CN106908759A - A kind of indoor pedestrian navigation method based on UWB technology - Google Patents

A kind of indoor pedestrian navigation method based on UWB technology Download PDF

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Publication number
CN106908759A
CN106908759A CN201710058101.8A CN201710058101A CN106908759A CN 106908759 A CN106908759 A CN 106908759A CN 201710058101 A CN201710058101 A CN 201710058101A CN 106908759 A CN106908759 A CN 106908759A
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uwb
zero
inertial navigation
inertial
navigation
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王敬贤
曾庆化
孟骞
曾世杰
熊智
刘建业
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Nanjing University of Aeronautics and Astronautics
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Nanjing University of Aeronautics and Astronautics
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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
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0294—Trajectory determination or predictive filtering, e.g. target tracking or Kalman filtering
    • 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
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0257—Hybrid positioning
    • G01S5/0263—Hybrid positioning by combining or switching between positions derived from two or more separate positioning systems

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  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Navigation (AREA)

Abstract

The invention discloses a kind of indoor pedestrian navigation method based on UWB technology, navigated using the inertial navigation system based on zero-velocity curve, effectively inhibit inertial navigation position error to be dissipated with the time；And distribute UWB base stations rationally at key node in this region, and Kalman filtering is carried out with the inertial navigation location data based on zero-velocity curve using UWB location datas, effectively realize the amendment to inertial navigation positioning result.The present invention cannot overlay area for satellite-signal, it is adaptable to the monitoring position of special population, is also applied for the real-time positioning of the special trade staff such as fire-fighting security, applies also for the navigator fix of normal pedestrian.

Description

A kind of indoor pedestrian navigation method based on UWB technology
Technical field
The invention belongs to pedestrian navigation technical field, a kind of more particularly to indoor pedestrian navigation side based on UWB technology Method.
Background technology
Pedestrian navigation system based on satellite fix has been widely used in positioning field, because satellite-signal is easily built The problems such as building thing obstruct, generation multipath, non line of sight, time variation, therefore satellite navigation receiver is difficult to realize the high-precision of interior Degree positioning application.U.S. Draper laboratories propose for the foot that inertia measurement device is arranged on human body to realize people in 20 end of the centurys Body positioning function, wherein preferably being solved using zero-velocity curve technology, inexpensive INS errors diverging is fast to ask Topic.
Because indoor course angle is difficult accurate acquisition, therefore course angle error in pedestrian's inertial navigation system has turned into and has been used to One of main source of property Navigation system error.The current method for solving course angle divergence problem mainly has：Magnetic heading auxiliary is calculated Method, gyro rotation correction algorithm etc..Magnetic heading aided algorithm mainly applies to outdoor, and indoor magnetic field environment is complicated, it is difficult to using The algorithm；Gyro rotation correction algorithm is used for machine, pedestrian cannot meet algorithm needed for the condition that at the uniform velocity rotates of gyro.It is right The importance that indoor pedestrian's inertial navigation system course is modified becomes increasingly conspicuous.
UWB (ultrawideband) is current one of positioning field study hotspot both at home and abroad.Indoors in position fixing process, UWB has positioning precision, good anti-multipath performance, relatively low transmission power and certain penetration capacity of Centimeter Level, with The indoor positioning technologies such as WiFi, ZigBee, RFID are notable compared to advantage.At present, domestic and international researcher is to inertial navigation/UWB combinations Research is concentrated mainly on UWB and the indoor positioning for realizing unmanned plane, UWB and PDR/SLU (Pedestrian Dead is combined with IMU Reckoning/Step Length Update) combine and realize pedestrian navigation.However it is necessary that pointing out steps of the PDR/SLU to pedestrian Long, step number required precision is higher, which has limited final navigation accuracy.
The content of the invention
In order to solve the technical problem that above-mentioned background technology is proposed, the present invention is intended to provide a kind of room based on UWB technology One skilled in the art's air navigation aid, in the case of unknown pedestrian's exact stepsize, is suppressed using the inertial navigation system based on zero-velocity curve Inertial navigation position error is dissipated with the time, and Kalman filtering is carried out by the UWB under distributing rationally and inertial navigation result, real Existing inexpensive, high-precision indoor navigation.
