CN104316947B - GNSS/INS ultra-tight combination navigation apparatus and relative navigation system thereof - Google Patents
GNSS/INS ultra-tight combination navigation apparatus and relative navigation system thereof Download PDFInfo
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- CN104316947B CN104316947B CN201410426136.9A CN201410426136A CN104316947B CN 104316947 B CN104316947 B CN 104316947B CN 201410426136 A CN201410426136 A CN 201410426136A CN 104316947 B CN104316947 B CN 104316947B
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- 238000005259 measurement Methods 0.000 claims abstract description 34
- 239000000969 carrier Substances 0.000 claims abstract description 20
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- 238000012938 design process Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000004927 fusion Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 238000013508 migration Methods 0.000 description 2
- 230000005012 migration Effects 0.000 description 2
- -1 INS compound Chemical class 0.000 description 1
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- 230000003247 decreasing effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 239000005433 ionosphere Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000003032 molecular docking Methods 0.000 description 1
- 238000003199 nucleic acid amplification method Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000005436 troposphere Substances 0.000 description 1
Classifications
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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
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
-
- 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
- G01S19/43—Determining position using carrier phase measurements, e.g. kinematic positioning; using long or short baseline interferometry
- G01S19/44—Carrier phase ambiguity resolution; Floating ambiguity; LAMBDA [Least-squares AMBiguity Decorrelation Adjustment] method
-
- 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
- G01S19/51—Relative positioning
-
- 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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- Computer Networks & Wireless Communication (AREA)
- Automation & Control Theory (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
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Abstract
The invention discloses a global navigation satellite system (GNSS)/inertial/navigation system (INS) ultra-tight combination navigation apparatus and a relative navigation system thereof. On the basis of the traditional GNSS/INS ultra-tight combination navigation apparatus, the provided GNSS/INS ultra-tight combination navigation apparatus uses a distributed filtering structure. Slave filters are used for carrying out pretreatment on I,Q signals of all satellite channels; and the processed information is sent to a combined filter. Meanwhile, the GNSS/INS ultra-tight combination navigation apparatus is also applied to a relative navigation system; while the navigation state and the inertia measurement of a carrier itself are received, navigation information and a carrier phase of another carrier are also received; with a dual-different carrier phase and inertia measurement, recursion filtering resolving is carried out by using an optimal kalman filter and an optimal relative position and a relative speed between each two carriers among multiple carriers are estimated.
Description
Technical field
The invention belongs to navigation field, more says it is GNSS/INS hypercompact combination navigations device and relative navigation system.
Background technology
Global navigation satellite system GNSS (Global Navigation Satellite System), inertial navigation system
INS(InertialNavigationSystem);GNSS/INS hypercompact combination navigations are the study hotspots of integrated navigation in recent years.
Satellite navigation and inertial navigation have complementary advantage, and both compound modes can efficiently solve satellite navigation signals by geographical position
Put and environmental disturbances, and inertial navigation system measurement error with time cumulation the problems such as.GNSS/INS compound modes have loose group
Conjunction, tight integration and hypercompact compound mode.Wherein, hypercompact compound mode is the study hotspot in the field.This mode make use of inertia
Auxiliary of the navigation information to GNSS signal acquisition and tracking, realize GNSS information tracking parameter and inertial navigation Position And Velocity it
Between information fusion.Under complex environment, the hypercompact combined systems of GNSS/INS have stronger capacity of resisting disturbance, can be complexity
Motion carrier under situation, there is provided the critical function such as accurate and stable navigator fix, attitude determination and inertia alignment.
At present GNSS/INS hypercompact combination navigation filter structure majorities belong to centralized data processing.Generally I, Q signal
Frequency is in MHz magnitudes, and inertia is exported in 100Hz magnitudes, and centralized processing directly focuses on two kinds of information, intractability
Greatly, it is difficult to realize.
