CN104597469B - Intelligent positioning method based on GPS/AGPS/GPSOne and target behavior characteristics - Google Patents

Abstract

The invention discloses an intelligent positioning method based on GPS/AGPS/GPSOne and target behavior characteristics and solves the problems of absence of acuity of group behavior characteristics and identification advantages of specific group positioning in the prior art. By the intelligent positioning method based on existing electronic maps, various areas are divided according to interest points, and according to the target behavior characteristics, weight is set for each stage of division; within error range of positioning, probability of the target in each interest point is calculated, the highest probability is used as a positioning result, the positioning result is low in error, and positioning accuracy is much superior to that existing positioning methods.

Description

Intelligent locating method based on GPS/AGPS/GPSOne and target behavior feature

Technical field

The present invention relates to a kind of localization method, specifically, it is to be related to one kind to be based on GPS/AGPS/GPSOne and target line The intelligent locating method being characterized.

Background technology

The openness improving constantly with society, the recurrent population increasingly increasing, also carry while promoting social development Carry out unsafe hidden danger.Middle and primary schools, the safety problem of kindergarten student are on the rise, the peace of each age level students Entirely become country, society, school and head of a family's focus of attention problem.At present the technological means of children's protection are mainly passed through The construction of technical precaution facility such as the monitoring within campus, antitheft, electronic visiting and application are improving campus security level.But these System is only capable of the children in campus environment are protected, and due to the uncertainty of child's range of activity outside campus, makes Must after-school activities child be carried out being effectively protected and become a difficult point.

With the development of location technology and wireless communication technology, GPS/AGPS/GPSOne location technology penetrates at present Every field, military, commercially, the aspect such as geographical, transport and communication is all widely used.Difference according to actual needs, Requirement to GPS system is also different.The positioning principle of GPS is relatively easy:Receptor is defended by the GPS in accurate measurement earth overhead The time of star transmission signal determines its position.The message of the continuous transmission of every satellite includes the time of message transmission, accurate rail Road parameter (ephemeris) and system mode and all gps satellites track (yearbook) substantially.Traditional GPS technology is due to excessive Rely on the performance of terminal, satellite is scanned, captures, pseudo range signals receive and the work such as positions calculations combines in terminal all over the body, thus Cause location sensitivity low and the aspect such as terminal power consumption amount is big defect.APGS/GPSOne technology then simplifies the work of terminal Amount, the heavy task the most such as satellite scanner uni positions calculations is handed to network from terminal side and completes, thus sensitivity, The aspects such as cold start speed, terminal power consumption amount have received satisfied effect.

