CN109708647A - A kind of indoor topological map pedestrian localization method based on fusion feature element - Google Patents
A kind of indoor topological map pedestrian localization method based on fusion feature element Download PDFInfo
- Publication number
- CN109708647A CN109708647A CN201910176373.7A CN201910176373A CN109708647A CN 109708647 A CN109708647 A CN 109708647A CN 201910176373 A CN201910176373 A CN 201910176373A CN 109708647 A CN109708647 A CN 109708647A
- Authority
- CN
- China
- Prior art keywords
- pedestrian
- map
- node
- camber line
- indoor
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 49
- 230000004927 fusion Effects 0.000 title claims abstract description 26
- 230000004807 localization Effects 0.000 title claims abstract description 13
- 230000001133 acceleration Effects 0.000 claims abstract description 14
- 238000004364 calculation method Methods 0.000 claims abstract description 11
- 238000000605 extraction Methods 0.000 claims abstract description 4
- 230000033001 locomotion Effects 0.000 claims description 17
- 239000000284 extract Substances 0.000 claims description 16
- 230000008569 process Effects 0.000 claims description 11
- 230000009471 action Effects 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 5
- 230000009466 transformation Effects 0.000 claims description 3
- 238000009825 accumulation Methods 0.000 abstract description 4
- 238000005516 engineering process Methods 0.000 abstract description 4
- 238000012360 testing method Methods 0.000 description 12
- 238000005259 measurement Methods 0.000 description 9
- 238000010586 diagram Methods 0.000 description 3
- 238000012937 correction Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 230000005484 gravity Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000007630 basic procedure Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
Landscapes
- Navigation (AREA)
Abstract
The invention belongs to field of locating technology, and in particular to a kind of indoor topological map pedestrian localization method based on fusion feature element.The present invention is by acquiring acceleration, angular speed and data acquisition time when pedestrian's walking using MEMS gyroscope and accelerometer, realize judgement of taking a step, step-size estimation, the course reckoning of pedestrian, and pedestrian's Initial Entry is set, to calculate the position for obtaining pedestrian indoors in map.It by creating characteristic element in indoor topological map and extraction chamber, is blended with the position of obtained pedestrian indoors is calculated, reduces the error generated by sensor accuracy, the final realization pedestrian accurate positioning in environment indoors.The present invention efficiently avoids the error accumulation problem of calculation result, positional accuracy with higher using the method for course constraint and position unsteady state operation.Present system independence is high, can not depend on external information completely and complete indoor positioning task, performance is stable and is easily achieved, and has very high engineering application value.
Description
Technical field
The invention belongs to field of locating technology, and in particular to a kind of indoor topological map pedestrian based on fusion feature element
Localization method.
Background technique
Indoor positioning technologies national economy, in terms of have universal application prospect, since interior can not make
It is positioned with satellite-signal, it is therefore desirable to by other navigation means.In recent years, MEMS inertial sensor is with its Gao Zizhu
The advantages that property, low-power consumption and low cost, is widely applied in the research and design of indoor positioning.Traditional indoor positioning skill
Art mainly uses MEMS Inertial Measurement Unit to realize the detection to pedestrian movement's state, obtains pedestrian with the method for reckoning and exists
It is the location of indoor.But such methods are positioned merely with Inertial Measurement Unit, positioning accuracy excessively relies on inertia biography
The measurement accuracy of sensor, and the case where will appear error accumulation.In view of the above problems, in the row based on MEMS Inertial Measurement Unit
Introduce topological map in people's indoor positioning device, auxiliary MEMS system carries out the reckoning of pedestrian's indoor location, to reduce by
Pedestrian's indoor positioning error caused by MEMS inertial sensor error.However, currently with topological map carry out indoor positioning according to
Rely the creation and identification in artificial landmark, positioning result is easy to be influenced by artificial landmark recognition result.In conclusion existing
Indoor orientation method limit the real work effect of system, the indoor orientation method based on MEMS Inertial Measurement Unit is determined
Position error can be accumulated constantly at any time, and the creation and knowledge of artificial landmark are excessively relied on using the indoor orientation method of topological map
Not.
The present invention designs a kind of indoor topological map using fusion feature element, passes through the analysis to pedestrian movement's state
The feature for judging pedestrian present position, in conjunction with pedestrian's indoor location that reckoning obtains, and with the interior in typing map
Shape feature is matched, to estimate the position of pedestrian indoors, has important engineering application value.