Distributed navigation system is a kind of new Navigation System Design theory.Distributed navigation is to see in multiple navigation carriers
Into a navigation system, by navigation system between multiple carriers navigation information be exchanged with each other with information sharing it is whole to improve
The navigation accuracy of individual system, while the failure tolerant level of the system of raising.Distributed navigation system can be divided into centralized configuration
And distributed frame.Lead-Follower structures are a kind of common centralized configurations, and its thought is to make in certain navigation carrier
For navigation terminal of leading a group, other conducts follow navigation carrier, the information between each navigation terminal be it is visible upwards, downwards not
It is visible.Distributed frame each navigation carrier exists together a rank, and the navigation information of each carrier is sent to Data processing
It is uniformly processed.Distributed navigation is in a group of planes is coordinated to form into columns using widely.
Relative navigation system is mainly used in the relative of satellite formation flying, Autonomous rendezvous and docking task and group of planes collaboration formation
The acquisition of navigation information.At present, the relative navigation system of view-based access control model is usually used in satellite Autonomous spacecrafts rendezvous task.
Relative navigation system is the key technology that a group of planes cooperates with formation flight.Relative Navigation information between flight carrier
Acquisition is to ensure the essential condition that Formation Flying keeps and converts.Its precision also can produce very big to formation flight effect
Affect.Rely on satellite navigation system more traditional Relative Navigation and autonomy is poor.Satellite navigation signals easily receive external interference,
Reliability cannot be guaranteed, once satellite-signal is interfered, Relative Navigation precise decreasing is quickly.How Relative Navigation is improved
Precision strengthen flight autonomy simultaneously and stability be current Relative Navigation research difficult point.
The content of the invention
Belong to centralized data processing to solve current GNSS/INS hypercompact combination navigations filter structure majority, to data
Processing speed requirement is very high, and system complex realizes the big problem of difficulty, the invention provides a kind of hypercompact combinations of GNSS/INS are led
Boat device, this is installed on Distributed filtering structure to realize, including GNSS radio-frequency front-ends, Inertial Measurement Unit, tracking ring
Road unit and junction filter;Junction filter is connected respectively with Inertial Measurement Unit, tracking loop unit, tracking
Loop unit is also connected with GNSS radio-frequency front-ends;
Wherein, tracking loop unit includes several visible satellite passages, each visible satellite passage correspondence one
Integral Processing unit and from wave filter;GNSS radio-frequency front-ends are received and processed and send data to after satellite signal data tracking and catch
Loop unit is obtained, the I of each visible satellite passage, Q signal are at corresponding Integral Processing unit in tracking loop unit
Send after reason to corresponding carries out the state vector that pretreatment obtains from wave filter from wave filter;Junction filter receives inertia and surveys
The metrical information and the state vector from wave filter of amount unit, using the information for receiving the carrier state information and load are estimated
Wave phase simultaneously generates loop control instruction tracking loop unit is controlled, wherein the carrier state information includes position
Put, speed and attitude.
Further preferred version, current, super from filter process in GNSS/INS hypercompact combination navigations device of the present invention
Front and delayed I, Q signal;
From state vector X of wave filteri=[δ wi δφi δti Mi]T, wherein δ wiFor estimating carrier frequencies error, δ φi
It is carrier phase estimation difference, δ tiFor phase estimator error, MiFor the carrier amplitude of signal, i be from wave filter is corresponding can
See satellite channel number, i=1,2 ... N, N are visible satellite port number, []TRepresenting matrix transposition;
The observed quantity Z from wave filteriFor current I, Q signal value, advanced I in integration period T, Q signal value and delayed I, Q believe
Number value, be expressed as:
Wherein, T0For the initial time of integration period, ε is that receiver produces the advanced and hysteresis between of pseudo noise code
Time migration.