The application of GPS positioning technology has reached perfervid degree a few days ago.From the electronic chart of handheld terminal to vehicle-mounted Guider all be unable to do without the support of GPS technology.But an important indicator as measurement alignment system performance, positioning precision Raising is still the big technological difficulties of current one.Positioning precision is affected by various factors, for intrinsic factor (as atmospheric environment, Systematic error) impact typically cannot directly eliminate；And the impact for random factor, can by the means of technology Lai It is controlled.In order to improve positioning precision, and meet the application demand of range finding, differential type GPS (DifferentialGPS, DGPS) arise at the historic moment, its method be accurately measure coordinate object of reference on arrange GPS, and and mobile station on GPS simultaneous observation is no less than the same group of satellite of four, tries to achieve differential corrections number (differential position, the pseudorange in this moment Difference, differential smooth pseudo distance of phase and phase contrast grade and revise number), by wireless software download these correction real-time broadcastings Give the mobile station (user) nearby working or send mobile station (user) afterwards to, by the received difference of mobile station (user) Divide correction that its GPS location data is revised in real time, its objective is to eliminate common error item, attenuation of correlation error effectively Impact, and then obtain more accurate positioning result, improve positioning precision.DGPS is with respect to the navigator fix that GPS can be user Precision brings the raising of the order of magnitude, in the boat such as the landing of aircraft precision approach, unmanned plane, ballistic trajectory measurement, vehicle positioning and navigation Sky, space flight, navigation and automotive field are applied.DGPS can provide accurate position and speed when using visible carrier phase Degree information, but the generation due to dephasing between receptor and satellite, can lead to cycle landing (cycleslip), and then affect to survey Accuracy of measurement.This cycle landing can greatly reduce positioning precision in a dynamic mode.For example, when vehicle enters tunnel, vehicle-mounted Gps receiver signal is easily interrupted by shielding.In order to improve DGPS performance in a dynamic mode, research worker proposes to adopt The mode that GPS/INS (Inertial Navigation System) combines strengthens the positioning precision of GPS, the short-term phase of INS Positional precision just be can be used to detect and correct the cycle landing in gps carrier phase place, meanwhile, the accurate measurement of receptor Constantly can provide for INS and update.INS can also be filled up the difference of satellite tracking by masking effect.This integrated form system System will be more accurate than single system, more reliable, and operationally have more retractility.But INS device is existed and makes an uproar at random Sound, the denoising method commonly used at present has mean filter, medium filtering, Wavelet Denoising Method etc..Mean Filtering Algorithm is simple and practical, filtering Time is short, but is only applicable to the denoising of static and low Dynamic Signal；Median filtering algorithm is applied to the stronger signal of dynamic Denoising, but when high-frequency noise in slowly varying signal, its denoising effect is not so good as mean filter；Wavelet Denoising Method effect Better than mean filter and medium filtering and static, Dynamic Signal is all applicable, but due to multi-level signal decomposition and weight will be carried out Structure, required time is longer, is difficult to meet the requirement of real-time of system.

So far, developing rapidly and popularizing with respect to GPS technology, is directed to the behavioral pattern of specific crowd accordingly Location technology relatively lags behind, and far from meeting specific crowd (such as child, old people) positioning field, crowd behaviour pattern is carried out Automatically classification and sterically defined requirement.Only at present adopt GPS/AGPS/GPSOne for the scheme that children's safety is guarded Deng technological orientation, although this method has the advantages that simple, directly perceived, this method can not obtain higher positioning accuracy, only Can determine that the general area of child present position it is impossible to entering to child or old people according to the behavior characteristicss of child or old people Row accurately positions it is impossible to effectively be positioned and safe preservation to specific crowd.Essentially, these drawbacks are produced Main reason is that the localization method being currently based on GPS/AGPS/GPSOne lacks the resolution capability of crowd behaviour feature, do not have The identification advantage of standby specific crowd positioning.

Content of the invention

It is an object of the invention to overcoming drawbacks described above, providing one kind can improve in existing location technology and being directed to specific crowd It is accurately positioned the intelligent locating method based on GPS/AGPS/GPSOne and target behavior feature of the identification capability in place.

To achieve these goals, the technical solution used in the present invention is as follows：

A kind of intelligent locating method based on GPS/AGPS/GPSOne and target behavior feature, comprises the following steps：

(1) all points of interest in electronic chart are carried out the hierarchical classification of X layer, respectively first order classification, the second level Classification, third level classification ... X level are classified, and wherein, each fraction apoplexy due to endogenous wind contains different types of point of interest class, the first fraction Higher level's class that class is classified for the second level, the second level is categorized as higher level's class of third level classification, the like, in the classification of X level Each point of interest class only includes certain specific point of interest；Specifically, all points of interest in electronic chart are carried out x layer Hierarchical classification, Partition for Interest Points is some big class (ground floor), and each big class is further subdivided into some subclasses, and each subclass continues It is divided into some little subclasses, gradually analogizes, until X layer, only include an object in each point of interest class of X layer, be i.e. electricity Certain specific point of interest on sub- map；The division of point of interest can depending on actual situation, be such as divided into 3 grades, 4 Level, 5 grades even more many, if being divided into 3 grades, have first order point of interest class, second level point of interest class and third level point of interest class, Wherein, first order point of interest class is higher level's type of second level point of interest class, and second level point of interest class is third level point of interest class Higher level's type, third level point of interest class then be specific point of interest；

