CN104296749A - Motion state perception-based low power consumption positioning method and system - Google Patents
Motion state perception-based low power consumption positioning method and system Download PDFInfo
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- 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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Abstract
The invention discloses a motion state perception-based low power consumption positioning method and system. The method comprises the following steps: carrying out offline training and online positioning; providing a low power consumption positioning service through introducing an acceleration sensor, wherein the acceleration sensor is capable of capturing the vibration changes in the X, Y and Z directions caused by the motion of the user; calculating the motion state and position change of the user through massive sample training and a machine learning method; providing a low power consumption position service with a certain positioning error; opening a GPS to complete precise positioning when the positioning error exceeds a certain threshold. According to the motion state perception-based low power consumption positioning method and system, the acceleration sensor with low power consumption is used for completing most of the positioning, so that the overall positioning power consumption can be greatly reduced.
Description
Technical field
The present invention relates to GPS field of locating technology, particularly relate to a kind of low-power consumption localization method based on motion state perception and system.
Background technology
Along with the development of mobile interchange networking industry, location-based service has become an important indicator of mobile terminal, for daily life location, navigation provide a great convenience.
GPS location mainly comprises two parts: one is receiver user, and another is gps satellite constellation.The continuous broadcast satellite signals outward of satellite constellation, receiver user receives more than 4 effective satellite-signals, can calculate current location.
At present, the wearable devices such as such as automobile mounted positioning system, smart mobile phone, intelligent watch, intelligent glasses, Intelligent bracelet all need extensive integrated positioning module to provide location-based service, usual various product can integrated gps system, can provide about 10 meters of positioning precision services.
But the power consumption of GPS module and Big Dipper module is very large, and about 160mW, is only second to screen and 3G communication module in intelligent terminal.Experiment display, smart mobile phone only can provide the GPS positioning service of continuous 5-6 hour, and the intelligent watch of up-to-date release can only provide the GPS positioning service of 2-3 hours, is difficult to meet the long-time location requirement of user.
Therefore, for above-mentioned technical matters, be necessary to provide a kind of low-power consumption localization method based on motion state perception and system.
Summary of the invention
In view of this, a kind of low-power consumption localization method based on motion state perception of the present invention and system mainly solve the power problems of actual GPS position fixing process, provide low-power consumption positioning service by introducing an acceleration transducer.Specifically, acceleration transducer can catch the vibration change in XYZ tri-directions that user movement causes in real time, user movement state and change in location is calculated by great amount of samples training and machine learning method, providing package is containing the low-power consumption location-based service of certain positioning error, when positioning error exceedes certain threshold value, then open GPS and complete and once accurately locate.
In order to achieve the above object, the technical scheme that provides of the embodiment of the present invention is as follows:
Based on a low-power consumption localization method for motion state perception, described method comprises:
S1, off-line training;
S11, standard data acquisition, acceleration information corresponding under gathering each standard movement state by acceleration transducer;
S12, user movement state learn, and extract proper vector to distinguish each standard movement state, obtain the corresponding relation of standard movement state and acceleration information waveform, set up off-line training model from acceleration information;
S2, tuning on-line;
The acquisition and processing of S21, user movement data, the acceleration information caused by acceleration transducer Real-time Collection user movement;
S22, user movement state analysis and Displacement Analysis, characteristic vector pickup is carried out to the acceleration information of current collection, use off-line training model to calculate the motion state of user, and acceleration information is calculated, obtain the change in displacement in a period of time and displacement cumulative errors.
S23, opportunistic GPS locate, and judge whether described displacement cumulative errors exceed threshold value, if so, then open GPS and re-start location, and restart acceleration transducer, return step S21 and start tuning on-line; If not, then directly return step S21 and start tuning on-line.
As a further improvement on the present invention, the standard movement state in described step S11 comprise walk, run, static; Motion state in described step S22 comprise walk, run, static.
As a further improvement on the present invention, described step S11 and step S21 also comprises:
Remove the data fluctuations due to external noise introducing in acceleration information, obtain the acceleration information of smooth change.
As a further improvement on the present invention, described step S11 and step S21 also comprises:
Use low-pass filter to remove high frequency noise, obtain the acceleration information of smooth change.
As a further improvement on the present invention, the proper vector in described step S12 comprises: the minimum value of acceleration, maximal value, median, mean value, variance, degree of tilt and Fourier energy in a period of time.
As a further improvement on the present invention, the proper vector in a described step S12 is classified by SVM method, obtains the corresponding relation of motion state and acceleration information waveform, sets up SVM model.
As a further improvement on the present invention, described step S22 is specially:
Carry out characteristic vector pickup to the acceleration information of current collection, proper vector comprises the minimum value of acceleration in a period of time, maximal value, median, mean value, variance, degree of tilt and Fourier energy;
The SVM model adopting off-line training to establish, calculates the motion state of user;
Quadratic integral is carried out to acceleration information, obtains the change in displacement in a period of time
Displacement cumulative errors e (t) is obtained, e (t)=Kalman (a'(t), s (t)) with kalman filter method.