Perigene et al. is being published in periodical " mapping spatial geographic information ", 2017, volume 6,54-57 page " indoor calmly
Position technology development and application study " in, propose the side for being mounted on waist and completing to speculate pedestrian's track route using acceleration
Method, but limitation of this method by accelerometer precision.Ni L M is being published in " Wireless Networks ", and 2004
Year, volume 10, the 6th phase, in 701-710 pages " Indoor Location Sensing Using Active RFID " text,
It proposes and compensates the method for calculating pedestrian's indoor location mutually using multiple sensors information, but this method does not solve
The problem of multiple sensors combined error accumulates at any time.Shi Chaoxia et al. is being published in " robot ", and 2007, volume 29,
It is devised in " topological map creation and navigation under extensive environment " text of 5th phase using topological map a kind of suitable for machine
The indoor navigation mode of device people, but this algorithm is not detached from the dependence to artificial landmark.
Summary of the invention
The purpose of the present invention is to provide a kind of indoor topological map pedestrian localization method based on fusion feature element.
The object of the present invention is achieved like this:
A kind of indoor topological map pedestrian localization method based on fusion feature element, comprising the following steps:
(1) indoor plane map is converted to the indoor topological map of fusion feature element；
(2) starting for completing system is arranged the Initial Entry of pedestrian, and completes coordinate conversion according to access information；
(3) exercise data when acquisition pedestrian walking, and pedestrian's map indoors is resolved according to collected exercise data
It is the location of middle；
(4) motion state of the location of pedestrian that data combination goes out and pedestrian carry out map match, finally obtain row
Accurate location in people's current indoor.
The indoor topological map of fusion feature element described in step 1 is made of node and camber line, indoor topological map
The connection relationship between key point is expressed as in map with traditional map, the key point extracted in traditional map is referred to as node,
Connection relationship between node is known as camber line；
Node diagnostic element set defined formula:
N is the rank of node in formula, and the non-access point node that the rank of node is defined as having connection relationship with N number of node is
N grades of nodes, in characteristic element setIt arrivesIt is all course angles that pedestrian occurs at the node,For pedestrian from this
Entrance enters course angle when body of a map or chart,Course angle when to leave body of a map or chart from the entrance；
Camber line characteristic element set defined formula:
It include rank X, the camber line start node coordinate P of the camber line in formulaaAnd PbCourse angle relative to map coordinates systemCourse angle is from the course angle of certain section of camber line origin-to-destination, and camber line is divided into 2 grades, wherein on turning, crossroad, T shape road
The camber line extracted in mouthful is 1 grade of camber line, and other camber lines are 2 grades of camber lines.
Involved coordinate transformation formula in step 2 are as follows:
In formula, what x and y were indicated is coordinate position of the pedestrian in map coordinates system, and what x' and y' were indicated is that pedestrian is passing
Coordinate position in sensor coordinate system,It is the node diagnostic information extracted from Ingress node characteristic set.
The data acquired in step 3 be respectively pedestrian's acceleration in the process of walking, angular speed and data acquisition when
Between, involved pedestrian position calculation formula are as follows:
Wherein xN' and yN' it is position of the pedestrian relative to sensor coordinate system x-axis and y-axis, L respectivelyNIt is that pedestrian N is walked
Step-length,By the course angle for the pedestrian N step that three axis angular rates of collected pedestrian movement are calculated by Quaternion Method.
Map match described in step 4 includes that position forces amendment and course to constrain two parts；It forces the position
Modified process specifically includes: pedestrian movement has arrived node location, extracts the characteristic set of P at this time, judges whether to have occurred turn
Curved movement, the amendment if there is not turning action without position, continues the resolving of position；If there is turning action,
Then by the position constraint of pedestrian at node, continues position and resolve；It extracts all using P as another endpoint of 1 grade of camber line of endpoint
Coordinate information, and judge the node P that pedestrian will reach1, conversion is forced into the position of pedestrian after turning
To P1, and extract with P1The camber line being presently in for 2 grades of camber lines of endpoint as pedestrian；The course constraint is rigid in pedestrian
When into certain section of camber line, extract in the camber line characteristic element setAnd it willWithIt is calculated with current system
Course is compared respectively, and a closest pressure for currently calculating course is replaced with boat of the pedestrian in this section of camber line
To；With P1For the camber line that 2 grades of camber lines of endpoint will enter as pedestrian, if P1It is entrance, then does not need to extract camber line.
Compared with prior art, the beneficial effects of the present invention are:
The present invention utilizes MEMS inertia measurement during carrying out indoor positioning resolving using MEMS Inertial Measurement Unit
The data calculation that unit is measured goes out the position of pedestrian indoors, and effective using the method for course constraint and position unsteady state operation
Ground avoids the error accumulation problem of calculation result, positional accuracy with higher.Present system independence is high, can be complete
External information is not depended on entirely and completes indoor positioning task, and performance is stable and is easily achieved, therefore the present invention has very high engineering
Application value.