In order to realize above-mentioned technical purpose, the technical scheme is that：
A kind of indoor pedestrian navigation method based on UWB technology, comprises the following steps：
(1) inertial sensor and UWB chips are arranged on the foot of pedestrian, configuration is optimized to UWB base stations, initialized Inertial navigation system, obtains initial position message and destination information；
(2) three axis accelerometer and three-axis gyroscope data of inertial sensor are obtained, reality is carried out by inertial navigation system When navigation calculation, while carrying out error correction using zero-velocity curve algorithm；
(3) judge whether pedestrian is located at indoor key node, the location information and inertial navigation system of comprehensive UWB chips Resolving information, carry out Kalman filtering, obtain positioning result；
(4) judge whether to arrive at, navigation is terminated after arriving at.
Further, in step (1), it is necessary to be demarcated to inertial sensor during initialization inertial navigation system, detain Except three axis accelerometer and zero bias of three-axis gyroscope；The output of Still time three-axis gyroscope is taken as three-axis gyroscope Zero bias；Zero bias of three axis accelerometer is calculated using three position accelerometer standardizations, is shown below：
In above formula, bx、by、bzRespectively zero bias of three axis accelerometer, Aix、Aiy、AizRespectively i-th the three of position The output average of axis accelerometer, i=1,2,3,miRepresent the flat of the i-th three axis accelerometer output of position Fang He, g represent local gravitational acceleration.
Further, in step (1), optimizing configuration to UWB base stations refers to, is only configured at key node indoors A number of UWB base station equipments, it is ensured that UWB chips are located at when at key node, can receive medium strong no less than 4 The base station signal of degree or the RMSE value of UWB chip positionings are less than 0.2m.
Further, the step of step (2) are as follows：
(21) judge whether inertial sensor data meets zero-speed decision condition, if meeting, into step (22), if not Meet, then into step (23)；
(22) zero-velocity curve algorithm erection rate is used, and recalculates attitude angle and resolve result to correct inertial navigation；
(23) navigation results are obtained using strap inertial navigation algorithm.
Further, in step (21), judge whether inertial sensor data meets the process of zero-speed decision condition：
The size of sliding window width N is set according to walking states, correlated variables is defined：
In above formula, ωx、ωy、ωzThe extreme difference of each axle output quantity of gyroscope respectively in the range of sliding window, max represents pole Big value, min represents minimum, and A is the maximum amplitude of three axis accelerometer output vector in the range of sliding window；
Work as ωx、ωy、ωz, at least 1 value of variable is in default threshold range in A, then it is assumed that be currently located at The Inertial Measurement Unit of foot is in zero-speed state, it is necessary to carry out zero-velocity curve.
Further, the detailed process of step (22)：
When carrying out zero-velocity curve, by speed zero setting, while recalculating attitude angle using following formula：
In above formula, θ, γ are respectively pitching, roll angle,Respectively three axis accelerometer is exported, and g is Local gravitational acceleration value.
Further, the step of step (3) are as follows：
(31) judge that whether UWB chips receive the base station signal of moderate strength no less than 4 or UWB chip positionings Whether RMSE value is less than 0.2m, if so, then explanation pedestrian is at key node, now into step (32), if it is not, then entering Step (33)；
(32) UWB positioning results are obtained, inertial navigation system calculation result and UWB positioning results is carried out into Kalman's filter Ripple, correction position information；
(33) using inertial navigation system calculation result as positioning result.
Further, in step (3), kalman filter state equation is with measurement equation：
In above formula：
Wherein, Xk、Xk-1The respectively quantity of state at k, k-1 moment, ZkIt is the measurement at k moment, Φk,k-1For state is shifted Matrix, Γk-1It is the system noise transfer matrix at k-1 moment, HkIt is the measurement matrix at k moment, Wk-1It is the system noise at k-1 moment Sound, VkIt is the measurement noise at k moment, F (tk) it is sytem matrix, G (tk) it is system noise matrix, T is discrete periodic.