Further preferred version, in GNSS/INS hypercompact combination navigations device of the present invention, the state of junction filter to
Amount
Wherein, δ x are site error state, and δ v are velocity error state,For attitude error state, δ w are that gyroscope is missed
Difference attitude vectors, δ a are acceleration error state vector;δtuFor the clock jitter of receiver, δ trBe receiver clock it is random
Drift error amount;
The measurement vector of junction filter is:
Wherein, δ ρiWithIt is respectively the difference and the difference of pseudorange rates of the pseudorange of GNSS and INS outputs.
Simultaneously the present invention in order to solve to rely on traditional Relative Navigation satellite navigation system and autonomy is poor asks more
Topic, present invention also offers a kind of relative navigation system based on GNSS/INS hypercompact combination navigation devices, the system is used to estimate
Optimum relative position and relative velocity in meter multichip carrier between each two carrier, it is characterised in that each carrier correspondence one
GNSS/INS hypercompact combination navigation devices, data transmission unit and the data processing unit being sequentially connected;
Wherein, data transmission unit includes wire transmission and is wirelessly transferred;Data processing unit includes that what is be connected with each other moves
States model construction unit and Relative Navigation wave filter;
The metrical information of Inertial Measurement Unit in GNSS/INS hypercompact combination navigation devices, from filter status vector
Carrier state information that carrier wave metrical information and junction filter are estimated, the wire transmission of carrier phase Jing are corresponding to the carrier
In dynamic model construction unit;The carrier state information and carrier phase also Jing that simultaneously junction filter is estimated is wirelessly transmitted to
In the dynamic model construction unit of other carriers;
The corresponding dynamic model construction unit of each carrier is using wire transmission and is wirelessly transferred the information of acquisition determining
Dynamic model is built after the quantity of state of dynamic model and observed quantity;According to dynamic model, Relative Navigation wave filter utilizes Kalman
Optimal filter recurrence equation group, is calculated the optimal estimation value of error state, relative position to two carriers and relatively speed
Degree compensates and then obtains the relative position and relative velocity of optimum.
Further preferred version, in relative navigation system of the present invention, the quantity of state of dynamic model and observed quantity are as follows:
The quantity of state of dynamic model is xGPSAnd xINS
xINS=[δ Δ v δ Δ x δ wm δam]T;
In formula, Δ x is the relative position of two carriers,For double difference integer ambiguity, Δ mφSingle poor carrier phase is more
Tracking error, δ T are tropospheric error;δ I are ionospheric error;δ Δ v are the relative velocity error state of two carriers, δ Δ x
For the relative position error state of two carriers, δ wmFor carrier m gyro error attitude vectors;δamFor carrier m acceleration errors
State vector, subscript m is carrier label;
The observed quantity of dynamic model is z=[Δ v Δ x]T, Δ v is the relative velocity of two carriers;Δ x is two loads
The relative position of body.
The present invention has compared with prior art following significant advantage:
(1) present invention adopts Distributed filtering structure first with, to each satellite channel I, Q signal carries out pre- from wave filter
Process, then will send to junction filter from the pretreated information of wave filter, it is to avoid centralized data processing to data at
Reason rate request is very high, and system complex realizes the big problem of difficulty;
(2) in based on the hypercompact combination relative navigation systems of GNSS/INS, GNSS/INS hypercompact combination navigation modes are make use of,
Both advantages are fully combined, information fusion mode is deep into into track loop I, the level of Q signal strengthens GNSS receiver
Capture and ability of tracking to satellite-signal, and then improve the anti-dynamic and capacity of resisting disturbance of system.Inertia survey is avoided simultaneously
The problems such as amount error is with time cumulation;(3) relative navigation system of GNSS/INS hypercompact combination navigation devices of the invention passes through
It is wirelessly transferred and the low-rate data (carrier phase and carrier navigation information) of each carrier is transmitted to the data processing unit of carrier
Shared, the enhancement information redundancy of information between carrier is completed, and then improves estimated accuracy.