Detailed description of the invention
Fig. 1 is that the 6th apartment map nodes of Harbin Engineering University student and camber line extract situation；
Fig. 2 is the basic procedure block diagram of pedestrian's indoor orientation method proposed by the present invention；
Fig. 3 is the basic flow chart of the map-matching algorithm in indoor orientation method proposed by the present invention；
Fig. 4 is in verification process using the course angle change curve and phase before and after indoor orientation method proposed by the present invention
Course angle error comparison diagram is corresponded to for corridor；
Fig. 5 is in verification process using the pedestrian track comparison diagram before and after indoor orientation method proposed by the present invention.
Specific embodiment
The present invention is described in more detail for citing with reference to the accompanying drawing.
A kind of indoor topological map pedestrian localization method based on fusion feature element, includes the following steps:
(1) the indoor topological map that the position of pedestrian indoors uses fusion feature element is resolved, indoor topological map is used
Traditional map is expressed as in map the connection relationship between key point, and the key point extracted in traditional map is referred to as node, section
Connection relationship between point is known as camber line；
The indoor topological map of creation fusion feature element creates the two-dimensional coordinate system of indoor map first, and is entering and leaving
Mouth, turning and the end in corridor extract the node of map, and corridor is extracted as camber line, and node definition is the set of the point feature,
Expression formula is as follows:
The coordinate position of all nodes of typing is needed in system, expression formula involved in node coordinate position is as follows:
P=(xP, yP)
Wherein in set, includes the level n of node and go out the N kind course angle that is likely to occur in the node, if N grades of nodes
P is the node that entrance extracts, then has N-1 camber line to intersect at the node, in characteristic element setPedestrian from this
Entrance enters course angle when body of a map or chart,Course corner node when to leave body of a map or chart from the entrance
It is N grades of nodes that rank, which is defined as having with N number of node the non-access point node of connection relationship, and each camber line is set as the camber line feature
The set of element, expression formula are as follows:
Rank including the camber line and the course angle relative to map coordinates system, which is from this section of camber line
Point arrives the course angle of terminal, and camber line is divided into 2 grades, wherein the camber line extracted in turning, crossroad, T shape crossing is 1 grade of arc
Line, other camber lines are 2 grades of camber lines；
(2) need to read the initial position of pedestrian indoors after system starting；In position fixing process, MEMS acceleration is needed
The temporal information of acceleration, angular speed and data acquisition each time when meter and gyroscope acquisition pedestrian's walking；
(3) system expresses position of the pedestrian indoors in map using coordinate position of the pedestrian in two-dimensional coordinate system,
Related indoor location P, expression formula are as follows:
PN=(xN, yN)
(4) primary Calculation for completing pedestrian's indoor location needs to calculate position of the pedestrian relative to sensor coordinate system first
It sets, is by estimating per length step by step and calculating each step course to complete to pedestrian；
Calculation expression is as follows:
Wherein xN' and yN' it is position of the pedestrian relative to sensor coordinate system x-axis and y-axis, L respectivelyNIt is that pedestrian N is walked
Step-length,It is the course of the pedestrian N step calculated by three axis angular rates of collected pedestrian movement by Quaternion Method
Angle；
(5) resolve pedestrian relative to the position of indoor coordinate system be by be arranged Initial Entry, and construct coordinate conversion square
Battle array is realized.Calculation expression is as follows:
Then pedestrian is as follows relative to the dead reckoning expression formula of map coordinates system:
(6) eliminate pedestrian when walking indoors existing error need indoor topological map by fusion feature element into
The constraint of row course and position correction；
Course constraint is the course angle that the motion profile by pedestrian in corridor is approximatively constrained to corresponding camber line at presentProcess；
Position correction is to move to the node (x that near nodal will be reached by estimating pedestrian in pedestrianP, yP), to pedestrian
Position and locating camber line carry out unsteady state operation process.
A kind of indoor topological map pedestrian localization method based on fusion feature element proposed by the present invention, such as attached drawing 2,3
Shown, the key step of this method is as follows:
1. the node and camber line in extraction indoor plane map and the indoor topological map for creating fusion feature element, such as attached
Shown in Fig. 1.The indoor topological map for creating fusion feature element is reduced to go firstly the need of by pedestrian in three-dimensional indoor movement
People is projected in movement of the boundaries such as indoor wall landform in the projection on two-dimensional surface, so indoor three-dimensional space is simplified
For two dimension, coordinate system uses the right-handed coordinate system for having ignored Z axis, and chooses a bit of the closest southwest in map building range
As origin, to the east of and the north to the forward direction respectively as X-axis and Y-axis.