Further, the quantity of state of Kalman filter is：
Wherein,Respectively inertial navigation east, north, the mathematical platform error angle in three, day direction, δ vE,δvN,δvURespectively It is inertial navigation east, north, three, the day velocity error in direction, δ L, δ λ, δ h are respectively the position mistake in inertial navigation east, north, three, day direction Difference, δ Kgx,δKgy,δKgz,δKax,δKay,δKazRespectively the demarcation factor of gyroscope X, Y, Z axis and accelerometer X, Y, Z axis is missed Difference；
The measurement of Kalman filtering is：
Z=[δ γ, δ θ, δ ψ, δ vE,δvN,δvU,δL,δλ,δh]T
Wherein, δ γ, δ θ, δ ψ are respectively roll angle, the angle of pitch, course angle and the zero-speed of current time inertial navigation resolving Roll angle, the angle of pitch, the difference of course angle that moment accelerometer is calculated, δ vE,δvN,δvURespectively current time inertial navigation Resolve the speed in direction of northeast days three and zero-speed difference, δ L, δ λ, δ h be respectively current time inertial navigation resolve position with UWB resolves position in east, north, three, the day difference in direction.
The beneficial effect brought using above-mentioned technical proposal：
For the relatively existing UWB of the present invention and PDR/SLU combinational algorithms, the inertial navigation based on zero-velocity curve has been used System, it is not necessary to know exact stepsize, the step number of pedestrian, can preferably suppress inertial navigation position error and be dissipated with the time；According to Kalman filtering is carried out by UWB positioning results and inertial navigation result, the course and position of inertial navigation system is corrected, while When UWB is disturbed positioning and deviation occurs, the accuracy of positioning is ensured using inertial navigation；Distribute UWB base station equipments rationally, realize The indoor navigation of low-cost and high-precision.
Brief description of the drawings
Fig. 1 is flow chart of the method for the present invention；
Fig. 2 is the geometrical model figure of TOA localization methods；
Fig. 3 is Kalman filtering recursion loop diagram.
Specific embodiment
Below with reference to accompanying drawing, technical scheme is described in detail.
A kind of indoor pedestrian navigation method based on UWB technology that the present invention is provided, is mainly used in leading in pedestrian room Boat positioning.The pedestrian position monitoring that can also be used in weak satellite-signal environment according to core concept of the present invention in specific implementation is chased after Track.
As shown in figure 1, the method comprises the following steps：
Step 1：Inertial sensor and UWB chips are arranged on the foot of pedestrian, configuration are optimized to UWB base stations, just Beginningization inertial navigation system, obtains initial position message and destination information.
Configuration is optimized to it when UWB base station equipments are installed, i.e., certain amount UWB bases are configured only at key node Station equipment, it is desirable to ensure that UWB chips receive medium-strength signal base station no less than 4 or UWB positioning RMSE at key node Value is less than 0.2m.The key node is the position that larger course change can occur in pedestrian's walking processes such as turning, stairs port Region.
Inertial sensor and the MEMS/UWB assembling devices that UWB chips are positioned on foot.Because inexpensive inertia device is steady Qualitative, poor repeatability, is demarcated using preceding to it every time, deducts the zero offset error of three-axis gyroscope and three axis accelerometer, The precision of sensor can be substantially improved.The output for taking Still time using gyroscope is inclined as zero, but accelerometer cannot be only Zero is obtained by the output of a certain position partially, therefore use a kind of three positions accelerometer standardization, by sensor in three differences The static data of position, obtains zero bias of accelerometer.The method is simple and practical, it is adaptable to the field calibration after installation Method.Algorithm is shown below：
In above formula, bx、by、bzRespectively zero bias of three axis accelerometer, Aix、Aiy、AizRespectively i-th the three of position The output average of axis accelerometer, i=1,2,3,miRepresent the flat of the i-th three axis accelerometer output of position Fang He, g represent local gravitational acceleration.
Positional information of the initial position with destination on default map is obtained from terminal is resolved, starts navigation.Certainly exist In other preferred embodiments, the initialization of inertia system and the acquisition of initial position can also be realized by other easy modes, The present invention is not particularly limited to this.
Step 2：The three axis accelerometer and three-axis gyroscope data of inertial sensor are obtained, is carried out by inertial navigation system Real-time navigation is resolved, while carrying out error correction using zero-velocity curve algorithm.
First determine whether whether inertial sensor data meets zero-speed decision condition, be output as this invention takes with gyroscope Sliding window determination methods supplemented by main, accelerometer output, the zero-speed moment to foot judges.Based on different walkings Sliding window width is set to variable N by state, and the size of the value is relevant with walking states, and following formula defines correlated variables：
In above formula, ωx、ωy、ωzThe extreme difference of each axle gyroscope output quantity respectively in the range of sliding window, max represents pole Big value, min represents minimum, and A is the maximum amplitude of three axis accelerometer output vector in the range of sliding window.Work as ωx、ωy、 ωz, at least 1 value of variable is in default threshold range in A, then it is assumed that currently at foot Inertial Measurement Unit In zero-speed state, zero-velocity curve is carried out.