(2) to different point of interest classes in every one-level, it is initial that the behavior characteristicss according to target arrange corresponding initial weight The point of interest class belonging to same higher level's class in weight, and same layer sets weight sum equal to 1, all emerging in first order classification The setting weight sum of interest point class is equal to 1；

(3) area size according to shared by X fraction apoplexy due to endogenous wind specific point of interest carries out fence to specific point of interest；

(4) all in the centre of location and error radius R according to calculating from the positioning result that GPS/AGPS/GPSONE obtains The set S of specific point of interest, and in set of computations S each specific point of interest and the centre of location apart from Dis；

(5) for each specific point of interest in set S, calculate type weight ω (i) of this point of interest according to formula (1)：

(6) actual weight ω of each specific point of interest in S is calculated according to formula (2)_i：

(7) probability that target is in each specific point of interest in set S is calculated according to formula (3)：

Wherein, R is error radius,The weight of the j-th stage point of interest classification belonging to point of interest i, k_jFor constant and full FootWith 1 ＞ k_m＞ k_n＞ 0, (x >=m ＞ n >=1), α, β are constant,Represent the reality of all points of interest in set S Border weight sum；

(8) point of interest choosing maximum probability in set S is target location.

Step (8)：The point of interest choosing maximum probability in set S is for, after target location, updating the point of interest i being selected The weight of affiliated point of interest classification at different levelsJ=1 ..., X：

Weight after renewal, it is fixed for next time that the weight after renewal is used as each higher level's point of interest class belonging to selected point of interest i Setting weight during position.

Compared with prior art, the invention has the advantages that：

The present invention is based on existing electronic chart, each region is carried out the division of point of interest, according to the behavior characteristicss of target, Every grade is divided and sets weight, then again in the range of error of positioning, calculate the probability that target is in each point of interest, choosing Take probability highest as positioning result, not only positioning result error is little, and setting accuracy is much better than existing localization method, and Effectively overcome the resolution capability that existing location technology lacks crowd behaviour feature, the identification not possessing specific crowd positioning is excellent The problem of gesture.

Brief description

Fig. 1 is the schematic diagram of certain positioning region.

Specific embodiment

With reference to embodiment, the invention will be further described, and embodiments of the present invention include but is not limited to following reality Apply example.

Embodiment

Present embodiments provide a kind of intelligent locating method based on GPS/AGPS/GPSOne and target behavior feature, youngster It is configured with positioner with child/old man, realize between this positioner and background server communicating, the opposing party is taken by backstage Business device reads location information.The design principle of the present embodiment is the behavior characteristicss (being drawn by statistics) according to target, to difference Point of interest sets corresponding weight, then calculates, in the range of position error, the probability that target is in each point of interest again, selects general Rate big as final positioning result.

Step one：Based on electronic chart, divide multistage point of interest：

By the POI (point of interest) on electronic chart according to the mode classification of high moral map, it is divided into level Four：The first order is affiliated The big class of POI, has at present：Physical culture and recreational facilities, medical related service, food and beverage sevice, accommodation service, scenic spot, write Building, development zone, residential quarters, government bodies, science and education and cultural facility, means of transportation, financial service facility, company and enterprise, Automobile related facility, such as sells, maintenance, high-speed service area viaduct etc. and a few species such as related POI, service for life of driving Type, symbolizationRepresent, k represents the type in first-level class catalogue, for example, belongs to scenic spot class, in order to distinguish inhomogeneity The point of interest of type, marks subscript below k.The second level is the subdivision further of first order POI place big class, is divided at present：Refuel Stand, other energy source station, automobile maintenance/decoration, washing bay, sale of automobile, Chinese Restaurant, the classification such as foreign country dining room, symbolization Represent, in order to distinguish different types of point of interest, below k, mark subscript.The third level is the thin further of every kind of second level classification Point, it is divided into Sinopec, Toyota of Guangzhou Automobile Workshop to sell at present, east wind is sold, the types such as maintenance, Sichuan cuisine are produced in Zhengzhou daily, we use symbol NumberRepresent, in order to distinguish different types of point of interest, below k, mark subscript.Concrete classification information is shown in high moral map POI classification Synopsis.The fourth stage is categorized as certain POI specific, be for example located at Chenghua district Wanke road 9 " Kai De square. glamour city " B1 floor 04th, the rural base fast food restaurant of No. 05A, adoptsRepresent.