The indoor topological map of fusion feature element is made of node and camber line.Each node is set as characteristic element at this
Set.Because having at the N grade node of non-entrance and only N camber line intersecting, node of the pedestrian in non-entrance
Place has and the only course angle that is likely to occur of N kind.It include the level n of node and at this in the characteristic element set of node
Node goes out the N kind course angle being likely to occur.The expression formula of definition node is as follows:
If N grades of node P are the node that entrance extracts, there are N-1 camber line intersection, characteristic element set at the node
InIt is course angle when pedestrian enters body of a map or chart from the entrance,To leave body of a map or chart from the entrance
When course angle, expression formula is as follows:
Set each camber line to the set of the camber line characteristic element, characteristic element include the camber line rank and relative to
The Normal Course angle of map coordinates system, the course angle be from the course angle of this section of camber line origin-to-destination, 1 grade of camber lineAnd it is not involved in operation.Such as X grades of camber line PaPbIt is as follows to define expression formula:
PaAnd PbIt is the coordinate of this section of camber line start node respectively,It is the corresponding course angle of this section of camber line.
Attached drawing 1 is after carrying out node, camber line extraction to the 6th apartment corridor of Harbin Engineering University student using this method
Obtained result.
2. the starting and preheating of the system of completion.The Initial Entry of pedestrian is set, and coordinate conversion is completed according to access information.
Involved Formula of Coordinate System Transformation are as follows:
In formula, what x and y were indicated is coordinate position of the pedestrian in map coordinates system, and what x' and y' were indicated is that pedestrian is passing
Coordinate position in sensor coordinate system.It is the node diagnostic information extracted from Ingress node characteristic set.
3. acquiring exercise data when pedestrian's walking, the data of acquisition are that the Z axis of pedestrian in the process of walking accelerates respectively
The time of degree, three axis angular rates and data acquisition.
Judge whether pedestrian generates course of a step by the variation of acceleration.Use sliding window first to slide mean value
Filtering handles acceleration information, and eliminates gravity influence, involved acceleration output such as following formula:
In formula, M is sliding window size, and g is acceleration of gravity.
In Z axis acceleration information after treatment according to detect detected after a wave crest again the feature of a trough come
Judge that pedestrian steps a step.When detecting that pedestrian steps a step, extracts pedestrian and step the time used in this step, and estimate
The step-length of this step of pedestrian, related formula are as follows:
L=af+b
Wherein L is the step-length that pedestrian steps a step, and f is the cadence that pedestrian steps this step, and a and b are by transporting to pedestrian
The constant that the study estimate of dynamic feature goes out.By the estimation and research to a and b, obtain:
A=0.4155
B=-0.0271
Three axis angular rates of pedestrian movement are acquired while acquiring pedestrian's Z axis acceleration, and course is asked according to quaternary number
The method at angle acquires the course angle variation that pedestrian occurs when stepping this step
If the initial position of pedestrian is O (x0,y0), by the x of initial time motion information acquisition sensor, y-axis is as coordinate
X-axis, the y-axis of reckoning, the length taken a step are LN, course angle isThe position of arrival is (xN,yN), expression formula is as follows:
Due to
A, b, f are brought into step-length L=af+b, available:
4. the motion state of the location of pedestrian that data combination goes out and pedestrian carry out map match, such as attached drawing 4.Map
Matching is the core of location algorithm of the present invention, is divided into two parts, and course constraint and the pressure of position are corrected.
Course constraint is when pedestrian enters in camber line, and system extracts the standard in map in camber line characteristic element set
Course angle information elementCome the method that course angle when walking in this section of camber line to pedestrian is constrained, can reduce due to
Since course angle resolves position error caused by inaccuracy in pedestrian's walking process.
When pedestrian's course angle that system calculates is close to Normal Course angle information elementWhen, system can be by the boat of pedestrian
It is constrained to angleWhen turning, u-turn behavior occur in this section of camber line for pedestrian, which is cancelled.When system calculates
Pedestrian's course angle close toWhen, the course angle of pedestrian is constrained to
The pressure amendment of position is applied to turning, when system judges that pedestrian's arrival is presently in camber line endpoint node,
Monitor course angle variation of the pedestrian from this moment in a period of timeWhen differentiating that turning action occurs for pedestrian, can extract
It is all using the node as 1 grade of camber line P of endpointaPb……PaPn, and extract Pb……PnCoordinate (xb,yb)……(xn,yn)。
By course constraint release and pedestrian position is resolved, and calculates pedestrian current location (x after turning actionN,yN), and calculate
Pedestrian at this time with (xb,yb)……(xn,yn) distance ln, involved expression formula is as follows:
Take lb……lnIn minimum value lm, and force amendment to (x the position of pedestrianm,ym), it is walked to reduce in straight line
The accumulated position error of walking in corridor.
After system completes map matching process, so that it may obtain the accurate location that pedestrian is presently in.
