Survey on the WIFI Positioning Technology

Survey on the wireless local ara net wager Positioning TechnologyA quick survey on the wireless fidelity placement engineering annulWireless posture appraisal applied science is employ heroicly into umteen field such as in the military parley, Internet of things and societal net bets. Meanwhile, with the growing necessity of WIFI engine room, access points of WIFI networks have been deployed in ample-scale department stores, cafes, schools and general hospitals. WIFI jam localisation atomic number 50 not only offset the drawbacks of GPS e extraly in built-up bea or inside environment but likewise enlarge the fix affection work in the relevant industrials. Specifically, more accurate result is the of import contribution of the WIFI spatial relation. Based on WIFI pickle devotion technology, this survey will parade diametrical kinds of glide pathes applied in WIFI coifing, give a comparison among them and discuss certain algorithmic ruleic rules in re produce technology.Key words WIFI technology, WIFI reparation, location positioning algorithms1 IntroductionWith the high development of Wireless Communication and the urgent need of Personal Communication Service, opposite kinds of wireless networks has emerged such as GSM, WCDMA, TDSCDMA base on Cellular Technology, Wi-Fi base on AP coverage, etc. Diverse wireless network has different swashs and dirty dog also beat about a wide variety of data services which can satisfy the substance ab exploiter for their own communication need. Largely, it can pop the question us high character of communication experience and alter our way of life.In the same time, the fast growth of the wireless communication pull out the social networks best-selling(predicate) among the modern generations. Location estimation technology will also make a great contribution to it. In advertising services, as long as the detailed location coordinate of the spry use uprs is once determined, it wil l bring about enormous economic benefits to the surrounding business. Business owners could send advertisements to consumers close to make more profit. The positioning technology could make creation bail services more completed. For example, it can aid us to find befogged articles, stolen bicycles and missing children or pets. Furthermore, for large manufactures, Location estimation technology could offer the detailed position instruction of each product comp ints. As for tourists, it can provide travelling information, too. Even in museums, campus and large amusement parks, users could also take the advantage of this location services.With the WIFI technology being applied into many fields, access points of WIFI networks be covered in large commercial buildings, cafes, schools, grand hospitals, bus stops and metro. WIFI positioning technology could make up the limits in indoor(a)s environment of GPS. It can not only correct the accuracy of location estimation but also cut d own the cost of coverage, which is significant to the society,2. Different approaches applied in WIFI positioningIn terms of positioning technology, the or so popular one is GPS. However, the environment should be flat and open. As for indoors regions, GPS technology has a relative poor accuracy in location estimation due to the fact that influenced by the building walls and former(a) subjects, the intensity of guide is attenuated largely. Therefore, WIFI position technology could be an optimized choice for indoors environment.2.1 The definition of the WIFI positioningLocalization is the process of estimating absolute or relative position of mobile objects, referring to the data of predefined spots position in restricted area. 1 In indoors environment, wireless local area network is the ideal option to identify the final puts. The access point just like the bases in wireless communication play a significant role in WIFI positioning. Therefore, WIFI could provide the larger cove rage as well as make the localization more convenient.2.2 The castification of the approaches in WIFI LocalizationCurrently, the volume of WLAN is victimisation the Radio Frequency to communicate with each new(prenominal) due to the fact that most Radio Waves could penetrate walls or obstacles in indoors environment. To be more specific, RSSI is the general localization technology to be applied in wireless environment. 2The following gives a simple verbal description of RSSI.RSSI ( legitimate augury strength indication) Research and experimental measurings show that wireless signal in contemporaries presents some rules as followed Once the transmission male monarch of AP is fixed, there is an inverse relationship amid the receivers received signal strength and place between sender and receiver.3 Specifically, if the blank between them is closer, the stronger received signal strength we will get. By using the cognize radio propagation model, RSSI manner could measure di fferent RSSI of APs from mobile terminals. In most cases, we could get the positioning result through three different APs.Therefore, positioning approaches base on RSSI could be crystaliseified into two fields one is