Step 2：To different point of interest classes in every one-level, the behavior characteristicss according to target arrange corresponding initial weight, And belong in same layer same higher level's class point of interest class set weight sum be equal to 1, the first order classification in all points of interest The setting weight sum of class is equal to 1：

The principle of weight setting is to be set according to the behavior characteristicss of target.For example：For child user, according to it Behavior characteristicss, beThe classification setting weight of every kind of difference POI.If first-level class a total of n kind is dissimilar, need RightDifferent weights are set, and weight coefficient is respectively α₁～α_n, and α₁+α₂+…+α_n=1.Equally, need to two, The corresponding weight coefficient of three-level classification setting, if the different type of secondary classification a total of m kind, corresponding secondary classification weight It is respectively β₁～β_m, and β₁+β₂+…+β_m=1, if three-level is classified, a total of l kind is dissimilar, corresponding three-level classified weight It is respectively λ₁～λ_lAnd λ₁+λ₂+…+λ_l=1.

Step 3：

According to shared by specific point of interest, area size carries out fence to xth level point of interest.Fence technology is Existing mature technology, therefore not to repeat here.

Step 4：

According to all tools calculating from the positioning result that GPS/AGPS/GPSONE obtains in the centre of location and error radius R The set S of the point of interest of body, and in set of computations S each specific point of interest and the centre of location apart from Dis；In set S Specific point of interest includes fence (the specific interest being contained in the circle being constituted with error radius or intersecting with it Point), as shown in Figure 1；

Step 5：

Type weight ω (i) of the affiliated higher level's point of interest class of each specific point of interest in set of computations S；Hypothesis is divided into Level Four point of interest, then, in set S, the type weight of specific point of interest i is equal toWherein,Represent that j-th stage is emerging The weight of the affiliated type of this point of interest, k in interest point classification_jLevel weights constant for j-th stage point of interest set in advance classification MeetAnd 1 ＞ k_m＞ k_n＞ 0, (4 >=m >=n >=1).For example：Point of interest class in first order classification is food and beverage sevice, Its weight is 0.2, and level weights constant is 0.0625；Point of interest class in the classification of the second level is Chinese Restaurant, level weights constant For 0.125, its weight is 0.3, the point of interest class in third level classification is rural base fast food, and level weights constant is 0.25, its Weight is 0.2, the fourth stage classification in point of interest class be Chenghua district Wanke road 9 " Kai De square. glamour city " B1 floor 04,05A Number rural base fast food restaurant, level weights constant be 0.5625, its weight be 0.3, then corresponding, for point of interest Chenghua district ten thousand Section road 9 " Kai De square. glamour city " type weight of rural base fast food restaurant of B1 floor 04,05A is equal to：0.0625*0.2+ 0.125*0.3+0.25*0.2+0.5625*0.3=0.186

Step 6：

Calculate actual weight ω of each specific point of interest in S according to formula (2)_i：

Step 7：

The probability that target is in each specific point of interest in set S is calculated according to formula (3)：

Wherein, R is error radius, and α, β are constant,Represent the actual weight of all specific points of interest in set S Sum；

Step 8：

The point of interest choosing maximum probability in set S is target location.

After in selection set S, the point of interest of maximum probability is target location, at different levels belonging to selected point of interest i The weight of point of interest classificationUpdate the weight of the point of interest classification at different levels belonging to the point of interest i being selectedJ=1 ..., X：

Wherein, point of interest classification at different levels refer to that first order classification, second level classification, third level classification ... X level are classified.

