navigation track.
Further, in step 1, the specific step of using the building local coordinate system includes:
1) setting a coordinate origin O in the building;
2) the direction of the perpendicular line of the point O is taken as the Z axis, and the pointing zenith is taken as the positive; the meridian direction is the X axis, and the north direction is positive; the Y axis is vertical to the X, Z axis, and is positive in the east direction; forming a left-hand rectangular coordinate system;
3) establishing a conversion relation between an indoor building coordinate system and an outdoor geocentric coordinate system through the earth coordinate of the coordinate origin O as follows:
the geocentric coordinate of the known origin of coordinates O is (X)0,Y0,Z0) The geodetic coordinates are latitude and longitude
Figure GDA0001973689210000031
Let the geocentric coordinate (X) of any point P in spaceP,YP,ZP) Then the spatial coordinates of point P in the building local coordinate system with point O as the origin are represented as follows:
Figure GDA0001973689210000041
conversely, if the spatial point P is known, the coordinates in the building local coordinate system with the point O as the origin are known
Figure GDA0001973689210000042
The geocentric coordinates of point P are then:
Figure GDA0001973689210000043
further, in step 1, an air pressure height measuring chip is arranged in the terminal device, and an absolute elevation value is obtained through differential calculation according to air pressure base point correction information provided by the air pressure height measuring chip and the base station.
Further, in step 1, the standing center coordinate system is set in a manner that an area coordinate system is set in the center of a city and at a commercial dense place, the Z axis and the plumb line are coincident and point to the zenith, the X axis points to the true north, and the Y axis is perpendicular to the X, Z axis and points to the true east, so that a left-hand coordinate system is formed.
Further, in step 2), a three-dimensional map of the overlapping signal coverage area at the indoor and outdoor boundary is drawn.
Further, in step 2, 3), an indoor and outdoor seamless navigation positioning measurement model is established as follows:
xi＝f(yi,zj,ρl,rk,δm) (3)
i＝1,2,.....n1
j＝1,2,.....n1
l＝1,2,.....n1
k＝1,2,.....n1
m＝1,2,.....n1
Ω:yi∩zj＞0
in the formula, xiRepresenting a coordinate value of a position to be solved of the terminal; y isiIs a measurement value of an outdoor signal source; z is a radical ofjIs a measured value of an indoor signal source; r iskOther indoor measurement quantities; rholOther outdoor measurement quantities; deltamOther measurement quantities of the universe; f (.) is a measurement function expression; omega: representing the intersection area of the indoor and outdoor signals.
Further, in step 2, step 4), the specific step of obtaining the optimized navigation track by using the generalized data fusion algorithm includes:
s1, constructing a problem solving model:
establishing a solution (x) for the trajectoryi,yi,zi),i＝1,2,3…neThe model (2) is as follows:
Figure GDA0001973689210000051
the model (4) is composed of two parts, the upper part being the direct solution part, where pj，ηlIs an absolute measurement or observation, f1(xi,yi,zi,xsj,ysj,zsj) Solving a functional relation, g, for the quantities of state1(xi,yi,zi) For the relation of the constraint function, neThe final epoch number is m, the signal source number is m, and k is the constraint equation number; the purpose of the combined constraint equation is to solve the space through combined compression, so that the solution precision is improved;
the lower part is the recursion part, where Δ Xi,ΔYi,ΔZiThe low-order state quantity can be a relative change quantity of the state variable, or can be a derivative value or a differential value of the state variable, f2(Δxi),f3(Δyi),f4(Δzi) Are respectively a recurrence relation, g2(Δxi,Δyi,Δzi) As a function of a constraint relating low order state quantities, alphaiRepresenting a constraint relationship between the components; after the correlation constraint is added among all component values, the coupling matching among different components can be strengthened, the correlation solution can be obtained favorably, and the real vector solution can be formed in fact favorably;
s2, coordinate transformation:
if the two parts in the model (4) are respectively established under different coordinate systems, coordinate conversion is carried out, and the two parts are unified to the same coordinate system for resolving; or firstly, resolving can be respectively completed under different coordinate systems, and then data are converted into the same coordinate system to be integrated and combined;
s3, solving the state solving equation of the absolute state quantity to directly obtain the state quantity value (x)i,yi,zi)；
If the equation is in a nonlinear form, solving the following nonlinear state solution equation by adopting a nonlinear direct solution algorithm:
f(xi)＝ρi+νi，i＝1,2,...,ne (5)
in the formula (5), f (x)i) Solving a relation for the state quantities, typically a non-linear functional relation, xiAs a function of the state variable, piTo measure quantity, viIs random noise, i is epoch number, neIs the number of equations;
firstly, a residual minimization optimization model is established, wherein the model comprises the following steps:
find x, make
Figure GDA0001973689210000061
If there is a constraint, find x, make
Figure GDA0001973689210000062
In the formula (7), g (x)n) Is a constraint function relation, c is a right-end term of a constraint equation, and upsilon is random noise; the formula (7) can be solved by adopting nonlinear direct solving algorithms such as a single forming method, a random complex method and the like, and the objective function value is approximated to an optimal point step by step through the steps of searching, comparing and the like;
s4, establishing a state quantity recurrence equation, and obtaining an optimal estimated value of the state quantity after recurrence
Figure GDA0001973689210000063
Establishing a recursion equation of the low-order state quantity, acquiring a new value of the high-order state quantity, and combining the new value with a state solution value directly obtained from solving of a solution equation to improve the precision of the state value solution and the relevance of the solution; the low-order state quantity can be a derivative value or a differential value related to the state quantity, and can also be differential information; when estimating the next epoch state estimation, the embodiment obtains the high-order state estimation of the next epoch by adding the first derivative value or the product of the high-order derivative value of the observable state quantity and the time interval on the basis of the current optimal state estimation value; the state quantity recurrence formula adopted in this process is expressed as follows:
Figure GDA0001973689210000064
wherein Z (. cndot.) represents a recurrence relation;
when the recurrence relation conforms to kinematics, the following relation is expressed:
Figure GDA0001973689210000071
in the formulae (8) and (9),
Figure GDA0001973689210000072
is tnThe first derivative value of the state variable at epoch,
Figure GDA0001973689210000073
is tnSecond derivative value of state variable in epoch, upsilonnIs tnThe random noise in the epoch is generated by the random noise,
Figure GDA0001973689210000074
is tnThe state quantity recursion estimated value in epoch,
Figure GDA0001973689210000075
is tn-1The optimal estimation value of the state quantity in the epoch is delta t which is the interval time between epochs;
initial state estimator at fusion initiation stage
Figure GDA0001973689210000076
It is not known to replace the state measurements of the first few epochs, or to replace the approximated values with approximated values;
s5 combination tnDirectly solving state value and optimal estimated state value to obtain optimal state estimated value in epoch
Figure GDA0001973689210000077
Performing integrated fusion solving on the state values obtained from the two types, and performing integrated fusion solving on the state values obtained from the two typesnState prediction in epoch
Figure GDA0001973689210000078
And tnDirect solution state value x in epochnThe ambiguities are combined to obtain tnState optimal interval estimator in epoch
Figure GDA0001973689210000079
Figure GDA00019736892100000710
Solving the coefficient alpha in the formula (10) by adopting a generalized continuation approximation method1，α2，α3Then, the following is obtained:
Figure GDA00019736892100000711
in the formula (11), ω0、ω1、ω2As the weight coefficient,
Figure GDA00019736892100000712
is the quantity to be determined alpha1，α2，α3The number of the constraint intervals of (2),
Figure GDA00019736892100000713
the above equation (11) is solved by an optimization algorithm, and the coefficient alpha of the generalized continuation approximation polynomial can be obtained1，α2，α3And a minimization of the objective function;
similarly, can be solved to obtain
Figure GDA00019736892100000714
S6, repeatedly applying iterative solution to obtain a group of optimized solutions:
assigning i +1 to i, replacing n with n + 1; by tn+1In place of tnRepeating steps S3-S6 to find tn+1Optimal state estimate at epoch
Figure GDA00019736892100000715
The iterative process is repeated, and the solution is recurrently carried out until i is equal to neWhen the time is over, a group of optimized navigation track solutions can be obtained
Figure GDA00019736892100000716
The invention has the beneficial effects that:
1. the indoor and outdoor seamless gradual change navigation transition method does not adopt switching at a certain point, but gradually changes in a section of area, and can realize smooth transition of indoor and outdoor navigation positioning, so that the position track has no break point and is continuous and smooth.