When inertia device is in the zero-velocity curve moment, by its speed zero setting, while being exported using accelerometer using following formula Information recalculates the roll angle and the angle of pitch of the device：
Wherein, θ, γ are respectively pitching, roll angle,Respectively three axis accelerometer output, g is to work as The gravity acceleration value on ground.
When inertia device is not in the zero-speed moment, using traditional strapdown calculation method, recursion obtain the position of itself with Attitude.
Step 3：Judge whether pedestrian is located at indoor key node, the location information and inertial navigation of comprehensive UWB chips The resolving information of system, carries out Kalman filtering, obtains positioning result.
Configuration is optimized to it when UWB base station equipments are installed, i.e., certain amount UWB bases are configured only at key node Station equipment, it is desirable to ensure that UWB chips receive medium-strength signal base station no less than 4 or UWB positioning RMSE at key node Value is less than 0.2m.The key node is the position that larger course change can occur in pedestrian's walking processes such as turning, stairs port Region.
Whether the signal that detection UWB chips are received first meets preset requirement, and (medium-strength signal base station is no less than 4 Or UWB positioning RMSE values are less than 0.2m).
When signal meets to be required, UWB positioning results are obtained, the present invention uses TOA methods：Accurate measurement positioning chip is sent out The wireless pulse signals that go out reach each base station elapsed time, be multiplied by the light velocity obtain between chip and each base station it is accurate away from From so as to calculate the chip position of degree of precision.As shown in Fig. 2 each base station BSiCoordinate be (xi,yi,zi), positioning chip The coordinate of MS is (x, y, z).Positioning chip MS and each base station BSiThe distance between riOne can be determined with base station BSiIt is ball The heart, riIt is the spheroid of radius.The intersection point of these three balls is exactly the position of positioning chip MS.In most cases, due to r1、r2、r3 Measured value there is error, three balls can't just intersect at a point, it is therefore desirable to N number of (N >=4) base station could complete positioning, It is shown below：
Above formula asks the difference can to obtain following formula by quadratic sum：
N number of locating base station can obtain the N-1 equation of similar above formula, be written as the matrix form shown in formula：
MI=b
Wherein,
I=[x, y, z]T
According to the data of base station, the value of M and b is obtained, using least square method, you can obtain the coordinate I of positioning chip MS. Certainly in other preferred embodiments, UWB chips can be positioned by the method for TDOA/AOA/RSSI, and the present invention is to this It is not particularly limited.
Further, inertial navigation system calculation result and UWB positioning results are carried out into Kalman filtering, correction position letter Breath.
Specifically, kalman filter state equation is with measurement equation：
In above formula：
Wherein, XkIt is quantity of state, Φk,k-1It is state-transition matrix, Γk-1It is system noise transfer matrix, HkTo measure square Battle array, Wk-1And VkSystem noise is represented respectively and measures noise, F (tk) it is sytem matrix, G (tk) be system noise matrix, T be from The cycle of dissipating.
Wherein：Kalman filter demands system noise and measurement noise are orthogonal white noise sequences, that is, meet association Variance matrix：
cov{Wk,Wj T}=Qkδkj
cov{Vk,Vj T}=Rkδkj
Wherein, Qk,RkSystem noise variance matrix and measuring noise square difference matrix are referred to as, they are respectively given values Nonnegative definite battle array and positively definite matrix.δkjIt is Kronecker functions, i.e., is 1 only when the moment of k=j.Kalman filtering according to it is previous when The filtering estimate and the measurement at current time at quarter carry out the optimal estimation of current state, have two in recursive process and return Road, as shown in Figure 3.In Fig. 3,Expression state one-step prediction value,Represent state estimation, Pk,k-1The step of expression state one Prediction mean square error, Pk,kRepresent and measure the estimate mean square error after updating, KkIt is filtering gain.Two above circuit cycle Recursion obtains the estimate of state.
