CN110487270A - A kind of indoor human body localization method based on wearable Inertial Measurement Unit and infrared sensor network - Google Patents
A kind of indoor human body localization method based on wearable Inertial Measurement Unit and infrared sensor network Download PDFInfo
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- 230000005021 gait Effects 0.000 claims abstract description 13
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- 238000009792 diffusion process Methods 0.000 claims description 3
- 210000004197 pelvis Anatomy 0.000 claims description 3
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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
- G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
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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
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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
- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J5/0022—Radiation pyrometry, e.g. infrared or optical thermometry for sensing the radiation of moving bodies
- G01J5/0025—Living bodies
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J5/10—Radiation pyrometry, e.g. infrared or optical thermometry using electric radiation detectors
- G01J5/34—Radiation pyrometry, e.g. infrared or optical thermometry using electric radiation detectors using capacitors, e.g. pyroelectric capacitors
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
- H04B10/11—Arrangements specific to free-space transmission, i.e. transmission through air or vacuum
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Abstract
The invention discloses a kind of indoor human body localization method based on wearable Inertial Measurement Unit and infrared sensor network, belong to electronic location field, this method, which is specifically included, obtains exercise data by wearable Inertial Measurement Unit, the data for constructing modelling of human body motion, being observed using the infrared sensor network in environment, fusion indoor map information are reduced accumulated error and using positioning blending algorithm realization human body indoor accurate positions.The present invention observes data using infrared sensor network, it merges indoor map information and carries out precision indoor positioning, modelling of human body motion algorithm constructs the motion model for wearing bracelet personnel by Gait Recognition, step-size estimation and course estimation, auxiliary positioning is carried out using the infrared sensor network arranged in environment, eliminate the error because of time integral, positioning accuracy is further increased, determines position of human body finally by locating and tracking blending algorithm.
Description
Technical field
The invention belongs to electronic location technical fields, and in particular to one kind is based on wearable Inertial Measurement Unit and infrared biography
The indoor human body localization method of sensor network.
Background technique
China steps into astogeny society since new century, and the quality of life of the elderly and guarantee of living on one's own life, which become, asks
Topic, smart home can solve these demands, much be needed in smart home product based on by the position letter of attendant
Breath.Traditional GPS global network positioning system may be implemented to position well in outdoor, there is the metals such as steel structure, household electrical appliances indoors
The interference of material and the decaying of signal strength cause interior to can not achieve accurate positioning.
Summary of the invention
The purpose of the present invention is to provide a kind of interior based on wearable Inertial Measurement Unit and infrared sensor network
Human body localization method, to solve the problems mentioned in the above background technology.
To achieve the above object, the invention provides the following technical scheme:
A kind of indoor human body localization method based on wearable Inertial Measurement Unit and infrared sensor network, this method tool
Body includes the following steps:
S1, acceleration, the angular velocity data that movement is obtained by wearable Inertial Measurement Unit, construct modelling of human body motion；
S2, the new nodes of locations data observed using the infrared sensor network in environment, fusion indoor map letter
Breath reduces accumulation nodes of locations error；
S3, human body indoor accurate position is realized using positioning blending algorithm.
As a preferred embodiment, wearable Inertial Measurement Unit is fixed on waist pelvis position in the S1
It sets, the algorithm of the building modelling of human body motion is that improved pedestrian's line position calculates algorithm.
As a preferred embodiment, improved pedestrian's line position calculates that algorithm includes the following steps:
A, using the Gait Recognition of double adaptive threshold value, original acceleration amplitude is obtained using sensor；
B, high-frequency noise and spine are removed using low-pass filtering smoothing processing；
C, Gait Recognition is carried out by the size of the wave crest and trough of waveform after processing and threshold value, setting updates the limit of threshold value
Buffer function of the condition processed as energy jump.
As a preferred embodiment, in the step a, using the linear of the frequency and acceleration variance walked
Combination indicates step-length；Passed through by the sensor of wearable Inertial Measurement Unit to the angular speed integral estimation walking in vertical axis direction
When course angle variation.
As a preferred embodiment, the infrared sensor network configuration in environment is with mark in the S2
Pyroelectric infrared sensor node, one region of each nodal test, when the people in the infrared sensor region is from one
When region moves to another region, new node can be triggered, it is fixed that when new node information integrated environment map of triggering can be used for
Restrictive condition when position.
In above scheme, it should be noted that the probabilistic model of infrared triggering information accessibility are as follows:
In formula,For pyroelectric infrared sensor network observations value,It is the observation that newly triggers to timing
People existsThe probability of position,For positionAccessibility, as default Environmental Map Information.
As a preferred embodiment, locating and tracking blending algorithm includes the following steps: in the S3
1) acceleration, the angular velocity data obtained according to wearable Inertial Measurement Unit sensor is inputted, rpyroelectric infrared
Sensor network observation, cartographic information and resampling threshold value initialize the position, course and weight of particle, detection step
State；
2) step-length and course are estimated if detecting a step, according to the weight of diffusion particle more new particle, by particle weight
Normalization calculates integral particles virtual value；
If 3) particle virtual value is less than resampling threshold value, implements resampling, otherwise estimate and export the position of people.