2. The indoor and outdoor seamless gradual change navigation transition method adopts the same resolving method, and not only can solve resolving of outdoor and indoor positioning, but also can solve resolving of seamless navigation positioning of indoor and outdoor signal coverage overlapping areas.
Detailed Description
Example 1
The indoor and outdoor seamless gradual change navigation transition method comprises the following steps:
step 1, constructing a coordinate reference frame:
on the basis of adopting a geocentric geostationary coordinate system frame, simultaneously adopting a building local coordinate system frame and a station center coordinate system frame, positioning by adopting terminal equipment, and correcting by a nearby base station; and an air pressure height measuring chip is arranged in the terminal equipment, and an absolute elevation value is obtained through differential calculation according to air pressure base point correction information provided by the air pressure height measuring chip and the base station.
The method for adopting the building local coordinate system comprises the following specific steps:
1) setting a coordinate origin O in the building;
2) the direction of the perpendicular line of the point O is taken as the Z axis, and the pointing zenith is taken as the positive; the meridian direction is the X axis, and the north direction is positive; the Y axis is vertical to the X, Z axis, and is positive in the east direction; forming a left-hand rectangular coordinate system;
3) establishing a conversion relation between an indoor building coordinate system and an outdoor geocentric coordinate system through the earth coordinate of the coordinate origin O as follows:
the geocentric coordinate of the known origin of coordinates O is (X)0,Y0,Z0) The geodetic coordinates are latitude and longitude
Figure GDA0001973689210000081
Let the geocentric coordinate (X) of any point P in spaceP,YP,ZP) Then the spatial coordinates of point P in the building local coordinate system with point O as the origin are represented as follows:
Figure GDA0001973689210000091
conversely, if the spatial point P is known, the coordinates in the building local coordinate system with the point O as the origin are known
Figure GDA0001973689210000092
The geocentric coordinates of point P are then:
Figure GDA0001973689210000093
the center coordinate system is arranged in the city center and at the commercial dense place, the Z axis and the plumb line are coincident and point to the zenith, the X axis points to the true north, the Y axis is perpendicular to the X, Z axis and points to the true east, and a left-hand coordinate system is formed
Step 2, indoor and outdoor seamless gradual change navigation transition:
1) arranging an overlapping signal coverage area at an indoor and outdoor junction, wherein the overlapping range is 20-50 m;
2) drawing a two-dimensional map or a three-dimensional map of an overlapping signal coverage area at an indoor and outdoor junction, and connecting the indoor map and the outdoor map; the two-dimensional map or the three-dimensional map of the overlapping signal coverage area is connected with the indoor map and the outdoor map, so that the outdoor navigation positioning track can be transited to the map of the overlapping signal coverage area, and the navigation positioning track can be transited to the indoor map from the map of the overlapping signal coverage area; similarly, the indoor navigation positioning track can be transited to the map of the overlapping signal coverage area, and then the navigation positioning track is transited to the outdoor map from the map of the overlapping signal coverage area.
3) Acquiring positioning information, gradually giving up satellite navigation signals and gradually increasing indoor navigation signals in transitional navigation from outdoor to indoor; in the transitional navigation from indoor to outdoor, gradually abandoning indoor navigation signals and gradually increasing satellite navigation signals; the indoor and outdoor navigation positioning measurement model used for resolving is listed as follows:
xi＝f(yi,zj,ρl,rk,δm) (3)
i＝1,2,.....n1
j＝1,2,.....n1
l＝1,2,.....n1
k＝1,2,.....n1
m＝1,2,.....n1
Ω:yi∩zj＞0
in the formula, xiRepresenting a coordinate value of a position to be solved of the terminal; y isiIs a measurement value of an outdoor signal source; z is a radical ofjIs a measured value of an indoor signal source; r iskOther indoor measurement quantities; rholOther outdoor measurement quantities; deltamOther measurement quantities of the universe; f (.) is a measurement function expression; omega: representing the intersection area of the indoor and outdoor signals.