Description of the drawings
Fig. 1 is the GNSS/INS hypercompact combination navigation schematic diagram of device of the present invention;
Fig. 2 is the relative navigation system schematic diagram based on GNSS/INS hypercompact combination navigation devices of the present invention;
Fig. 3 is the workflow diagram of the data processing unit of the present invention;
With reference to the accompanying drawings and detailed description the present invention is described in further detail;
Specific embodiment
As shown in figure 1, a kind of GNSS/INS hypercompact combination navigations device of the invention, the device is based on Distributed filtering structure
To realize, including GPS radio frequency front end, Inertial Measurement Unit, tracking loop unit and junction filter;The tracking
Loop unit includes N number of visible satellite passage, and each visible satellite passage corresponds to an Integral Processing unit and from wave filter;
GPS radio frequency front end receiver satellite-signal, and power amplification, frequency conversion and digital-to-analogue conversion are carried out, by the data is activation after conversion
To tracking loop unit, the I of each visible satellite passage, Q signal are at corresponding integration in tracking loop unit
Send after reason cell processing to corresponding carries out the state vector that pretreatment obtains from wave filter from wave filter;Junction filter connects
The metrical information and the state vector from wave filter of Inertial Measurement Unit are received, using above- mentioned information the carrier state information is estimated
With carrier phase and generate loop control instruction tracking loop unit is controlled.
Continuous position that GNSS system is provided, velocity information can aid in the initial alignment of INS systems, error estimation,
Compensation and correction etc..Meanwhile, GNSS system is also by the auxiliary of INS when obtaining next in combination, and then effectively improves dynamic environment
Capture and ability of tracking of the lower GNSS receiver to satellite-signal, and can guarantee that poor in satellite distribution situation or visible star number amount is few
In the case of keep higher positioning accuracy and reliability.GNSS radio-frequency front-ends are nursed one's health the satellite-signal for collecting, frequency conversion
And digitized.Tracking loop is responsible for the capture and tracking of signal.The hypercompact combined filter structures of GNSS/INS include combination filter
Ripple device and from wave filter two parts.Junction filter is based on pseudorange, pseudorange rates and carrier phase level, should from responsible from filtering
Before, the I of lead and lag, Q signal.Junction filter completes the optimum fusion output navigation letter to inertial navigation information and satellite information
Breath, while sending loop control instruction to acquisition and tracking loop.
From the handling process of wave filter:I after each passage, Q signal it is integrated enter from wave filter, make each passage from
State vector X of wave filteri=[δ wi δφi δti Mi]T, wherein δ wiFor estimating carrier frequencies error, δ φiIt is carrier phase
Estimation difference, δ tiFor phase estimator error, MiFor the carrier amplitude of signal, i is visible satellite passage corresponding from wave filter
Number, i=1,2 ... N, N be visible satellite port number, []TRepresenting matrix transposition;
The observed quantity from wave filter is current I, Q signal value, advanced I in integration period T, Q signal value and delayed I, Q signal
Value, is represented by:
Wherein, T0For the initial time of integration period, T is integration period, ε be receiver produce the advanced of pseudo noise code with
Time migration between hysteresis;
Therefore, it is from the state and measurement equation of wave filter in Distributed filtering structure:
Wherein, XiFor quantity of state, ZiFor observed quantity, Ai(k, k-1) represent from the k-1 moment to the state at k moment transfer away from
Battle array;Wi(k-1) it is the dynamic noise at k-1 moment, CiK () represents k moment observed differential matrixes, ViK () is made an uproar for the observation at k moment
Sound, k is the time quantum after sliding-model control, W in formulai(k-1)、Ai(k,k-1)、Vi(k)、CiK the specific design process of () is
Prior art, referring specifically to document:.GPS satellite navigations positioning principle and method [M] more than Liu Ji. Beijing:Science Press
.2003.
The handling process of junction filter:The state vector of junction filter increased on the basis of inertial navigation quantity of state is obtained from
The error state estimation of wave filter, i.e.,:
Wherein, δ x, δ v andRespectively position, speed and attitude error state, δ w are gyro error attitude vectors, δ a
For acceleration error state vector;δtuFor the clock jitter of receiver, δ trIt is the clock Random Drift Error amount of receiver.