trilateration positioning and the other is reproduceing positioning.2.2.1 Trilateration positioning technologyTrilateration positioning technology means setting the 3 APs to be the center and the distance between AP and to be localized subject to be radius. Therefore, we get the 3 different circles and the focus among them. By using the above data, we could attain the equations to work out the distance of the solution.In WIFI networks, the distance between AP and user could be attained by two approaches.1. TOA (time of arrival) TOA is measuring the one-way propagation time between the AP and mobile terminals or the round-trip propagation time. 4The former need to record the precise signal transmission time of the AP or mobile terminals.Fig.3-1 shows the prefatorial idea of TOA positioning approach. Moreover, the receiver is highly depend on the clock, too the latter dont worry about the synchronization. However, there are still high demands on the clock.Fig.2-1 The schematic diagram of TOA approachYet, TOA is highly depend on accurate time clock. During the localization, 1ms of the measuring fault could result in the 300m positioning mistake. Therefore, for the AP and mobile terminal there are high demand on precise clock, which increased the localization aphonic ware costs.2. TDOA (time dispute of arrival) Different from TOA, TDOA is to detect the arrival time difference between the two APs other than the absolute arrival time for the physical object terminal localization5. Fig.3-2 describe the basic schematic diagram of TDOA approach. Obviously, via this approach, we can smear the high demand of the synchronization between the sender and receiver. By using the three different AP, it is easy to measure two TDOA values. The mobile termin al is located on two hyperbolic intersection determined by the two TDOA.Fig.2-2 The schematic diagram of TDOA approach2.2.2 Fingerprinting positioning technologySimilar to the traditional reproduce technology, fingermark technology relies on characterizing the feature of the database to identify the target.Fig.3-3 gives a detailed description of the working principle in finger printing technology. 6There are two stages in the localization readiness stage and positioning stage.Training Stage The target in this stage is to build a fingerprint database. First, we should adopt a reasonable graphic symbol point distribution for ensuring to provide enough information in the positioning stage. Then, It is important to measure the value of RSS in different reference points. 11The location information of reference points and the corresponding MAC address are enter in the database. Due to the environment factor, wireless signal strength is not stable. In order to overcome this disadvanta ge, generally, we take the average of multiple measurements at each reference point. Table2-1 below indicates the establishment of the fingerprint database.Table2-1 An example of the fingerprint databasePositioning Stage Once the database is settle down, according to the certain twin(a) algorithms, the RSS value of the target point is compared with cognize information in the database. The common matching algorithm is Nearest Neighbor algorithm (NN) , k-Nearest Neighbor algorithm and so on. These approaches will be discussed thoroughly in the next part. At last, we could attain estimated user location.Fig.2-3 The schematic location positioning technology in fingerprintThe above is some basic approaches in WLAN establish indoor location estimation technology. The table 2-2 blow presents a instruct comparison among them.Table 2-2 the comparison among the different approaches in WLAN based indoor environment3. Location algorithmic programs in fingerprint technologyIn this section, we will introduce two classical positioning algorithms based on fingerprint technology Nearest Neighbor (NN) algorithm and Nave Bayesian algorithm.3.1 The Nearest Neighbor algorithm (NN)NN could be regarded as a special case of KNN algorithm namely k=1. KNN approach is first introduced in early 1950s. Within the large amount of training set, it is computationally intensive. From past on, it is applied rapidly in the field of pattern recognition.8NN is based on analogical learning. To be more specific, we could attain the result by comparison the given test examples and resembled training samples. In the field of wireless location estimation, the test samples are fingerprint and the class label is the physical location corresponding to the fingerprint. 