【摘要】：基于位置的服務(wù)已在智慧醫(yī)療、安全保護(hù)、商業(yè)廣告、智能出行、地圖導(dǎo)航等多個(gè)領(lǐng)域被廣泛應(yīng)用,在信息化與自動(dòng)化程度越來(lái)越高的當(dāng)今社會(huì)扮演著愈加重要的角色,對(duì)用戶(hù)進(jìn)行準(zhǔn)確的位置獲取與運(yùn)動(dòng)軌跡估計(jì)是該類(lèi)服務(wù)的基礎(chǔ)。由于室內(nèi)環(huán)境下存在信號(hào)反射,多徑效應(yīng),環(huán)境多變等問(wèn)題,使得基于外部信號(hào)(被定位目標(biāo)以外的設(shè)備產(chǎn)生的信號(hào))的估計(jì)方法在室內(nèi)環(huán)境下并不能很好的滿(mǎn)足位置服務(wù)的需求。手機(jī)慣性導(dǎo)航技術(shù)具有定位區(qū)域可變、環(huán)境適用性強(qiáng)、不依賴(lài)外部信號(hào)的天然優(yōu)勢(shì),因此,非常適合作為解決室內(nèi)位置服務(wù)問(wèn)題的解決方案。但由于手機(jī)慣性導(dǎo)航技術(shù)存在傳感器數(shù)據(jù)噪聲大,手機(jī)攜帶者運(yùn)動(dòng)狀態(tài)與手機(jī)攜帶狀態(tài)隨機(jī)、多變的問(wèn)題,使得使用場(chǎng)景適用性較差,從而影響運(yùn)動(dòng)軌跡估計(jì)的準(zhǔn)確性與魯棒性。本文通過(guò)對(duì)手機(jī)內(nèi)置傳感器的工作原理進(jìn)行分析,確定其數(shù)據(jù)組成及噪聲特性,針對(duì)不同使用場(chǎng)景設(shè)計(jì)不同的噪聲處理器；從人體運(yùn)動(dòng)特征與手機(jī)使用特征的分析入手,討論運(yùn)動(dòng)狀態(tài)與手機(jī)攜帶狀態(tài)的分類(lèi)與估計(jì)方法；在確定的運(yùn)動(dòng)狀態(tài)與手機(jī)攜帶狀態(tài)的基礎(chǔ)上,并利用室內(nèi)建筑特征進(jìn)行運(yùn)動(dòng)軌跡估計(jì)方法的設(shè)計(jì),達(dá)到提高室內(nèi)運(yùn)動(dòng)軌跡估計(jì)的準(zhǔn)確性與魯棒性的目標(biāo)。主要研究?jī)?nèi)容有：1.傳感器噪聲處理通過(guò)分析傳感器的工作原理,確定不同使用場(chǎng)景下的傳感器數(shù)據(jù)組成；通過(guò)分析不同噪聲的特性,對(duì)不同使用場(chǎng)景設(shè)計(jì)不同的噪聲處理器。2.運(yùn)動(dòng)狀態(tài)的分類(lèi)與估計(jì)通過(guò)對(duì)人體的運(yùn)動(dòng)特征的分析,將運(yùn)動(dòng)狀態(tài)分解為若干特征狀態(tài),從傳感器數(shù)據(jù)中選取特征變量,討論特征狀態(tài)的估計(jì)方法,并設(shè)計(jì)運(yùn)動(dòng)狀態(tài)估計(jì)器。3.手機(jī)攜帶狀態(tài)的分類(lèi)與估計(jì)通過(guò)分析用戶(hù)對(duì)手機(jī)的使用習(xí)慣,將手機(jī)攜帶狀態(tài)分解為若干特征狀態(tài),根據(jù)傳感器數(shù)據(jù)對(duì)其特征狀態(tài)的影響,討論特征狀態(tài)的估計(jì)方法,并設(shè)計(jì)手機(jī)攜帶狀態(tài)估計(jì)器。4.運(yùn)動(dòng)軌跡估計(jì)以確定的運(yùn)動(dòng)狀態(tài)與手機(jī)攜帶狀態(tài)為基礎(chǔ),進(jìn)行高使用場(chǎng)景適用性的運(yùn)動(dòng)軌跡估計(jì)方法的設(shè)計(jì),提高其準(zhǔn)確性與魯棒性。
[Abstract]:Location-based services have been widely used in many fields, such as intelligent medical care, security protection, commercial advertising, intelligent travel, map navigation and so on. Accurate location acquisition and motion trajectory estimation are the basis of this kind of service. Because of the problems of signal reflection, multipath effect and environment variability in indoor environment, The estimation method based on the external signal (the signal generated by the equipment other than the target) can not meet the needs of the location service in the indoor environment. Mobile inertial navigation technology has the advantages of variable location region, strong environmental applicability and independent of external signals. Therefore, it is very suitable as a solution to the indoor location service problem. However, the mobile phone inertial navigation technology has the problems of high noise of sensor data, random moving state of mobile phone carrier and mobile phone carrying state, which makes the applicability of the use scene poor. Therefore, the accuracy and robustness of motion trajectory estimation are affected. Through the analysis of the working principle of the built-in sensor in the mobile phone, the data composition and noise characteristics of the sensor are determined, and different noise processors are designed for different usage scenarios. Starting with the analysis of human motion and mobile phone usage characteristics, the classification and estimation methods of motion state and mobile phone carrying state are discussed. On the basis of determining the motion state and the mobile phone carrying state and using the indoor architectural features to design the motion trajectory estimation method, the accuracy and robustness of the indoor motion trajectory estimation can be improved. The main research contents are as follows: 1. By analyzing the working principle of the sensor, the sensor data composition under different usage scenarios is determined, and different noise processors are designed for different use scenes by analyzing the characteristics of different noise. 2. The classification and estimation of motion state by analyzing the motion characteristics of human body, the motion state is decomposed into several characteristic states, the feature variables are selected from the sensor data, and the estimation method of characteristic state is discussed. And design motion state estimator. 3. The classification and estimation of mobile phone carrying state by analyzing the user's usage habits, the mobile phone carrying state is decomposed into several feature states. According to the influence of sensor data on the characteristic state, the method of feature state estimation is discussed. And the design of mobile phone carrying state estimator. 4. Based on the determined motion state and the mobile phone carrying state, the motion trajectory estimation is designed to improve the accuracy and robustness of the motion trajectory estimation method with high applicability in the use of the scene.
【學(xué)位授予單位】：西北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：TP212

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