Specific embodiment
To verify reasonability of the invention, feasibility, the 6th apartment corridor of Harbin Engineering University student is chosen to this hair
It is bright to be tested.The Z axis acceleration of pedestrian, three axis angular rates and data are adopted respectively using Inertial Measurement Unit MPU6050
Collect time data, and step involved in the present invention is tested according to these data.
Pedestrian's paces distinguished number is tested first, chooses the test that 20 measured carry out 100 steps of walking respectively,
By pedestrian's step number for measuring of the present invention compared with true value, test result is as follows table:
1 paces of table judge test of heuristics result
As shown above, 7 measured step counting error, every 100 step of 20 measured occur in 20 measured
Step counting mean error be 0.4 step.It can be seen that the paces in the present invention judge that algorithm can complete the task of paces judgement.
Step-size estimation algorithm in the present invention is tested, 20 measured are chosen, carries out the test of 100 steps of walking,
Measure respectively they average step length, average cadence, and according to average cadence and step-size estimation algorithm employed in the present invention,
The average step length of pedestrian is estimated, and is compared with measured value, test result is as follows shown in table:
2 step-size estimation test of heuristics result of table
As shown above, the maximum step-length mean error occurred in 20 groups of tests is -0.06765m/ step, can be preferable
The task of ground completion step-size estimation.
Course angle computation in the present invention is tested, this partial test is never calculated using map match respectively
Method and it is unfolded for the use of map-matching algorithm two, and the test result of these two aspects is compared, test result is for example attached
Shown in Fig. 4.It is by attached drawing 4 as it can be seen that obvious excellent in stationarity, accuracy using the course angle calculated after map-matching algorithm
In the course angle calculation result for not using map match.
Finally positioning calculation result of the invention is tested, test is also respectively from using map-matching algorithm and do not have
It is unfolded for the use of map-matching algorithm two, test result is as shown in Fig. 5.
Based on the above results, available following result: Z axis acceleration, three axis angular rate sum numbers by measuring pedestrian
The position of pedestrian indoors can be calculated according to acquisition time, solves the problems, such as that traditional indoor positioning algorithms independence is poor；It is logical
The indoor topological map and corresponding map-matching algorithm for introducing fusion feature element are crossed, solves and utilizes MEMS inertia measurement list
Member carries out the problem of positioning calculation error accumulation.The indoor pedestrian positioning of topological map based on fusion feature element can be effective
Complete pedestrian's indoor positioning task in ground.
It should be understood that these examples are only for illustrating the present invention and are not intended to limit the scope of the present invention.In addition, it should also be understood that,
After reading the content taught by the present invention, those skilled in the art can make various modifications or changes to the present invention, these
Equivalent form is also fallen within the scope of the appended claims of the present application.
Claims (5)
1. a kind of indoor topological map pedestrian localization method based on fusion feature element, which comprises the following steps:
(1) indoor plane map is converted to the indoor topological map of fusion feature element；
(2) starting for completing system is arranged the Initial Entry of pedestrian, and completes coordinate conversion according to access information；
(3) exercise data when acquisition pedestrian walking, and according to institute in collected exercise data resolving pedestrian indoors map
The position at place；
(4) motion state of the location of pedestrian that data combination goes out and pedestrian carry out map match, finally obtain pedestrian and work as
Accurate location in cup.
2. a kind of indoor topological map pedestrian localization method based on fusion feature element according to claim 1, special
Sign is: the indoor topological map of fusion feature element described in step 1 is made of node and camber line, and indoor topological map is used
Traditional map is expressed as in map the connection relationship between key point, and the key point extracted in traditional map is referred to as node, section
Connection relationship between point is known as camber line；
Node diagnostic element set defined formula:
N is the rank of node in formula, and it is N grades that the rank of node, which is defined as having with N number of node the non-access point node of connection relationship,
Node, in characteristic element setIt arrivesIt is all course angles that pedestrian occurs at the node,Go out for pedestrian from this
Entrance enters course angle when body of a map or chart,- 180 ° are course angle when leaving body of a map or chart from the entrance；
Camber line characteristic element set defined formula:
It include rank X, the camber line start node coordinate P of the camber line in formulaaAnd PbCourse angle relative to map coordinates systemBoat
It is from the course angle of certain section of camber line origin-to-destination to angle, camber line is divided into 2 grades, wherein in turning, crossroad, T shape crossing
The camber line of extraction is 1 grade of camber line, and other camber lines are 2 grades of camber lines.
3. a kind of indoor topological map pedestrian localization method based on fusion feature element according to claim 1, special
Sign is: involved coordinate transformation formula in step 2 are as follows:
In formula, what x and y were indicated is coordinate position of the pedestrian in map coordinates system, and what x' and y' were indicated is pedestrian in sensor
Coordinate position in coordinate system,It is the node diagnostic information extracted from Ingress node characteristic set.
