【摘要】：近年來,隨著無線通信技術(shù)的迅猛發(fā)展,基于位置的服務(wù)(LBS)在實(shí)際應(yīng)用中的重要性日趨凸顯。由于在建筑密集區(qū)域和室內(nèi)存在較多障礙物阻擋,常用的衛(wèi)星定位系統(tǒng)的定位性能受到嚴(yán)重影響,因此采用廣泛存在的WiFi網(wǎng)絡(luò)進(jìn)行室內(nèi)定位已成為當(dāng)前研究的熱點(diǎn)。論文首先設(shè)計(jì)了基于接收信號強(qiáng)度(RSSI)的被動WiFi定位系統(tǒng)。該系統(tǒng)主要包括前端AP模塊、Socket通信模塊、服務(wù)器模塊以及定位算法模塊,采用的是路由器“被動”定位的方法,其優(yōu)勢在于:(1)支持任何未預(yù)裝APP或定位芯片的Wi Fi設(shè)備;(2)定位路由器無需進(jìn)行硬件改造;(3)系統(tǒng)后臺可以直接獲得定位數(shù)據(jù),無需待定位設(shè)備主動上報(bào)位置信息。本文通過軟硬件的設(shè)計(jì),實(shí)現(xiàn)了各個(gè)模塊的預(yù)設(shè)功能,為接下來的定位算法驗(yàn)證提供實(shí)際測試平臺。其次,本論文研究一些新方法,從以下三個(gè)方面提高定位系統(tǒng)的精度:(1)采用高斯濾波法篩選收集到的RSSI數(shù)據(jù),從而過濾掉存在較大誤差的點(diǎn);(2)研究常用的室內(nèi)傳播模型,并對室內(nèi)環(huán)境衰減因子進(jìn)行測試,進(jìn)一步獲得符合實(shí)測環(huán)境的傳播損耗模型;(3)對比分析現(xiàn)有的定位算法,結(jié)合質(zhì)心算法和極大似然算法,提出一種改進(jìn)的基于極大似然和加權(quán)質(zhì)心的混合定位算法。最后,將上述研究的新方法應(yīng)用于本課題的被動WiFi定位平臺,搭架了一套完整的定位演示系統(tǒng);實(shí)測結(jié)果表示該系統(tǒng)較好的滿足了設(shè)計(jì)性能需求,同時(shí)相對于原有定位系統(tǒng),在定位精度上實(shí)現(xiàn)了有效提高。
[Abstract]:In recent years, with the rapid development of wireless communication technology, the importance of location-based service (LBS) in practical applications is becoming increasingly prominent. Because there are many obstacles in the dense building area and indoor, the positioning performance of the commonly used satellite positioning system has been seriously affected. Therefore, indoor positioning using the widely existing WiFi network has become a hot spot of current research. In this paper, a passive WiFi positioning system based on received signal strength (RSSI) is designed. The system mainly includes front-end AP module, Socket communication module, server module and location algorithm module. Its advantages lie in: (1) supporting any Wi Fi device without pre-installed APP or positioning chip; (2) the location router does not need hardware modification; (3) the system can obtain the location data directly in the background, and it is not necessary for the positioning equipment to report the position information actively. Through the design of software and hardware, the presupposition function of each module is realized, which provides a practical test platform for the next localization algorithm verification. Secondly, this paper studies some new methods, from the following three aspects to improve the accuracy of the positioning system: (1) using Gao Si filtering method to filter the collected RSSI data, so as to filter out the existence of large error points; (2) the commonly used indoor propagation model is studied, and the attenuation factor of indoor environment is tested to obtain the propagation loss model which accords with the measured environment. (3) comparing and analyzing the existing localization algorithms, combining centroid algorithm and maximum likelihood algorithm, an improved hybrid localization algorithm based on maximum likelihood and weighted centroid is proposed. Finally, the new method mentioned above is applied to the passive WiFi positioning platform of this subject, and a complete positioning demonstration system is set up. The measured results show that the system meets the design performance requirements well, and the accuracy of the system is improved effectively compared with the original positioning system.
【學(xué)位授予單位】：華僑大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TN92

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相關(guān)期刊論文 前2條

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本文編號：2402980