【摘要】：基于位置的服務已在智慧醫(yī)療、安全保護、商業(yè)廣告、智能出行、地圖導航等多個領(lǐng)域被廣泛應用,在信息化與自動化程度越來越高的當今社會扮演著愈加重要的角色,對用戶進行準確的位置獲取與運動軌跡估計是該類服務的基礎(chǔ)。由于室內(nèi)環(huán)境下存在信號反射,多徑效應,環(huán)境多變等問題,使得基于外部信號(被定位目標以外的設(shè)備產(chǎn)生的信號)的估計方法在室內(nèi)環(huán)境下并不能很好的滿足位置服務的需求。手機慣性導航技術(shù)具有定位區(qū)域可變、環(huán)境適用性強、不依賴外部信號的天然優(yōu)勢,因此,非常適合作為解決室內(nèi)位置服務問題的解決方案。但由于手機慣性導航技術(shù)存在傳感器數(shù)據(jù)噪聲大,手機攜帶者運動狀態(tài)與手機攜帶狀態(tài)隨機、多變的問題,使得使用場景適用性較差,從而影響運動軌跡估計的準確性與魯棒性。本文通過對手機內(nèi)置傳感器的工作原理進行分析,確定其數(shù)據(jù)組成及噪聲特性,針對不同使用場景設(shè)計不同的噪聲處理器；從人體運動特征與手機使用特征的分析入手,討論運動狀態(tài)與手機攜帶狀態(tài)的分類與估計方法；在確定的運動狀態(tài)與手機攜帶狀態(tài)的基礎(chǔ)上,并利用室內(nèi)建筑特征進行運動軌跡估計方法的設(shè)計,達到提高室內(nèi)運動軌跡估計的準確性與魯棒性的目標。主要研究內(nèi)容有：1.傳感器噪聲處理通過分析傳感器的工作原理,確定不同使用場景下的傳感器數(shù)據(jù)組成；通過分析不同噪聲的特性,對不同使用場景設(shè)計不同的噪聲處理器。2.運動狀態(tài)的分類與估計通過對人體的運動特征的分析,將運動狀態(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)的估計方法,并設(shè)計運動狀態(tài)估計器。3.手機攜帶狀態(tài)的分類與估計通過分析用戶對手機的使用習慣,將手機攜帶狀態(tài)分解為若干特征狀態(tài),根據(jù)傳感器數(shù)據(jù)對其特征狀態(tài)的影響,討論特征狀態(tài)的估計方法,并設(shè)計手機攜帶狀態(tài)估計器。4.運動軌跡估計以確定的運動狀態(tài)與手機攜帶狀態(tài)為基礎(chǔ),進行高使用場景適用性的運動軌跡估計方法的設(shè)計,提高其準確性與魯棒性。
[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.
【學位授予單位】：西北大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TP212

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本文編號：2381313