4. a kind of indoor topological map pedestrian localization method based on fusion feature element according to claim 1, special
Sign is: the data acquired in step 3 be respectively pedestrian's acceleration in the process of walking, angular speed and data acquisition when
Between, involved pedestrian position calculation formula are as follows:
Wherein xN' and yN' it is position of the pedestrian relative to sensor coordinate system x-axis and y-axis, L respectivelyNIt is the step of pedestrian N step
It is long,By the course angle for the pedestrian N step that three axis angular rates of collected pedestrian movement are calculated by Quaternion Method.
5. a kind of indoor topological map pedestrian localization method based on fusion feature element according to claim 1, special
Sign is: map match described in step 4 includes that position forces amendment and course to constrain two parts；It forces to repair in the position
Positive process specifically includes: pedestrian movement has arrived node location, extracts the characteristic set of P at this time, judges whether turning occurred
Movement, the amendment if there is not turning action without position continues the resolving of position；If there is turning action,
By the position constraint of pedestrian at node, continues position and resolve；It extracts all using P as another endpoint of 1 grade of camber line of endpoint
Coordinate information, and judge the node P that pedestrian will reach1, the position of pedestrian is forced to be transformed into after turning
P1, and extract with P1The camber line being presently in for 2 grades of camber lines of endpoint as pedestrian；The described course constraint be pedestrian just into
When entering certain section of camber line, extract in the camber line characteristic element setAnd it willWith- 180 ° of boats calculated with current system
To being compared respectively, a closest pressure for currently calculating course is replaced with into boat of the pedestrian in this section of camber line
To；With P1For the camber line that 2 grades of camber lines of endpoint will enter as pedestrian, if P1It is entrance, then does not need to extract camber line.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910176373.7A CN109708647A (en) | 2019-03-08 | 2019-03-08 | A kind of indoor topological map pedestrian localization method based on fusion feature element |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910176373.7A CN109708647A (en) | 2019-03-08 | 2019-03-08 | A kind of indoor topological map pedestrian localization method based on fusion feature element |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109708647A true CN109708647A (en) | 2019-05-03 |
Family
ID=66265635
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910176373.7A Pending CN109708647A (en) | 2019-03-08 | 2019-03-08 | A kind of indoor topological map pedestrian localization method based on fusion feature element |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109708647A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110686682A (en) * | 2019-11-15 | 2020-01-14 | 北京理工大学 | Indoor pedestrian course fusion constraint algorithm based on inertial system |
| CN112362044A (en) * | 2020-11-03 | 2021-02-12 | 北京无限向溯科技有限公司 | Indoor positioning method, device, equipment and system |
| CN113188546A (en) * | 2021-04-30 | 2021-07-30 | 成都市微泊科技有限公司 | Indoor positioning navigation method based on image recognition and pedestrian dead reckoning |
Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102506880A (en) * | 2011-10-28 | 2012-06-20 | 深圳市路畅科技有限公司 | Method for matching global positioning system (GPS) coordinate and coordinate on road in vector map |
| CN103076619A (en) * | 2012-12-27 | 2013-05-01 | 山东大学 | System and method for performing indoor and outdoor 3D (Three-Dimensional) seamless positioning and gesture measuring on fire man |
| TW201350795A (en) * | 2012-04-10 | 2013-12-16 | Qualcomm Inc | Map modification using ground-truth measurements |
| CN104236564A (en) * | 2013-06-14 | 2014-12-24 | 现代Mnsoft公司 | Method for performing map matching in user terminal |
| CN104864871A (en) * | 2015-05-27 | 2015-08-26 | 重庆大学 | Indoor positioning and path leading method based on mobile terminal inertial navigation |
| CN104914874A (en) * | 2015-06-09 | 2015-09-16 | 长安大学 | Unmanned aerial vehicle attitude control system and method based on self-adaption complementation fusion |