The measurement vector being made up of pseudorange error and pseudorange rates error is:
Wherein, δ ρiWithIt is respectively the difference and the difference of pseudorange rates of the pseudorange of GNSS and INS outputs, subscript N is defended for visible
Star port number.
The state and observational equation of junction filter is represented by:
Wherein, X is quantity of state, and Z is observed quantity, and W (k-1) is the dynamic noise at k-1 moment, and V (k) is the observation at k moment
Noise, k is the time quantum after sliding-model control, and C (k) represents k moment observed differential matrixes, and A (k, k-1) was represented from the k-1 moment
To the state transfer matrix at k moment, W (k-1), V (k), C (k), the specific design process of A (k, k-1) are prior art, specifically
Referring to document:.GPS satellite navigations positioning principle and method [M] more than Liu Ji. Beijing:Science Press .2003.
As shown in Fig. 2 the relative navigation system based on GNSS/INS hypercompact combination navigation devices, including carrier 1 and carrier
2, the corresponding GNSS radio-frequency front-ends 11 of carrier 1, Inertial Measurement Unit 12, tracking loop unit 13, junction filter 14, data
Transmission unit 15 and data processing unit 16;Wherein, junction filter 14 respectively with tracking loop unit 13, inertia measurement
Unit 12, data transmission unit 15 are connected, and tracking loop unit 13 is also connected with GNSS radio-frequency front-ends 11, data transfer list
Unit 15 is also connected with data processing unit 16;Data transmission unit 15 includes wire transmission 151 and is wirelessly transferred 152;At data
Reason unit 16 includes connected model construction unit 161 and Relative Navigation wave filter 162;
The corresponding GNSS radio-frequency front-ends 21 of carrier 2, Inertial Measurement Unit 22, tracking loop unit 23, junction filter
24th, data transmission unit 25 and data processing unit 26;Wherein, junction filter 24 respectively with tracking loop unit 23,
Inertial Measurement Unit 22, data transmission unit 25 are connected, and tracking loop unit 23 is also connected with GNSS radio-frequency front-ends 21, number
Also it is connected with data processing unit 26 according to transmission unit 25;Data transmission unit 25 includes wire transmission 251 and is wirelessly transferred
252;Data processing unit 26 includes connected model construction unit 261 and Relative Navigation wave filter 262;
GNSS radio-frequency front-ends 11 are received and processed and send data to after satellite signal data tracking loop unit, with
The I of each visible satellite passage, Q signal send to right after corresponding Integral Processing cell processing in track Capture Circle unit 13
That what is answered carries out the state vector that pretreatment obtains from wave filter from wave filter;
Junction filter 14 receives the metrical information of Inertial Measurement Unit:Acceleration a1, angular velocity omega1With from wave filter
State vector, using above- mentioned information the position x of carrier 1 is estimated1, speed v1, attitude and carrier phase phi1And generate loop control
System instruction is controlled to tracking loop unit 13;
GNSS radio-frequency front-ends 21 are received and processed and send data to after satellite signal data tracking loop unit, with
The I of each visible satellite passage, Q signal send to right after corresponding Integral Processing cell processing in track Capture Circle unit 23
That what is answered carries out the state vector that pretreatment obtains from wave filter from wave filter;
Junction filter 24 receives the metrical information of Inertial Measurement Unit:Acceleration a2, angular velocity omega2With from wave filter
State vector, using above- mentioned information the position x of carrier 2 is estimated2, speed v2, attitude and carrier phase phi2And generate loop control
System instruction is controlled to tracking loop unit 23;
The metrical information of Inertial Measurement Unit 11, the carrier wave metrical information from the state vector of wave filter and combined filter
The status information of carrier 1 and carrier phase phi that device 14 is estimated1Jing wire transmission 151 is to the measurement module construction unit 161 of carrier 1
In;Simultaneously junction filter 14 will also estimate the position x of carrier 11, speed v1And carrier phase phi1Jing be wirelessly transferred 152 to