9Supposed that if the number of fingerprint is l (denoted as ) in the localization area, there is a part relationship between each fingerprint and the corresponding physical location information.In the real-time positioning stage, on e RSS fingerprint example is denoted as S. It contains average RSS value from N different APs, namely .In the fingerprint database, each fingerprint is expressed as. is the fingerprint of No.i, which contains the average value of RSS in No.n AP. Therefore, the similarity between the fingerprint S of the real-time signal and the training samples in the database could be measured by the distance between them, for instance, the Euclidean distance. Just like the formula 3-1 belowFinally, for the fingerprint S of the real-time signal, the estimated result is the physical location corresponding to the fingerprint which is the nearest one from it. Shown as formula (3-2).3.2The Naive Bayesian AlgorithmThe nave Bayesian algorithm is based on the hazard method deriving from categorization in statistics.10 Bayesian compartmentalisation could predict the likeliness of the class members, for instance the given sample belongs to a particular class. The of import idea of Bayesian classificati on is that in many applications, the relationship between the samples and class labels is not determined. In other words, though the test samples are very similar to some training samples, we couldnt predict the class label clearly. The noise leads to this situation or other confounders which affected the classification didnt be contained in analysis. Different from KNN, Bayesian classification gives the fortune of test samples belonging to the certain class other than the exact class label of test samples.Based on Bayes Theorem, Bayesian classification is a statistic principle which combines the prior knowledge and new evidence collect from the new data set. Naive Bayes is the impletion of the Bayesian classification. The localization based on naive Bayesian is as followed First, supposed that there are l fingerprints in the localization area, denoted as , there is a mapping relationship between the each fingerprint and the corresponding group of location information. In the real -time positing stage, a RSS fingerprint sample is denoted as S and it contains average RSSI value from n different APs,Then, nave Bayesian algorithm is to attain the posteriori probability of real-time RSS fingerprint samples S in the positioning area, it could be described as belowIn the formula (3-1),with the known location,is the conditional probability of real-time RSS fingerprint sample S.is the prior probability of Li in the localization area. Generally, users could appear on any position of the location area. So we consider is subject to the uniform distribution. The key surmisal of Naive Bayesian is that the impact of each attribute value for a given class is independent of the other property values. In other words, in certain location, the RSSI value from different APs is independent and unrelated. Therefore, the calculation of is simplified as We could use Gaussian probability distribution to approximate the RSSI in certain location, the formula is as below.Eventually , by using the MAP, we estimate the uses location, described as formula(3-3).4. Conclusion and Future prospectsBased on WIFI positioning technology, this survey analyze the needs of wireless localization, severalise and compare the different approaches implemented in indoor environment and present two classical algorithms in fingerprint technology.With the high development of WLAN, the technology based on RSSI, especially fingerprint attracts more and more attention. On the basis of the more accurate estimated result, the early research goal is to improve the ease of use in the positioning system and make the location-based services more convenient and more practical. Here are some tips towards the future research fieldsThe fingerprint technology algorithm its self has the drawbacks of enormous complicated preparation works. By using the propagation model, we could reduce the large amount of working preparations.Most people study or work in indoors environment. So, how to use othe r peoples information to improve the users own localization accuracy is an arouse issue and many researcher has put emphasis on it.Recently, most algorithms are just in theoretical research or basic test scene lacking of practical application consideration. Therefore, how to implement these algorithms into public paces is another urgent issue, too.ReferencesN0HA S, LEE W J, YOUNG J. Comparison of the mechanisms of the Zigbees indoor localization algorithmC, Ninth ACIS International Conference on Software Engineering, hokey Intelligence, Networking, and Parallel Distributed Computing. Phuket, S.l. s.n., 2008 13-18.ZHUMinghui,ZHANG Huiqing. Research on model of indoor distance measurement based on receiving signal strengthC.2010 International Conference on computing machine Design and Appliations. Qinhuangdao, s.l.s.n., 2010 54-58.K.C.Ho,Y.T.Chan.Geolocation of a known altitude object from TDOA and FDOA measurementsJ. IEEE Transactions on Aerospace and Electronic Systems, 2007 33(3 ) 770-783.Binghao Li, Yufei Wang, Hyung Keun Lee,ect.A New Method of Yielding a Database of Location Fingerprints in WLAN,IEEE Proceedings Communications. 2005. pp.580-586.Bahl P, Padmanabhan VN. Enhancements of the RADAR User Location and Tracking System. Technical sketch MSR-TR-2000-12, 2000.Yongliang Sun,Yubin Xu, Lin Ma, Zhian Deng, KNN-FCM hybrid algorithm for indoor location in WLAN , Power Electronics and Intelligent Transportation System (PEITS), 2009.pp.251-254dd.Roos T, Myllymaki P, Tirri H, et al. A Probabilistic undertake to WLAN User Location Estimation. International Journal of Wireless knowledge Networks, 2002, 9, 155-16.