| CN105115497A (en) * | 2015-09-17 | 2015-12-02 | 南京大学 | Reliable indoor mobile robot precise navigation positioning system and method |
| CN105606102A (en) * | 2016-01-27 | 2016-05-25 | 中国地质大学（武汉） | Grid model based PDR indoor positioning method and system |
| KR20160094021A (en) * | 2015-01-30 | 2016-08-09 | 한국과학기술연구원 | Map-matching device and method for pedestrian indoor navigation |
| CN106289282A (en) * | 2016-07-18 | 2017-01-04 | 北京方位捷讯科技有限公司 | A kind of indoor map pedestrian's track matching method |
| CN106840163A (en) * | 2016-12-29 | 2017-06-13 | 上海斐讯数据通信技术有限公司 | A kind of indoor orientation method and system |
| CN106969772A (en) * | 2017-04-10 | 2017-07-21 | 南京大学 | A kind of seeing-eye dog method based on cell phone platform |
| CN107084718A (en) * | 2017-04-14 | 2017-08-22 | 桂林电子科技大学 | Indoor orientation method based on pedestrian's reckoning |
| CN107094319A (en) * | 2016-02-17 | 2017-08-25 | 王庆文 | A kind of high-precision indoor and outdoor fusion alignment system and method |
| CN107218938A (en) * | 2017-05-22 | 2017-09-29 | 南京航空航天大学 | The Wearable pedestrian navigation localization method and equipment aided in based on modelling of human body motion |
| CN107990895A (en) * | 2017-11-08 | 2018-05-04 | 北京工商大学 | A kind of building floor gap pedestrian track tracking and system based on wearable IMU |
| CN108362282A (en) * | 2018-01-29 | 2018-08-03 | 哈尔滨工程大学 | A kind of inertia pedestrian's localization method based on the adjustment of adaptive zero-speed section |
| CN108444473A (en) * | 2018-03-20 | 2018-08-24 | 南京华苏科技有限公司 | Track localization method in a kind of pedestrian room |
| CN108871333A (en) * | 2018-05-31 | 2018-11-23 | 金华航大北斗应用技术有限公司 | Step-length real-time computing technique based on indoor plane figure topology information |
| CN108957510A (en) * | 2018-07-25 | 2018-12-07 | 南京航空航天大学 | Based on inertia/zero-speed/GPS pedestrian is seamless combined navigation locating method |
| CN109115209A (en) * | 2018-07-20 | 2019-01-01 | 湖南格纳微信息科技有限公司 | Personnel positioning method and device in a kind of piping lane |
-
2019
- 2019-03-08 CN CN201910176373.7A patent/CN109708647A/en active Pending
Patent Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102506880A (en) * | 2011-10-28 | 2012-06-20 | 深圳市路畅科技有限公司 | Method for matching global positioning system (GPS) coordinate and coordinate on road in vector map |
| TW201350795A (en) * | 2012-04-10 | 2013-12-16 | Qualcomm Inc | Map modification using ground-truth measurements |
| CN103076619A (en) * | 2012-12-27 | 2013-05-01 | 山东大学 | System and method for performing indoor and outdoor 3D (Three-Dimensional) seamless positioning and gesture measuring on fire man |
| CN104236564A (en) * | 2013-06-14 | 2014-12-24 | 现代Mnsoft公司 | Method for performing map matching in user terminal |
| KR20160094021A (en) * | 2015-01-30 | 2016-08-09 | 한국과학기술연구원 | Map-matching device and method for pedestrian indoor navigation |
| CN104864871A (en) * | 2015-05-27 | 2015-08-26 | 重庆大学 | Indoor positioning and path leading method based on mobile terminal inertial navigation |
| CN104914874A (en) * | 2015-06-09 | 2015-09-16 | 长安大学 | Unmanned aerial vehicle attitude control system and method based on self-adaption complementation fusion |
| CN105115497A (en) * | 2015-09-17 | 2015-12-02 | 南京大学 | Reliable indoor mobile robot precise navigation positioning system and method |
| CN105606102A (en) * | 2016-01-27 | 2016-05-25 | 中国地质大学（武汉） | Grid model based PDR indoor positioning method and system |
| CN107094319A (en) * | 2016-02-17 | 2017-08-25 | 王庆文 | A kind of high-precision indoor and outdoor fusion alignment system and method |
| CN106289282A (en) * | 2016-07-18 | 2017-01-04 | 北京方位捷讯科技有限公司 | A kind of indoor map pedestrian's track matching method |
| CN106840163A (en) * | 2016-12-29 | 2017-06-13 | 上海斐讯数据通信技术有限公司 | A kind of indoor orientation method and system |
| CN106969772A (en) * | 2017-04-10 | 2017-07-21 | 南京大学 | A kind of seeing-eye dog method based on cell phone platform |
| CN107084718A (en) * | 2017-04-14 | 2017-08-22 | 桂林电子科技大学 | Indoor orientation method based on pedestrian's reckoning |
| CN107218938A (en) * | 2017-05-22 | 2017-09-29 | 南京航空航天大学 | The Wearable pedestrian navigation localization method and equipment aided in based on modelling of human body motion |
| CN107990895A (en) * | 2017-11-08 | 2018-05-04 | 北京工商大学 | A kind of building floor gap pedestrian track tracking and system based on wearable IMU |
| CN108362282A (en) * | 2018-01-29 | 2018-08-03 | 哈尔滨工程大学 | A kind of inertia pedestrian's localization method based on the adjustment of adaptive zero-speed section |