The quantity of state of Kalman filter is：
Wherein,Respectively inertial navigation northeast day three mathematical platform error angles in direction, δ vE,δvN,δvURespectively Three velocity errors in direction in inertial navigation northeast day, δ L, δ λ, δ h is respectively three site errors in direction in inertial navigation northeast day, δ Kgx,δ Kgy,δKgz,δKax,δKay,δKazRespectively gyro X, Y, Z axis and plus Table X, Y, the demarcation factor error of Z axis.Quantity of state initial value is needed In the light of actual conditions independently to set.
The measurement of Kalman filtering is：
Z=[δ γ, δ θ, δ ψ, δ vE,δvN,δvU,δL,δλ,δh]T
Wherein, δ γ, δ θ, δ ψ are respectively roll angle, the angle of pitch, course angle and the zero-speed moment of current time inertial reference calculation Roll angle, the angle of pitch, the difference of course angle that accelerometer is calculated, δ vE,δvN,δvURespectively current time inertial reference calculation northeast Its three speed in direction and zero-speed difference, δ L, δ λ, δ h are respectively current time inertial reference calculation position and exist with UWB resolvings position Three differences in direction in northeast day.
The use of inertial navigation system calculation result is positioning result when signal is unsatisfactory for requiring.
Step 4：Judge whether to arrive at, in this way, then terminate navigation, if not, return to step 2.
Embodiment is only explanation technological thought of the invention, it is impossible to limit protection scope of the present invention with this, it is every according to Technological thought proposed by the present invention, any change done on the basis of technical scheme, each falls within the scope of the present invention.

Claims (9)

1. a kind of indoor pedestrian navigation method based on UWB technology, it is characterised in that comprise the following steps：
(1) inertial sensor and UWB chips are arranged on the foot of pedestrian, configuration is optimized to UWB base stations, initialize inertia Navigation system, obtains initial position message and destination information；
(2) three axis accelerometer and three-axis gyroscope data of inertial sensor are obtained, is led in real time by inertial navigation system Boat is resolved, while carrying out error correction using zero-velocity curve algorithm；
(3) judge whether pedestrian is located at indoor key node, the location information of comprehensive UWB chips and the solution of inertial navigation system Calculation information, is input into Kalman filter, obtains positioning result；
(4) judge whether to arrive at, navigation is terminated after arriving at.
2. the indoor pedestrian navigation method of UWB technology is based on according to claim 1, it is characterised in that：In step (1), , it is necessary to demarcated to inertial sensor during initialization inertial navigation system, three axis accelerometer and three-axis gyroscope are deducted Zero bias；The output of Still time three-axis gyroscope is taken as zero bias of three-axis gyroscope；Using three position accelerometer marks Determine zero bias that method calculates three axis accelerometer, be shown below：
b x b y b z = 1 2 A 1 x A 1 y A 1 z A 2 x A 2 y A 2 z A 3 x A 3 y A 3 z - 1 z 1 z 2 z 3
In above formula, bx、by、bzRespectively zero bias of three axis accelerometer, Aix、Aiy、AizThree axles of respectively i-th position add The output average of speedometer, i=1,2,3,miI-th quadratic sum of the three axis accelerometer output of position is represented, G represents local gravitational acceleration.
3. the indoor pedestrian navigation method of UWB technology is based on according to claim 1, it is characterised in that in step (1), Optimizing configuration to UWB base stations refers to, only configures a number of UWB base station equipments at key node indoors, it is ensured that UWB Chip is located at when at key node, can receive the base station signal or UWB chip positionings of moderate strength no less than 4 RMSE value is less than 0.2m.
4. the indoor pedestrian navigation method based on UWB technology according to claim 1, it is characterised in that the step of step (2) It is as follows：
(21) judge whether inertial sensor data meets zero-speed decision condition, if meeting, into step (22), if discontented Foot, then into step (23)；
(22) zero-velocity curve algorithm erection rate is used, and recalculates attitude angle and resolve result to correct inertial navigation；
(23) navigation results are obtained using strap inertial navigation algorithm.