4) Processing information in the overlapping signal coverage area by adopting a generalized data fusion algorithm to obtain an optimized navigation track;
the method specifically comprises the following steps:
and S1, constructing a problem solving model.
Establishing a solution (x) for the trajectoryi,yi,zi),i＝1,2,3…neThe model (2) is as follows:
Figure GDA0001973689210000101
the model (4) is composed of two parts, the upper part being the direct solution part, where pj，ηlIs an absolute measurement or observation, f1(xi,yi,zi,xsj,ysj,zsj) Solving a functional relation, g, for the quantities of state1(xi,yi,zi) For the relation of the constraint function, neAnd m is the number of signal sources and k is the quantity of constraint equations for the final epoch number. The purpose of the combined constraint equations here is to improve the accuracy of the solution by combining the compressed solution space.
The lower part is the recursion part, where Δ Xi,ΔYi,ΔZiThe low-order state quantity can be a relative change quantity of the state variable, or can be a derivative value or a differential value of the state variable, f2(Δxi),f3(Δyi),f4(Δzi) Are respectively a recurrence relation, g2(Δxi,Δyi,Δzi) As a function of a constraint relating low order state quantities, alphaiRepresenting the constraint relationship between the components. After the correlation constraint is increased among the component values, the coupling matching among different components can be strengthened, the correlation solution can be obtained favorably, and the real vector solution can be formed.
And S2, coordinate transformation.
If the two parts in the model (4) are respectively established under different coordinate systems, coordinate conversion is carried out, and the two parts are unified to the same coordinate system for resolving; or the calculation can be respectively completed under different coordinate systems, and then the data are converted into the same coordinate system for integrated combination.
S3, solving the state solving equation of the absolute state quantity to directly obtain the state quantity value (x)i,yi,zi)。
If the equation is in a nonlinear form, solving the following nonlinear state solution equation by adopting a nonlinear direct solution algorithm:
f(xi)＝ρi+νi，i＝1,2,...,ne (5)
in the formula (5), f (x)i) Solving a relation for the state quantities, typically a non-linear functional relation, xiAs a function of the state variable, piTo measure quantity, viIs random noise, i is epoch number, neIs the number of equations.
Firstly, a residual minimization optimization model is established, wherein the model comprises the following steps:
find x, make
Figure GDA0001973689210000111
If there is a constraint, find x, make
Figure GDA0001973689210000112
In the formula (7), g (x)n) And c is a right-end term of the constraint equation, and upsilon is random noise. The formula (7) can be solved by adopting nonlinear direct solving algorithms such as a single forming method, a random complex method and the like, and the objective function value is approximated to the optimal point step by step through the steps of searching, comparing and the like.
S4, establishing a state quantity recurrence equation, and obtaining an optimal estimated value of the state quantity after recurrence
Figure GDA0001973689210000113
And establishing a recursion equation of the low-order state quantity, acquiring a new value of the high-order state quantity, and combining the new value with a state solution value directly obtained from solving the equation to improve the precision of the state value solution and the relevance of the solution. The low-order state quantity may be a derivative value or a differential value related to the state quantity, or may be differential information. When estimating the next epoch state estimation, the present embodiment obtains the next epoch high-order state estimation by adding the first derivative value or the product of the high-order derivative value of the observable state quantity and the time interval on the basis of the current optimal state estimation value. The state quantity recurrence formula adopted in this process is expressed as follows:
Figure GDA0001973689210000121
wherein Z (. cndot.) represents a recurrence relation;
when the recurrence relation conforms to kinematics, the following relation is expressed:
Figure GDA0001973689210000122
in the formulae (8) and (9),
Figure GDA0001973689210000123
is tnThe first derivative value of the state variable at epoch,
Figure GDA0001973689210000124
is tnSecond derivative value of state variable in epoch, upsilonnIs tnThe random noise in the epoch is generated by the random noise,
Figure GDA0001973689210000125
is tnThe state quantity recursion estimated value in epoch,
Figure GDA0001973689210000126
is tn-1And the delta t is the interval time between epochs.