Correspondingly, a kind of low-power consumption positioning system based on motion state perception, described system comprises:
Off-line training module, for:
Standard data acquisition, acceleration information corresponding under gathering each standard movement state by acceleration transducer;
User movement state learns, and extracts proper vector to distinguish each standard movement state, obtain the corresponding relation of standard movement state and acceleration information waveform, set up off-line training model from acceleration information;
Tuning on-line module, for:
The acquisition and processing of user movement data, the acceleration information caused by acceleration transducer Real-time Collection user movement;
User movement state analysis and Displacement Analysis, characteristic vector pickup is carried out to the acceleration information of current collection, use off-line training model to calculate the motion state of user, and acceleration information is calculated, obtain the change in displacement in a period of time and displacement cumulative errors.
Opportunistic GPS locates, and judges whether described displacement cumulative errors exceed threshold value, if so, then opens GPS and re-start location, and restart acceleration transducer, starts tuning on-line; If not, then directly tuning on-line is started.
The present invention has following beneficial effect:
Use the acceleration transducer of low-power consumption to come major part location, overall location power consumption can be reduced;
The various different motion state of acceleration transducer off-line learning, tuning on-line mainly uses acceleration to do position calculation, seldom uses GPS module;
According to actual location requirement, different cumulative errors threshold values can be selected, and then meets different location requirement.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, the accompanying drawing that the following describes is only some embodiments recorded in the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the process flow diagram of a kind of low-power consumption localization method based on motion state perception of the present invention.
Embodiment
Technical scheme in the present invention is understood better in order to make those skilled in the art person, below in conjunction with the accompanying drawing in the embodiment of the present invention, technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, should belong to the scope of protection of the invention.
Shown in ginseng Fig. 1, the invention discloses a kind of low-power consumption localization method based on motion state perception, comprising:
S1, off-line training;
S11, standard data acquisition, acceleration information corresponding under gathering each standard movement state (comprise walk, run, static etc.) by acceleration transducer;
S12, user movement state learn, and extract proper vector to distinguish each standard movement state, obtain the corresponding relation of standard movement state and acceleration information waveform, set up off-line training model from acceleration information;
S2, tuning on-line;
The acquisition and processing of S21, user movement data, the acceleration information caused by acceleration transducer Real-time Collection user movement;
S22, user movement state analysis and Displacement Analysis, characteristic vector pickup is carried out to the acceleration information of current collection, off-line training model is used to calculate the motion state (comprise walk, run, static etc.) of user, and acceleration information is calculated, obtain the change in displacement in a period of time and displacement cumulative errors.
S23, opportunistic GPS locate, and judge whether described displacement cumulative errors exceed threshold value, if so, then open GPS and re-start location, and restart acceleration transducer, return step S21 and start tuning on-line; If not, then directly return step S21 and start tuning on-line.
Correspondingly, a kind of low-power consumption positioning system based on motion state perception, this system comprises:
Off-line training module, for:
Standard data acquisition, acceleration information corresponding under gathering each standard movement state by acceleration transducer;
User movement state learns, and extracts proper vector to distinguish each standard movement state, obtain the corresponding relation of standard movement state and acceleration information waveform, set up off-line training model from acceleration information;
Tuning on-line module, for:
The acquisition and processing of user movement data, the acceleration information caused by acceleration transducer Real-time Collection user movement;
User movement state analysis and Displacement Analysis, characteristic vector pickup is carried out to the acceleration information of current collection, use off-line training model to calculate the motion state of user, and acceleration information is calculated, obtain the change in displacement in a period of time and displacement cumulative errors.
Opportunistic GPS locates, and judges whether described displacement cumulative errors exceed threshold value, if so, then opens GPS and re-start location, and restart acceleration transducer, starts tuning on-line; If not, then directly tuning on-line is started.
The present invention is mainly used in the power problems solving mobile terminal GPS location, introduces acceleration transducer and a series of new location algorithm, can provide continuous print hi-Fix.At actual location algorithm, acceleration can the motion conditions in perception user XYZ tri-directions, first by great amount of samples training and the machine learning method of off-line training, sets up corresponding relation between acceleration information and motion state.In locating in real time, gather acceleration transducer and directly calculate motion state and change in displacement, as long as when displacement error is larger, just need a GPS location.
In of the present invention one specifically strength, detailed off-line training and tuning on-line process as follows:
S1, off-line training
S11, standard data acquisition:
Degree of will speed up sensor is bundled on tester's health, and straight down, X-axis is along working direction, and Y-axis is along laterally and vertical with X-axis for Z axis.Tester completes the walking of standard, runs, the state such as static, acceleration transducer continuous capturing some sections of acceleration informations, suppose that XYZ tri-directional accelerations are respectively: a (t)=[x (t) y (t) z (t)].