In the measurement module construction unit 262 of carrier 2;The metrical information of Inertial Measurement Unit 12, the load from the state vector of wave filter
The status information of carrier 2 and carrier phase phi that wave measurement information and junction filter are estimated2Jing wire transmission 251 is to carrier 2
In measurement module construction unit 261;Simultaneously junction filter 24 will also estimate the position x of carrier 22, speed v2, carrier phase
φ2Jing is wirelessly transferred in the measurement module construction unit 162 of 252 to carrier 1,
Measurement module construction unit 161 is according to by metrical information, the carrier wave measurement letter from the state vector of wave filter
Breath, the status information of carrier 1, carrier phase phi1, the status information of carrier 2 and carrier phase phi2To determine the quantity of state of dynamic model
With dynamic model is built after observed quantity,
Relative Navigation wave filter 162 utilizes Kalman's optimal filter recurrence equation group, is calculated the optimum of error state
Estimated value, compensates and then obtains the position of the opposite carrier 2 of carrier 1 of optimum to the relative position and relative velocity of two carriers
Put and speed;
Measurement module construction unit 261 is according to by metrical information, the carrier wave measurement letter from the state vector of wave filter
Breath, the status information of carrier 2, carrier phase phi2, the status information of carrier 1 and carrier phase phi1To determine the quantity of state of dynamic model
With dynamic model is built after observed quantity,
Relative Navigation wave filter 262 utilizes Kalman's optimal filter recurrence equation group, is calculated the optimum of error state
Estimated value, compensates and then obtains the position of the opposite carrier 1 of carrier 2 of optimum to the relative position and relative velocity of two carriers
Put and speed.
As shown in figure 3, the purpose of data processing centre is to carry out error estimation to Relative Navigation and complete Relative Navigation most
Excellent output.Position on carrier and speed state are estimated to be sent to the data processing list of each carrier by low-rate data chain
Unit, using the Relative Navigation information after each carrier positions and speed state work difference as nominal value.The data processing of destination carrier
Unit utilizes GNSS double difference carrier phasesWith the Inertia information on self-vector, optimum is carried out to Relative Navigation error state
Estimate, and complete the optimal estimation of Relative Navigation state;
Specifically complete to estimate relative position using double difference carrier phase, completed using acceleration analysis and relative position
Estimation to relative velocity.
Below by taking carrier 1 and carrier 2 as an example:Double difference carrier phase is obtained by difference twice:First by carrier 1 and carrier 2
Carrier wave measurement carry out first difference, this process eliminates Satellite clock errors and ephemeris error;Again by first time difference component phase
Difference again is carried out to the first difference component of main satellite, receiver clock error, double difference carrier phase is again, eliminatingCan
It is expressed as:
Wherein, Δ x=x1-x2, x1And x2The position of carrier 1 and carrier 2 under ECEF coordinate system (ECEF) is represented respectively
Put vector;λ is carrier wavelength;For the coefficient matrix of satellite i,For the coefficient matrix of satellite j;δTi,jWith δ Ii,jRespectively defend
The troposphere residual sum Ionosphere Residual Error of star i and satellite j;It is the double difference integer ambiguity of satellite i and satellite j;For
The poor carrier phase Multipath Errors of list of satellite i;For the poor carrier phase Multipath Errors of list of satellite j;For satellite i
With the double difference carrier phase measurement noise of satellite j, satellite i and satellite j refers to the corresponding satellite i of carrier 1, carrier 2 is corresponding defends
Star j;Here satellite i respective channel number i, satellite j respective channel number j;
Therefore, GNSS estimates that the state vector of relative position is represented by:
In formula,For double difference integer ambiguity, Δ mφSingle poor carrier phase Multipath Errors, δ T are tropospheric error;δ
I is ionospheric error.