Initial state estimator at fusion initiation stage
Figure GDA0001973689210000127
It is not known to replace the state measurements of the first few epochs, or to replace the approximated values with approximated values.
S5 combination tnDirectly solving state value and optimal estimated state value to obtain optimal state estimated value in epoch
Figure GDA0001973689210000128
Performing integrated fusion solving on the state values obtained from the two types, and performing integrated fusion solving on the state values obtained from the two typesnState prediction in epoch
Figure GDA0001973689210000129
And tnDirect solution state value x in epochnThe ambiguities are combined to obtain tnState optimal interval estimator in epoch
Figure GDA00019736892100001210
Figure GDA00019736892100001211
Solving the coefficient alpha in the formula (10) by adopting a generalized continuation approximation method1，α2，α3Then, the following is obtained:
Figure GDA00019736892100001212
in the formula (11), ω0、ω1、ω2As the weight coefficient,
Figure GDA00019736892100001213
is the quantity to be determined alpha1，α2，α3The number of the constraint intervals of (2),
Figure GDA00019736892100001214
using optimization calculation for the above equation (11)Solving by the method, the coefficient alpha of the generalized continuation approximation polynomial can be obtained1，α2，α3And a minimization of the objective function.
Similarly, can be solved to obtain
Figure GDA00019736892100001215
And S6, repeatedly applying the iterative solution to obtain a group of optimized solutions.
Assigning i +1 to i, replacing n with n + 1; by tn+1In place of tnRepeating steps S3-S6 to find tn+1Optimal state estimate at epoch
Figure GDA0001973689210000131
The iterative process is repeated, and the solution is recurrently carried out until i is equal to neWhen the time is over, a group of optimized navigation track solutions can be obtained
Figure GDA0001973689210000132
The present invention provides a specific embodiment of an indoor and outdoor navigation canine teeth interlaced seamless gradual transition method, which further describes the objects, technical solutions and advantages of the present invention in detail, it should be understood that the above description is only an embodiment of the present invention, and is not intended to limit the present invention, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (5)

1. An indoor and outdoor seamless gradual change navigation transition method is characterized by comprising the following steps:
step 1, constructing a coordinate reference frame:
on the basis of adopting a geocentric geostationary coordinate system frame, simultaneously adopting a building local coordinate system frame and a station center coordinate system frame, positioning by adopting terminal equipment, and correcting by a nearby base station;
step 2, indoor and outdoor seamless gradual change navigation transition:
1) arranging an overlapping signal coverage area at an indoor and outdoor junction, wherein the overlapping range is 20-50 m;
2) drawing a two-dimensional map of an overlapping signal coverage area at an indoor and outdoor junction, and connecting the indoor map and the outdoor map;
3) acquiring positioning information, gradually giving up satellite navigation signals and gradually increasing indoor navigation signals in transitional navigation from outdoor to indoor; in the transitional navigation from indoor to outdoor, gradually abandoning indoor navigation signals and gradually increasing satellite navigation signals; listing indoor and outdoor navigation positioning measurement models used for resolving; the measurement model for indoor and outdoor seamless navigation positioning is established as follows:
xi＝f(yi,zj,ρl,rk,δm) (3)
i＝1,2,…n1
j＝1,2,…n2
l＝1,2,…n3
k＝1,2,…n4
m＝1,2,…n5
Ω:yi∩zj＞0
in the formula, xiRepresenting a coordinate value of a position to be solved of the terminal; y isiIs a measurement value of an outdoor signal source; z is a radical ofjIs a measured value of an indoor signal source; r iskOther indoor measurement quantities; rholOther outdoor measurement quantities; deltamOther measurement quantities of the universe; f (.) is a measurement function expression; omega: representing the intersection region of the indoor and outdoor signals, n1,n2,n3,n4,n5The number of variables i, j, l, k, m, respectively;
4) the method comprises the following specific steps of processing information in an overlapping signal coverage area by adopting a generalized data fusion algorithm to obtain an optimized navigation track, and calculating by adopting the generalized data fusion algorithm to obtain the optimized navigation track:
s1, constructing a problem solving model:
establishing and solving user track solution (x)i,yi,zi),i＝1,2,3…neThe model (2) is as follows:
Figure FDA0002747409390000021
the model (4) is composed of two parts, the upper part being the direct solution part, where pj，ηlIs the absolute measured value and observed value, f1(xi,yi,zi,xsj,ysj,zsj) Solving a functional relation, g, for the quantities of state1(xi,yi,zi) For the relation of the constraint function, neThe final epoch number is m, the signal source number is m, and k is the constraint equation number; the purpose of the combined constraint equation is to solve the space through combined compression, so that the solution precision is improved; x is the number ofsj，ysj，zsjThree-dimensional position coordinates of the navigation satellite;
the lower part is the recursion part, where (Δ x)i,Δyi,Δzi) Is a low order state quantity, is a relative change or derivative or differential of a state variable, f2(Δxi),f3(Δyi),f4(Δzi) Are respectively a recurrence relation, g2(Δxi,Δyi,Δzi) As a function of a constraint relating low order state quantities, alphaiRepresenting a constraint relationship between the components; after the correlation constraint is added among all component values, the coupling matching among different components can be strengthened, the correlation solution can be obtained favorably, and the real vector solution can be formed in fact favorably;
s2, coordinate transformation:
if the two parts in the model (4) are respectively established under different coordinate systems, coordinate conversion is carried out, and the two parts are unified to the same coordinate system for resolving; the calculation can be respectively completed under different coordinate systems, and then the data are converted into the same coordinate system for integrated combination;
s3, solving the state solving equation of the absolute state quantity to directly obtain the state quantity value (x)i,yi,zi)；
If the equation is in a nonlinear form, solving the following nonlinear state solution equation by adopting a nonlinear direct solution algorithm:
f(xi)＝ρi+νi，i＝1,2,...,ne (5)
in the formula (5), f (x)i) Solving a relation for the state quantities, typically a non-linear functional relation, xiAs a function of the state variable, piTo measure quantity, viIs random noise, i is epoch number, neIs the number of equations;
firstly, a residual minimization optimization model is established, wherein the model comprises the following steps:
find x, make
Figure FDA0002747409390000031
If there is a constraint, find x, make
Figure FDA0002747409390000032
In the formula (7), g (x)n) Is a constraint function relation, c is a right-end term of a constraint equation, and upsilon is random noise; l is the total number of the accumulated items of least square accumulated summation, the formula (7) adopts a nonlinear direct solving algorithm to solve, and the objective function value approaches to an optimal point step by step through searching and comparing steps;
s4, establishing a state quantity recurrence equation, and obtaining an optimal estimated value of the state quantity after recurrence
Figure FDA0002747409390000039
Establishing a recursion equation of the low-order state quantity, acquiring a new value of the high-order state quantity, and combining the new value with a state solution value directly obtained from solving of a solution equation to improve the precision of the state value solution and the relevance of the solution; the low-order state quantity is a derivative value or a differential value or differential information related to the state quantity; when estimating the next epoch state estimation, on the basis of the current optimal state estimation value, adding a first order derivative value or a product of a high order derivative value and a time interval of the observed state quantity to obtain the high order state estimation of the next epoch; the state quantity recurrence formula adopted in this process is expressed as follows:
Figure FDA0002747409390000033
wherein Z (. cndot.) represents a recurrence relation;
when the recurrence relation conforms to kinematics, the following relation is expressed:
Figure FDA0002747409390000034
in the formulae (8) and (9),
Figure FDA0002747409390000035
is tnThe first derivative value of the state variable at epoch,
Figure FDA0002747409390000036
is tnSecond derivative value of state variable in epoch, upsilonnIs tnThe random noise in the epoch is generated by the random noise,
Figure FDA0002747409390000037
is tnThe state quantity recursion estimated value in epoch,
Figure FDA0002747409390000038
is tn-1The optimal estimation value of the state quantity in the epoch is delta t which is the interval time between epochs;