Compared with prior art, the beneficial effects of the present invention are:
The present invention observes data using infrared sensor network, and fusion indoor map information carries out precision indoor positioning, people
Body motion model algorithm constructs the motion model for wearing bracelet personnel, benefit by Gait Recognition, step-size estimation and course estimation
Auxiliary positioning is carried out with the infrared sensor network arranged in environment, the error because of time integral is eliminated, further increases positioning
Precision determines position of human body finally by locating and tracking blending algorithm.
Detailed description of the invention
Fig. 1 is pyroelectric infrared sensor infrared node queuing message process flow diagram of the invention；
Fig. 2 is the algorithm flow chart of locating and tracking blending algorithm of the invention.
Specific embodiment
Below with reference to embodiment, the present invention will be further described.
The following examples are intended to illustrate the invention, but cannot be used to limit the scope of the invention.Item in embodiment
Part can be adjusted according to actual conditions are further, under concept thereof of the invention all to method simple modifications of the invention
Belong to the scope of protection of present invention.
The present invention provides a kind of indoor human body positioning side based on wearable Inertial Measurement Unit and infrared sensor network
Method, this method specifically comprise the following steps:
S1, acceleration, the angular velocity data that movement is obtained by wearable Inertial Measurement Unit, construct modelling of human body motion；
S2, the new nodes of locations data observed using the infrared sensor network in environment, fusion indoor map letter
Breath reduces accumulation nodes of locations error；
S3, human body indoor accurate position is realized using positioning blending algorithm.
In the present embodiment, modelling of human body motion algorithm constructs pendant by Gait Recognition, step-size estimation and course estimation
The motion model for wearing bracelet personnel carries out auxiliary positioning using the infrared sensor network arranged in environment, eliminates because of time product
Tired error, further increases positioning accuracy, determines position of human body finally by locating and tracking blending algorithm.
Specifically, wearable Inertial Measurement Unit is fixed on waist pelvis position in step S1, keep sensor
Good data coordinate system；The algorithm for constructing modelling of human body motion is that improved pedestrian's line position calculates algorithm, improved walking
Person's line position calculates that algorithm includes the following steps:
A, using the Gait Recognition of double adaptive threshold value, original acceleration amplitude is obtained using sensor；Original acceleration
Amplitude is calculated by the acceleration value on three axis:
C, Gait Recognition is carried out by the size of the wave crest and trough of waveform after processing and threshold value, setting updates the limit of threshold value
Buffer function of the condition processed as energy jump.
In formula, ax、ay、azAcceleration respectively in three reference axis of sensor；
B, original acceleration amplitude is smoothed removal high-frequency noise and spine by low-pass filter；
C, Gait Recognition is carried out by the size of the wave crest and trough of waveform after processing and threshold value, in a sliding window
The wave crest and trough for searching for signal waveform, if wave crest is more than threshold value THAnd trough is lower than threshold value TLIt is considered as a complete step, then makes
Use Vn-1、Vn、Pn、Pn-1Dynamically to update threshold value TH、TL, wherein Vn、PnFor back wave crest and valley value, Vn-1、Pn-1, for before more
The wave crest and valley value of one step；
Renewal process are as follows:
In formula, K is the restrictive condition for updating threshold value, TLFor Low threshold, THFor high threshold, C1, C2It is surveyed for coefficient by experiment
, setting K is Pn、Pn-1In lesser value, can be used as the buffer function of energy suddenly change.
More specifically, in step a, step-length S is indicated using the linear combination of the frequency and acceleration variance walkedk:
Sk=α Fk+β·ak+γ；
In formula, α, β, γ are previously obtained in calibration phase by experiment, FkAnd akFor frequency and the acceleration variance of walking:
In formula, tkAnd tk-1For the time that every step is detected, n andFor in a step period hits and acceleration it is equal
Value.
Changed by being placed on course angle of the sensor of waist by walking to the angular speed integral estimation in vertical axis direction when:
θk=θk-1+θt+θa；
θt=ωtT+θt-1+nt；
In formula, θt-1For the accumulation angle that a upper sampled point is, T is sampling period, ntFor white noise, N is current survival
Population, K are amendment course degree zoom factor；
Finally obtain modelling of human body motion are as follows:
In formula, LkPosition vector when being walked for kth, nkFor process noise.
Specifically, referring to Fig. 1, Fig. 1 is pyroelectric infrared sensor infrared node queuing message processing stream of the invention
Cheng Tu；Infrared sensor network use is with tagged pyroelectric infrared sensor, by sensor node separate configurations in smallpox
On plate, interior is divided into multiple rectangular areas, one rectangular area of each nodal test on ceiling, when indoor occupant from
One region can trigger new node when moving to another region, when new node information integrated environment map of triggering is used for positioning
Restrictive condition, infrared triggering information reachable probability model is defined as:
In formulaObservation newly to trigger exists to timing peopleThe probability of position,For position
Accessibility, as default Environmental Map Information.