With in step 5 point of interest Chenghua district Wanke road 9 " Kai De square. glamour city " B1 floor 04,05A rural area As a example base fast food restaurant, if this point of interest is selected, the new weight of the point of interest class in fourth stage classification belonging to it is：(1+ 0.5625) * 0.3=0.469；In third level classification, the new weight of rural base fast food class is (1+0.25) * 0.2=0.25；Second The new weight of fraction apoplexy due to endogenous wind Chinese Restaurant class is (1+0.125) * 0.3=0.3375；

In first order classification, the new weight of food and beverage sevice is (1+0.0625) * 0.2=0.2125.

By said method, according to the behavior characteristicss of target, can achieve target is accurately positioned, its position to accurate Degree is far superior to existing location technology.

According to above-described embodiment, the present invention just can be realized well.What deserves to be explained is, before above-mentioned design principle Put, for solving same technical problem, even if some made on architecture basics disclosed in this invention are no substantial Change or polish, the essence of the technical scheme being adopted is still as the present invention, therefore it should also be as the protection model in the present invention In enclosing.

Claims (2)

1. a kind of intelligent locating method based on GPS/AGPS/GPSOne and target behavior feature is it is characterised in that include following Step：

(1) all points of interest in electronic chart are carried out the hierarchical classification of X layer, respectively the first order is classified, classify in the second level, The third level is classified ..., and X level is classified, and wherein, each fraction apoplexy due to endogenous wind contains different types of point of interest class, and the first order is categorized as Higher level's class of second level classification, the second level is categorized as higher level's class of third level classification, the like, each classified in X level Point of interest class only includes certain specific point of interest；

(2) to different point of interest classes in every one-level, the behavior characteristicss according to target arrange corresponding initial weight, and same layer In belong to same higher level's class point of interest class set weight sum be equal to 1, the first order classification in all point of interest classes setting Weight sum is equal to 1；

(3) area size according to shared by X fraction apoplexy due to endogenous wind specific point of interest carries out fence to specific point of interest；

(4) all concrete in the centre of location and error radius R according to calculating from the positioning result that GPS/AGPS/GPSOne obtains Point of interest set S, and in set of computations S each specific point of interest and the centre of location apart from Dis；

(5) for each specific point of interest i in set S, according to the weight calculation point of interest of affiliated higher level's point of interest classification Type weight ω (i)；

$\mathrm{\ω}\left(i\right)=\underset{j=1}{\overset{X}{\mathrm{\Σ}}}{k}_j{\mathrm{\ω}}_j^i---\left(1\right)$

WhereinRepresent the weight of the j-th stage point of interest classification belonging to point of interest i, k_jFor constant, and have

(6) actual weight ω according to each specific point of interest in formula (2) set of computations S_i：

${\mathrm{\ω}}_i=\mathrm{\α}(1-\frac{Dis}{R})+\mathrm{\β}\mathrm{\ω}\left(i\right)---\left(2\right)$

(7) probability that target is in each specific point of interest in set S is calculated according to formula (3)：

$p_i=\frac{{\mathrm{\ω}}_i}{\underset{i\∈S}{\mathrm{\Σ}}{\mathrm{\ω}}_i}---\left(3\right)$

Wherein, R is error radius, and α, β are constant,Represent the actual weight sum of all points of interest in set S；

(8) point of interest choosing maximum probability in set S is target location.

2. a kind of intelligent locating method based on GPS/AGPS/GPSOne and target behavior feature according to claim 1, It is characterized in that, described step (8) chooses the point of interest of maximum probability in set S for, after target location, updating according to formula (4) The weight of each higher level's point of interest class belonging to selected point of interest iWeight after renewal is used as selected emerging Setting weight during each higher level's point of interest class positioning next time belonging to interesting point i, formula (4) is as follows：

${\mathrm{\ω}}_j^i=(1+k_j){\mathrm{\ω}}_j^i---\left(4\right).$