initial state estimator at fusion initiation stage
Figure FDA0002747409390000041
It is not known to use the first fewReplacing the state measurement value of the epoch or replacing the state measurement value with an approximation value after approximation processing;
s5 combination tnDirectly solving state value and optimal estimated state value to obtain optimal state estimated value in epoch
Figure FDA0002747409390000042
Performing integrated fusion solving on the state values obtained from the two types, and performing integrated fusion solving on the state values obtained from the two typesnState prediction in epoch
Figure FDA0002747409390000043
And tnDirect solution state value x in epochnThe ambiguities are combined to obtain tnState optimal interval estimator in epoch
Figure FDA0002747409390000044
Figure FDA0002747409390000045
Solving the coefficient alpha in the formula (10) by adopting a generalized continuation approximation method1，α2，α3Then, the following is obtained:
Figure FDA0002747409390000046
in the formula (11), ω0、ω1、ω2As the weight coefficient,
Figure FDA0002747409390000047
is the quantity to be determined alpha1，α2，α3The number of the constraint intervals of (2),
Figure FDA0002747409390000048
Figure FDA0002747409390000049
Figure FDA00027474093900000410
is the supremum of the constraint interval; 1a, 2a, 3ais the infimum boundary of the constraint interval, the above formula (11) is solved by an optimization algorithm, and the coefficient alpha of the generalized continuation approximation polynomial can be obtained1，α2，α3And a minimization of the objective function;
in the same way, the solution is obtained
Figure FDA00027474093900000411
S6, repeatedly applying iterative solution to obtain a group of optimized solutions:
assigning i +1 to i, replacing n with n + 1; by tn+1In place of tnRepeating the steps S3-S6 to find the value at tn+1Optimal state estimate at epoch
Figure FDA00027474093900000412
The iterative process is repeated, and the solution is recurrently carried out until i is equal to neWhen the time is over, a group of optimized navigation track solutions can be obtained
Figure FDA00027474093900000413
2. The indoor and outdoor seamless gradual navigation transition method according to claim 1, wherein in the step 1, the specific step of adopting a building local coordinate system comprises:
1) setting a coordinate origin O in the building;
2) the direction of the perpendicular line of the point O is taken as the Z axis, and the pointing zenith is taken as the positive; the meridian direction is the X axis, and the north direction is positive; the Y axis is vertical to the X, Z axis, and is positive in the east direction; forming a left-hand rectangular coordinate system;
3) establishing a conversion relation between an indoor building coordinate system and an outdoor geocentric coordinate system through the earth coordinate of the coordinate origin O as follows:
the geocentric coordinate of the known origin of coordinates O is (X)0,Y0,Z0) The geodetic coordinates are latitude and longitude
Figure FDA0002747409390000051
Let the geocentric coordinate (X) of any point P in spaceP,YP,ZP) Then the spatial coordinates of point P in the building local coordinate system with point O as the origin are represented as follows:
Figure FDA0002747409390000052
conversely, if the spatial point P is known, the coordinates in the building local coordinate system with the point O as the origin are known
Figure FDA0002747409390000053
The geocentric coordinates of point P are then:
Figure FDA0002747409390000054
3. the indoor and outdoor seamless gradual-change navigation transition method according to claim 2, wherein in the step 1, an air pressure height measuring chip is arranged in the terminal device, and an absolute elevation value is obtained through differential calculation according to air pressure base point correction information provided by the air pressure height measuring chip and the base station.
4. The indoor and outdoor seamless gradual change navigation transition method according to claim 1, wherein in the step 1, a station center coordinate system is set in a manner that an area coordinate system is set in a city center and a commercial dense place, a Z axis is coincident with a plumb line and points to a zenith, an X axis points to true north, a Y axis is perpendicular to an X, Z axis and points to true east, and a left-hand coordinate system is formed.
5. The indoor and outdoor seamless gradual navigation transition method according to claim 1, wherein in step 2), a three-dimensional map of an overlapping signal coverage area at an indoor and outdoor boundary is drawn.
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