本文選題：行人軌跡推算　切入點(diǎn)：軟件開發(fā)工具包　出處：《內(nèi)蒙古大學(xué)》2017年碩士論文

【摘要】：近年來,基于位置服務(wù)(Location Based Service,LBS)的興起加快了移動(dòng)智能領(lǐng)域的發(fā)展,越來越多的移動(dòng)開發(fā)者投身于LBS應(yīng)用開發(fā)。與此同時(shí),對(duì)位置信息獲取的精確性、穩(wěn)定性、節(jié)能性提出了更高的要求。本文針對(duì)上述需求,結(jié)合基于智能手機(jī)慣性傳感器的輔助定位方法有助于降低能耗、提高定位精度的特點(diǎn),在Android平臺(tái)下設(shè)計(jì)并實(shí)現(xiàn)了利用行人軌跡推算(Pedestrian Dead Reckoning,PDR)算法進(jìn)行輔助定位的SDK。首先,設(shè)計(jì)了一個(gè)可以容納與拓展不同定位、輔助定位算法以及融合策略的框架。并在此框架中封裝了 GPS、基站、Wi-Fi定位算法,用于輔助定位的面向非約束智能手機(jī)的PDR算法,以及基于粒子濾波的融合算法。其次,本文實(shí)現(xiàn)了一系列輔助工具來拓展SDK的功能。其中包含了用于顯示定位結(jié)果與描述運(yùn)動(dòng)軌跡的地圖工具,用于分析定位數(shù)據(jù)的圖表工具等。最后,對(duì)上述功能進(jìn)行了單元測試,驗(yàn)證了功能的可行性。并基于粒子濾波的融合算法,使用面向非約束智能手機(jī)PDR算法對(duì)Wi-Fi指紋定位進(jìn)行了輔助,與僅使用Wi-Fi指紋定位的條件下對(duì)比分析了定位結(jié)果,驗(yàn)證了該融合定位算法的可行性。綜上所訴,本文為LBS應(yīng)用開發(fā)人員提供了一個(gè)可行的定位SDK,為PDR算法研究人員提供了一個(gè)便捷的研究環(huán)境。
[Abstract]:In recent years, the rise of Location-Based Based Service (LBS-based) has accelerated the development of mobile intelligence, and more and more mobile developers have devoted themselves to the development of LBS applications.At the same time, higher requirements for accuracy, stability and energy saving of location information acquisition are put forward.In order to meet the above requirements, combined with the intelligent mobile phone inertial sensor based on the auxiliary positioning method is helpful to reduce energy consumption, improve positioning accuracy characteristics,Based on the Android platform, an aided location algorithm based on Pedestrian Dead Reckoning (PDR) algorithm is designed and implemented.Firstly, a framework is designed to accommodate and extend different localization, auxiliary location algorithms and fusion strategies.In this framework, we encapsulate GPS, base station Wi-Fi location algorithm, PDR algorithm for unconstrained smart phone and fusion algorithm based on particle filter.Secondly, this paper implements a series of auxiliary tools to extend the function of SDK.It includes a map tool for displaying the location result and describing the motion track, a graphic tool for analyzing the location data and so on.Finally, the unit test of the above function is carried out, and the feasibility of the function is verified.Based on the particle filter fusion algorithm, the PDR algorithm for unconstrained smart phone is used to assist the Wi-Fi fingerprint location. The results are compared with those using only Wi-Fi fingerprint location, and the feasibility of the fusion algorithm is verified.In summary, this paper provides a feasible location for LBS application developers and a convenient research environment for PDR algorithm researchers.
【學(xué)位授予單位】：內(nèi)蒙古大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP311.52;TP316

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