Because raw acceleration data comprises a large amount of high frequency noise, use low-pass filter f (t) to remove high frequency noise respectively, obtain the acceleration information of smooth change, i.e. a'(t)=a (t) * f (t).
S12, user movement state learn:
Because the Acceleration pulse of different motion state is different, needs to extract some to characterize the proper vector of different conditions, comprise the minimum value of acceleration in a period of time, maximal value, median, mean value, variance, degree of tilt, Fourier energy etc.
That is: v (t)=[min (a (t)) max (a (t)) median (a (t)) mean (a (t)) var (a (t)) fft (a (t))].
Then use SVM method to classify, obtain the corresponding relation of motion state and acceleration information waveform.
S2, tuning on-line
The acquisition and processing of S21, user movement data:
The weak vibration situation in XYZ tri-directions caused by an acceleration transducer Real-time Collection user movement (as walked, running etc.), its acceleration information is: a (t)=[x (t) y (t) z (t)].
To the acceleration information analysis in a period of time, the data fluctuations of external high frequency noise introducing is removed with low-pass filter f (t), obtain the acceleration information of one section of comparatively smooth change, i.e. a'(t)=a (t) * f (t).
S22, user movement state analysis and Displacement Analysis:
Characteristic vector pickup is carried out to the acceleration information of the current collection of user, comprises the minimum value of acceleration in a period of time, maximal value, median, mean value, variance, degree of tilt, Fourier energy etc.:
v(t)＝[min(a(t))?max(a(t))?median(a(t))?mean(a(t))?var(a(t))?fft(a(t))]。
The SVM model established with off-line training, calculates the motion state (as walked, running, static) of user.
Then, quadratic integral is carried out to acceleration information, obtains the change in displacement s (t) in a period of time:
Finally, displacement cumulative errors e (t) is obtained with kalman filter method:
e(t)＝Kalman(a'(t),s(t))。
S23, opportunistic GPS locate:
If displacement cumulative errors e (t) is less than the threshold value T of setting, then jump to step S21, start the tuning on-line of next time;
If displacement cumulative errors e (t) is more than or equal to the threshold value T of setting, then open a GPS, obtain a comparatively accurate position location, then acceleration transducer is restarted, jump to step S21, restart a tuning on-line process, that is:
Ife(t)<T，gotoS21；
Else，openGPS,gotoS21。
As can be seen from above embodiment, the present invention has following beneficial effect:
Use the acceleration transducer of low-power consumption to come major part location, overall location power consumption can be reduced;
The various different motion state of acceleration transducer off-line learning, tuning on-line mainly uses acceleration to do position calculation, seldom uses GPS module;
According to actual location requirement, different cumulative errors threshold values can be selected, and then meets different location requirement.
To those skilled in the art, obviously the invention is not restricted to the details of above-mentioned one exemplary embodiment, and when not deviating from spirit of the present invention or essential characteristic, the present invention can be realized in other specific forms.Therefore, no matter from which point, all should embodiment be regarded as exemplary, and be nonrestrictive, scope of the present invention is limited by claims instead of above-mentioned explanation, and all changes be therefore intended in the implication of the equivalency by dropping on claim and scope are included in the present invention.Any Reference numeral in claim should be considered as the claim involved by limiting.
In addition, be to be understood that, although this instructions is described according to embodiment, but not each embodiment only comprises an independently technical scheme, this narrating mode of instructions is only for clarity sake, those skilled in the art should by instructions integrally, and the technical scheme in each embodiment also through appropriately combined, can form other embodiments that it will be appreciated by those skilled in the art that.
Claims (8)
1. based on a low-power consumption localization method for motion state perception, it is characterized in that, described method comprises:
S1, off-line training;
S11, standard data acquisition, acceleration information corresponding under gathering each standard movement state by acceleration transducer;
S12, user movement state learn, and extract proper vector to distinguish each standard movement state, obtain the corresponding relation of standard movement state and acceleration information waveform, set up off-line training model from acceleration information;
S2, tuning on-line;
The acquisition and processing of S21, user movement data, the acceleration information caused by acceleration transducer Real-time Collection user movement;
S22, user movement state analysis and Displacement Analysis, characteristic vector pickup is carried out to the acceleration information of current collection, use off-line training model to calculate the motion state of user, and acceleration information is calculated, obtain the change in displacement in a period of time and displacement cumulative errors.
S23, opportunistic GPS locate, and judge whether described displacement cumulative errors exceed threshold value, if so, then open GPS and re-start location, and restart acceleration transducer, return step S21 and start tuning on-line; If not, then directly return step S21 and start tuning on-line.