Dynamic model after linearisation is represented by general type:
δxGPSFor the relative position error quantity of state of GNSS, wGFor state error, ΦGFor coefficient matrix.
Make v1And v2The respectively velocity vector of the relative earth of carrier 1 and carrier 2, then
v1=v2+Δv+wen×Δx (9)
It can be seen from specific force equation:
a1=a2+Δa+2wen×Δv+wen×Δx+wen×(wen×Δx) (10)
a1=f1-2wie×v1+g1 (11)
a2=f2-2wie×v2+g2 (12)
Wherein, subscript 1,2 represent respectively carrier 1 and carrier 2, and Δ v is the relative velocity of two carriers, and Δ x is two loads
The relative position of body, a1For the vector acceleration of the relative earth of carrier 1, a2For the vector acceleration of the relative earth of carrier 2;f1For
The specific force output under navigational coordinate system of carrier 1;f2The specific force output under navigation system for carrier 2;g1Gravity suffered by carrier 1 to
Amount, g2Gravity vector suffered by carrier 2, wenFor the angular velocity of the relative Department of Geography of navigational coordinate system;wieIt is used to relatively for Department of Geography
The angular velocity of property system,
Formula (9), (11) and (12) are substituted into (10) and can be obtained,
Formula (12) is carried out into the state that Taylor series expansion is obtained relative position and relative velocity, its dynamic model
Quantity of state xINSFor
xINS=[δ Δ v δ Δ x δ w1δa1]T (13)
δ Δ v are the relative velocity error state of two carriers, and δ Δ x are the relative position error state of two carriers, δ w1
For the gyro error attitude vectors of carrier 1;δa1For the acceleration error state vector of carrier 1;
Dynamic model after linearisation is represented by
Wherein, δ xINSRelative velocity and site error quantity of state for INS, wINSFor state error, ΦIFor corresponding system
Matrix number.
Formula (8) and (14) constitute the state equation of Relative Navigation wave filter,
Observation vector z=[Δ v Δ x]T, the dynamic model of Relative Navigation wave filter is represented by:
Wherein M (k) is k moment nominal trajectorys, and Φ (k, k-1) is represented from the k-1 moment to the state transfer matrix at k moment;C
K () represents the observed differential matrix at k moment;V (k) is observing matrix, and w (k-1) is dynamic noise, and x represents quantity of state, and z is represented
Observed quantity.Here Φ (k, k-1), C (k), v (k), the specific design process of w (k-1) are determined with reference to .GPS satellite navigations more than Liu Ji
Position principle and method [M]. Beijing:Science Press .2003.
According to formula (15) using Kalman's optimal filter recurrence equation group, the error of relative position and relative velocity is carried out
Estimate, and then draw the Relative Navigation information of optimum;
Pk,k-1=Φk,k-1Pk-1Φk,k-1+Qk-1
By above-mentioned recurrence equation group, the optimal estimation of error state is calculatedAfterwards, to the relative position of two carriers
The relative position and relative velocity of optimum are compensated and then obtained with relative velocity, with regard to Kalman's optimal filter recurrence equation
Group is prior art, referring to Yu Jixiang, chief editor《Kalman filtering and its application in inertial navigation》, aviation specialized teaching material volume
Careful group, 1984.