More specifically, modelling of human body motion is constructed by the acceleration that wearable Inertial Measurement Unit sensor is moved
And angular velocity data, it determines whether that new node triggers in conjunction with infrared sensing network, judges whether to deposit in buffer queue if having
If whether the node that judgement triggers earliest is more than threshold value there are the time, if there is removal queue, if not having without new node triggering
Have and judge whether to terminate, terminates if terminating, it is above-mentioned to judge whether exist in buffer queue, queue is then added if it exists, moves
To queue tail, continue to determine whether to trigger the time existing for node earliest more than threshold value.
Specifically, referring to Fig. 2, locating and tracking blending algorithm includes the following steps:
1) acceleration, the angular velocity data obtained according to wearable Inertial Measurement Unit sensor is inputted, rpyroelectric infrared
Sensor network observation, cartographic information and resampling threshold value initialize the position, course and weight of particle, detection step
State；
2) step-length and course are estimated if detecting a step, according to the weight of diffusion particle more new particle, by particle weight
Normalization calculates integral particles virtual value；
If 3) particle virtual value is less than resampling threshold value, implements resampling, otherwise estimate and export the position of people.
More specifically, position of human body is determined by locating and tracking blending algorithm, referring to Fig. 2, Fig. 2 is positioning of the invention
Track the algorithm flow chart of blending algorithm；The initial position course weight for initializing each particle carries out gait inspection according to formula
It surveys, continues to test if can't detect, predicted if detecting, estimation obtains step-length, and grain is spread further according to formula in course
Son, more new particle weight, normalized calculate particle entirety virtual value, judge whether to be greater than threshold value, if more than output people's
Position continues gait detection if being less than.
It although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of variations, modification, replacement can be carried out to these embodiments without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (6)
1. a kind of indoor human body localization method based on wearable Inertial Measurement Unit and infrared sensor network, feature exist
In this method specifically comprises the following steps:
S1, acceleration, the angular velocity data that movement is obtained by wearable Inertial Measurement Unit, construct modelling of human body motion；
S2, the new nodes of locations data observed using the infrared sensor network in environment, fusion indoor map information are subtracted
Small accumulation nodes of locations error；
S3, human body indoor accurate position is realized using positioning blending algorithm.
2. according to claim 1 positioned based on the indoor human body of wearable Inertial Measurement Unit and infrared sensor network
Method, which is characterized in that in the S1, wearable Inertial Measurement Unit is fixed on waist pelvis position, the building people
The algorithm of body motion model is that improved pedestrian's line position calculates algorithm.
3. according to claim 2 positioned based on the indoor human body of wearable Inertial Measurement Unit and infrared sensor network
Method, which is characterized in that improved pedestrian's line position calculates that algorithm includes the following steps:
A, using the Gait Recognition of double adaptive threshold value, original acceleration amplitude is obtained using sensor；
B, high-frequency noise and spine are removed using low-pass filtering smoothing processing；
C, Gait Recognition is carried out by the size of the wave crest and trough of waveform after processing and threshold value, setting updates the limitation item of threshold value
Buffer function of the part as energy jump.
4. according to claim 3 positioned based on the indoor human body of wearable Inertial Measurement Unit and infrared sensor network
Method, which is characterized in that in the step a, step-length is indicated using the linear combination of the frequency and acceleration variance walked；By
The course angle when sensor of wearable Inertial Measurement Unit is by walking to the angular speed integral estimation in vertical axis direction changes.
5. according to claim 1 positioned based on the indoor human body of wearable Inertial Measurement Unit and infrared sensor network
Method, which is characterized in that in the S2, the infrared sensor network configuration in environment is sensed with tagged rpyroelectric infrared
Device node, one region of each nodal test, when the people in infrared sensor region moves to another area from a region
When domain, new node can be triggered, the restrictive condition when new node information integrated environment map of triggering can be used for positioning.
6. according to claim 1 positioned based on the indoor human body of wearable Inertial Measurement Unit and infrared sensor network
Method, which is characterized in that in the S3, locating and tracking blending algorithm includes the following steps:
1) acceleration, the angular velocity data obtained according to wearable Inertial Measurement Unit sensor is inputted, rpyroelectric infrared sensing
Device network observations value, cartographic information and resampling threshold value initialize the position, course and weight of particle, detect gait；
2) step-length and course are estimated if detecting a step, according to the weight of diffusion particle more new particle, by particle weight normalizing
Change, calculates integral particles virtual value；
If 3) particle virtual value is less than resampling threshold value, implements resampling, otherwise estimate and export the position of people.
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| CN117824624A (en) * | 2024-03-05 | 2024-04-05 | 深圳市瀚晖威视科技有限公司 | Indoor tracking and positioning method, system and storage medium based on face recognition |
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| US20120232792A1 (en) * | 2011-03-08 | 2012-09-13 | Seiko Epson Corporation | Positioning apparatus and positioning method |
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