2. method according to claim 1, is characterized in that, the standard movement state in described step S11 comprise walk, run, static; Motion state in described step S22 comprise walk, run, static.
3. method according to claim 1, is characterized in that, described step S11 and step S21 also comprises:
Remove the data fluctuations due to external noise introducing in acceleration information, obtain the acceleration information of smooth change.
4. method according to claim 3, is characterized in that, described step S11 and step S21 also comprises:
Use low-pass filter to remove high frequency noise, obtain the acceleration information of smooth change.
5. method according to claim 1, is characterized in that, the proper vector in described step S12 comprises: the minimum value of acceleration, maximal value, median, mean value, variance, degree of tilt and Fourier energy in a period of time.
6. method according to claim 5, is characterized in that, the proper vector in a described step S12 is classified by SVM method, obtains the corresponding relation of motion state and acceleration information waveform, sets up SVM model.
7. method according to claim 6, is characterized in that, described step S22 is specially:
Carry out characteristic vector pickup to the acceleration information of current collection, proper vector comprises the minimum value of acceleration in a period of time, maximal value, median, mean value, variance, degree of tilt and Fourier energy;
The SVM model adopting off-line training to establish, calculates the motion state of user;
Quadratic integral is carried out to acceleration information, obtains the change in displacement s (t) in a period of time,
Displacement cumulative errors e (t) is obtained, e (t)=Kalman (a'(t), s (t)) with kalman filter method.
8., as claimed in claim 1 based on a low-power consumption positioning system for motion state perception, it is characterized in that, described system comprises:
Off-line training module, for:
Standard data acquisition, acceleration information corresponding under gathering each standard movement state by acceleration transducer;
User movement state learns, and extracts proper vector to distinguish each standard movement state, obtain the corresponding relation of standard movement state and acceleration information waveform, set up off-line training model from acceleration information;
Tuning on-line module, for:
The acquisition and processing of user movement data, the acceleration information caused by acceleration transducer Real-time Collection user movement;
User movement state analysis and Displacement Analysis, characteristic vector pickup is carried out to the acceleration information of current collection, use off-line training model to calculate the motion state of user, and acceleration information is calculated, obtain the change in displacement in a period of time and displacement cumulative errors.
Opportunistic GPS locates, and judges whether described displacement cumulative errors exceed threshold value, if so, then opens GPS and re-start location, and restart acceleration transducer, starts tuning on-line; If not, then directly tuning on-line is started.
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| CN104614749A (en) * | 2015-02-10 | 2015-05-13 | 上海美迪索科电子科技有限公司 | Low-power-consumption positioning method based on motion posture |
| CN104677351A (en) * | 2015-01-26 | 2015-06-03 | 泰科智慧科技（北京）有限公司 | Personnel positioning system and method based on multiple signal fusion |
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| CN106441290B (en) * | 2016-09-14 | 2019-04-12 | 南京理工大学 | A kind of indoor orientation method dynamically adjusted in real time based on moving direction |
| CN108008151A (en) * | 2017-11-09 | 2018-05-08 | 惠州市德赛工业研究院有限公司 | A kind of moving state identification method and system based on 3-axis acceleration sensor |
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| CN108981744B (en) * | 2018-08-06 | 2020-07-07 | 浙江大学 | Step frequency real-time calculation method based on machine learning and low-pass filtering |
| CN109375762A (en) * | 2018-09-27 | 2019-02-22 | 北京奇虎科技有限公司 | A kind of method, apparatus and terminal reducing power consumption |
| CN110180158A (en) * | 2019-07-02 | 2019-08-30 | 乐跑体育互联网（武汉）有限公司 | A kind of running state identification method, system and terminal device |
| CN112637758A (en) * | 2020-08-05 | 2021-04-09 | 华为技术有限公司 | Equipment positioning method and related equipment thereof |
| CN112637758B (en) * | 2020-08-05 | 2022-09-09 | 华为技术有限公司 | Equipment positioning method and related equipment thereof |
| CN113824461A (en) * | 2021-08-04 | 2021-12-21 | 惠州Tcl云创科技有限公司 | Positioning method and system based on smart watch and mobile terminal |
| CN114513752A (en) * | 2021-12-30 | 2022-05-17 | 山东信通电子股份有限公司 | Mobile terminal positioning control method, equipment and medium |
| CN114513752B (en) * | 2021-12-30 | 2024-02-27 | 山东信通电子股份有限公司 | Mobile terminal positioning control method, mobile terminal positioning control equipment and mobile terminal positioning control medium |
| CN116224387A (en) * | 2023-05-09 | 2023-06-06 | 深圳市易赛通信技术有限公司 | Positioning method, device and equipment of wearable equipment and storage medium |
| CN116224387B (en) * | 2023-05-09 | 2023-07-07 | 深圳市易赛通信技术有限公司 | Positioning method, device and equipment of wearable equipment and storage medium |
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