Claims (4)
1. a kind of GNSS/INS hypercompact combination navigations device, it is characterised in that the device realized based on Distributed filtering structure,
Including GNSS radio-frequency front-ends, Inertial Measurement Unit, tracking loop unit and junction filter;Junction filter respectively with it is used
Property measuring unit, tracking loop unit be connected, tracking loop unit is also connected with GNSS radio-frequency front-ends;
Wherein, tracking loop unit includes several visible satellite passages, each one integration of visible satellite passage correspondence
Processing unit and from wave filter;GNSS radio-frequency front-ends are received and processed and send data to after satellite signal data tracking ring
Road unit, the I of each visible satellite passage, Q signal are after corresponding Integral Processing cell processing in tracking loop unit
Send to corresponding carries out the state vector that pretreatment obtains from wave filter from wave filter;Junction filter receives inertia measurement list
The metrical information and the state vector from wave filter of unit, using the information for receiving carrier state information and carrier phase are estimated
And generate loop control instruction tracking loop unit is controlled, wherein the carrier state information includes position, speed
Degree and attitude, from filter process is current, lead and lag I, Q signal;
From state vector X of wave filteri=[δ wi δφi δti Mi]T, wherein δ wiFor estimating carrier frequencies error, δ φiIt is to carry
Wave phase estimation difference, δ tiFor phase estimator error, MiFor the carrier amplitude of signal, i is visible to defend from wave filter is corresponding
Star port number, i=1,2 ... N, N be visible satellite port number, []TRepresenting matrix transposition;
The observed quantity Z from wave filteriFor current I, Q signal value, advanced I in integration period T, Q signal value and delayed I, Q signal value,
It is expressed as:
Wherein, T0For the initial time of integration period, ε is the advanced time and hysteresis between that receiver produces pseudo noise code
Skew.
2. GNSS/INS hypercompact combination navigations device according to claim 1, it is characterised in that the state of junction filter to
Amount
Wherein, δ x are site error state, and δ v are velocity error state,For attitude error state, δ w are gyro error appearance
State vector, δ a are acceleration error state vector;δtuFor the clock jitter of receiver, δ trIt is the clock random drift of receiver
The margin of error;
The measurement vector Z of junction filter is:
Wherein, δ ρiThe difference of the pseudorange of GNSS and INS outputs is represented,Represent that GNSS and INS exports the difference of pseudorange rates.
3. a kind of relative navigation system based on GNSS/INS hypercompact combination navigations device described in claim 2, the system is used for
Estimate optimum relative position and relative velocity between each two carrier in multichip carrier, it is characterised in that each carrier correspondence one
Individual GNSS/INS hypercompact combination navigation devices, data transmission unit and the data processing unit being sequentially connected;
Wherein, data transmission unit includes wire transmission and is wirelessly transferred;Data processing unit includes the dynamic analog being connected with each other
Type construction unit and Relative Navigation wave filter;
The metrical information of Inertial Measurement Unit, the carrier wave from filter status vector in GNSS/INS hypercompact combination navigation devices
Carrier state information, the wire transmission of carrier phase Jing that metrical information and junction filter are estimated is to the corresponding dynamic of the carrier
In model construction unit;The carrier state information and carrier phase also Jing that simultaneously junction filter is estimated is wirelessly transmitted to other
In the dynamic model construction unit of carrier;
The corresponding dynamic model construction unit of each carrier is using wire transmission and is wirelessly transferred the information of acquisition determining dynamic
Dynamic model is built after the quantity of state of model and observed quantity;According to dynamic model, Relative Navigation wave filter is optimum using Kalman
Filtering recurrence equation group, is calculated the optimal estimation value of error state, and the relative position and relative velocity of two carriers are entered
Row compensation further obtains the relative position and relative velocity of optimum.
4. relative navigation system according to claim 3, it is characterised in that the quantity of state of dynamic model and observed quantity are such as
Under:
The quantity of state of dynamic model is xGPSAnd xINS
xINS=[δ Δ v δ Δ x δ wm δam]T;
In formula, Δ x is the relative position of two carriers,For double difference integer ambiguity, Δ mφSingle poor carrier phase multipath
Error, δ T are tropospheric error;δ I are ionospheric error;δ Δ v are the relative velocity error state of two carriers, and δ Δs x is two
The relative position error state of individual carrier, δ wmFor carrier m gyro error attitude vectors;δamFor carrier m acceleration error states
Vector, subscript m is carrier label;
The observed quantity of dynamic model is z=[Δ v Δ x]T, Δ v is the relative velocity of two carriers.
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