5. the indoor pedestrian navigation method of UWB technology is based on according to claim 4, it is characterised in that：In step (21), Judge whether inertial sensor data meets the process of zero-speed decision condition：
The size of sliding window width N is set according to walking states, correlated variables is defined：
ω x = | ω x max - ω x min | ω y = | ω y max - ω y min | ω z = | ω z max - ω z min | A = max i = 0 N ( a x i 2 + a y i 2 + a z i 2 )
In above formula, ωx、ωy、ωzThe extreme difference of each axle output quantity of gyroscope respectively in the range of sliding window, max represents very big Value, min represents minimum, and A is the maximum amplitude of three axis accelerometer output vector in the range of sliding window；
Work as ωx、ωy、ωz, at least 1 value of variable is in default threshold range in A, then it is assumed that currently located at foot Inertial Measurement Unit be in zero-speed state, it is necessary to carry out zero-velocity curve.
6. the indoor pedestrian navigation method of UWB technology is based on according to claim 4, it is characterised in that：The tool of step (22) Body process：
When carrying out zero-velocity curve, by speed zero setting, while recalculating attitude angle using following formula：
θ = a r c s i n ( f i b y b / g ) γ = - arctan ( f i b x b / f i b z b )
In above formula, θ, γ are respectively pitching, roll angle,Respectively three axis accelerometer output, g is locality Gravity acceleration value.
7. the indoor pedestrian navigation method based on UWB technology according to claim 1, it is characterised in that the step of step (3) It is as follows：
(31) judge UWB chips receive moderate strength base station signal whether no less than 4 or UWB chip positionings RMSE Whether value is less than 0.2m, if so, then explanation pedestrian is at key node, now into step (32), if it is not, then entering step (33)；
(32) UWB positioning results are obtained, inertial navigation system calculation result and UWB positioning results is carried out into Kalman filtering, repaiied Positive position information；
(33) using inertial navigation system calculation result as positioning result.
8. the indoor pedestrian navigation method of UWB technology is based on according to any one in claim 1-7, it is characterised in that： In step (3), kalman filter state equation is with measurement equation：
X k = Φ k , k - 1 X k - 1 + Γ k - 1 W k - 1 Z k = H k X k + V k
In above formula：
Φ k , k - 1 = Σ n = 0 ∞ [ F ( t k ) T ] n / n ! Γ k - 1 = { Σ n = 1 ∞ [ 1 n ! ( F ( t k ) T ) n - 1 ] } G ( t k ) T
Wherein, Xk、Xk-1The respectively quantity of state at k, k-1 moment, ZkIt is the measurement at k moment, Φk,k-1It is state-transition matrix, Γk-1It is the system noise transfer matrix at k-1 moment, HkIt is the measurement matrix at k moment, Wk-1System noise, V for the k-1 momentk It is the measurement noise at k moment, F (tk) it is sytem matrix, G (tk) it is system noise matrix, T is discrete periodic.
9. the indoor pedestrian navigation method of UWB technology is based on according to any one in claim 1-7, it is characterised in that： The quantity of state of Kalman filter is：
Wherein,Respectively inertial navigation east, north, the mathematical platform error angle in three, day direction, δ vE,δvN,δvURespectively it is used to East, north, three, the day velocity error in direction are led, δ L, δ λ, δ h are respectively inertial navigation east, north, three, the day site error in direction, δ Kgx,δKgy,δKgz,δKax,δKay,δKazThe respectively demarcation factor error of gyroscope X, Y, Z axis and accelerometer X, Y, Z axis；
The measurement of Kalman filtering is：
Z=[δ γ, δ θ, δ ψ, δ vE,δvN,δvU,δL,δλ,δh]T
Wherein, δ γ, δ θ, δ ψ are respectively roll angle, the angle of pitch, course angle and the zero-speed moment of current time inertial navigation resolving Roll angle, the angle of pitch, the difference of course angle that accelerometer is calculated, δ vE,δvN,δvURespectively current time inertial navigation is resolved Three, the northeast day speed in direction and zero-speed difference, δ L, δ λ, δ h are respectively current time inertial navigation and resolve position with UWB solutions Position is calculated in east, north, three, the day difference in direction.
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CN108170136A (en) * 2017-12-15 2018-06-15 武汉理工大学 More unmanned boat formation control system and methods based on wireless sensor network
CN108279003A (en) * 2018-02-01 2018-07-13 福州大学 It is a kind of based on the unmanned plane high accuracy positioning cruising inspection system used suitable for substation
CN108680167A (en) * 2018-05-16 2018-10-19 深迪半导体(上海)有限公司 Indoor dead reckoning localization method and system based on UWB and laser ranging
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