| CN108444473A (en) * | 2018-03-20 | 2018-08-24 | 南京华苏科技有限公司 | Track localization method in a kind of pedestrian room |
| CN108871333A (en) * | 2018-05-31 | 2018-11-23 | 金华航大北斗应用技术有限公司 | Step-length real-time computing technique based on indoor plane figure topology information |
| CN109115209A (en) * | 2018-07-20 | 2019-01-01 | 湖南格纳微信息科技有限公司 | Personnel positioning method and device in a kind of piping lane |
| CN108957510A (en) * | 2018-07-25 | 2018-12-07 | 南京航空航天大学 | Based on inertia/zero-speed/GPS pedestrian is seamless combined navigation locating method |
Non-Patent Citations (6)
| Title |
|---|
| 尹航: "使用MEMS惯性测量单元和拓扑地图的室内定位与导航技术研究", 《中国优秀硕士学位论文全文数据库 (信息科技辑)》 * |
| 王旭凤: "基于惯性导航的室内定位系统的研究", 《中国优秀硕士学位论文全文数据库 (信息科技辑)》 * |
| 胡东旭: "基于手机惯性传感器的室内轨迹跟踪技术研究", 《中国优秀博硕士学位论文全文数据库(硕士)信息科技辑》 * |
| 胡安冬等: "一种基于地图匹配辅助行人航位推算的室内定位方法", 《测绘科学技术学报》 * |
| 赵小平等: "蓝牙和地图辅助行人航位推算的室内定位系统", 《测绘科学》 * |
| 陈波等: "一种基于网络拓扑关系的地图匹配算法", 《测绘科学技术学报》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110686682A (en) * | 2019-11-15 | 2020-01-14 | 北京理工大学 | Indoor pedestrian course fusion constraint algorithm based on inertial system |
| CN112362044A (en) * | 2020-11-03 | 2021-02-12 | 北京无限向溯科技有限公司 | Indoor positioning method, device, equipment and system |
| CN113188546A (en) * | 2021-04-30 | 2021-07-30 | 成都市微泊科技有限公司 | Indoor positioning navigation method based on image recognition and pedestrian dead reckoning |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103776446B (en) | A kind of pedestrian's independent navigation computation based on double MEMS-IMU | |
| CN109991636A (en) | Map constructing method and system based on GPS, IMU and binocular vision | |
| CN110095116A (en) | A kind of localization method of vision positioning and inertial navigation combination based on LIFT | |
| CN105910601B (en) | A kind of indoor ground magnetic positioning method based on Hidden Markov Model | |
| CN104655131B (en) | Inertial navigation Initial Alignment Method based on ISTSSRCKF | |
| RU2558724C2 (en) | Diagnostic complex for determination of pipeline position, and method for determining relative displacement of pipeline as per results of two and more inspection passes of diagnostic complex for determination of pipelines position | |
| CN106979780B (en) | A kind of unmanned vehicle real-time attitude measurement method | |
| CN107909614B (en) | Positioning method of inspection robot in GPS failure environment | |
| CN103791902B (en) | It is applicable to the star sensor autonomous navigation method of high motor-driven carrier | |
| CN109807911B (en) | Outdoor patrol robot multi-environment combined positioning method based on GNSS, UWB, IMU, laser radar and code disc | |
| CN108955675A (en) | A kind of underground piping track detection system and method based on inertia measurement | |
| CN109708647A (en) | A kind of indoor topological map pedestrian localization method based on fusion feature element | |
| CN105241445A (en) | Method and system for acquiring indoor navigation data based on intelligent mobile terminal | |
| CN103453901B (en) | A kind of position guidance system and position guidance method | |
| CN108180923B (en) | Inertial navigation positioning method based on human body odometer | |
| CN102128625A (en) | Initial matching method for use in gravimetric map matching in gravity-aided inertial navigation system | |
| CN109470238A (en) | A kind of localization method, device and mobile terminal | |
| CN111025366B (en) | Grid SLAM navigation system and method based on INS and GNSS | |
| CN109459028A (en) | A kind of adaptive step estimation method based on gradient decline | |
| CN109612463A (en) | A kind of pedestrian navigation localization method based on side velocity constrained optimization | |
| CN107677267A (en) | Indoor pedestrian navigation course feedback modifiers method based on MEMS IMU | |
| CN110207692A (en) | A kind of inertia pre-integration pedestrian navigation method of map auxiliary | |
| CN109764870A (en) | Carrier initial heading evaluation method based on transformation estimator modeling scheme | |
| CN108592907A (en) | A kind of quasi real time step-by-step movement pedestrian navigation method based on bidirectional filtering smoothing technique | |
| KR101301462B1 (en) | Pedestiran dead-reckoning apparatus using low cost inertial measurement unit and method thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190503 |
|
| RJ01 | Rejection of invention patent application after publication |