基于慣性傳感器的行人室內(nèi)軌跡推算與定位算法研究
發(fā)布時間：2018-11-23 11:43
【摘要】：近年來,隨著基于位置服務(wù)(Location Based Service,LBS)應(yīng)用的飛速發(fā)展以及微電子機(jī)械系統(tǒng)(Micro-Electro-Mechanical System,MEMS)技術(shù)的不斷完善成熟,基于慣性傳感器的行人慣性導(dǎo)航與軌跡追蹤技術(shù)因其適用環(huán)境廣、抗外界干擾能力強(qiáng)以及對用戶無妨礙等優(yōu)點(diǎn),受到越來越多研究者的關(guān)注與青睞。然而,由于連續(xù)二次積分運(yùn)算引起的累計(jì)誤差問題嚴(yán)重約束了慣性導(dǎo)航算法的定位精度,修正推算過程中的累計(jì)誤差成為了提高算法性能的關(guān)鍵。此外,隨著智能終端硬件的更新升級,其內(nèi)置的嵌入式微傳感單元為其作為慣性導(dǎo)航與軌跡追蹤算法的實(shí)現(xiàn)平臺提供了可能。如今,以新興智能終端為平臺的行人室內(nèi)軌跡追蹤與定位算法逐漸成為熱門研究領(lǐng)域。本文以慣性傳感器為主要研究對象,分別針對可穿戴傳感節(jié)點(diǎn)與智能終端兩種平臺中行人慣性導(dǎo)航與軌跡追蹤算法實(shí)現(xiàn)改良與創(chuàng)新。主要研究成果如下:(1)在可穿戴傳感節(jié)點(diǎn)平臺上,針對傳統(tǒng)捷聯(lián)式慣性導(dǎo)航系統(tǒng)由于連續(xù)二次積分引起的累計(jì)誤差問題,本文提出了一種以行人步伐為周期的分段式軌跡推算算法。該算法首先對行人步伐狀態(tài)作劃分并判別,而后在每一個步伐周期中不同狀態(tài)內(nèi)分別計(jì)算行人腳體的旋轉(zhuǎn)角度、水平位移與偏航角,最終逐步更新行人的位置坐標(biāo)并復(fù)原其運(yùn)動軌跡。實(shí)際驗(yàn)證表明,本文算法的軌跡推算結(jié)果中終點(diǎn)與總距離估計(jì)誤差均值分別為0.74m與1.41m,對比傳統(tǒng)捷聯(lián)式慣性導(dǎo)航算法在精確度方面有顯著提高。(2)在智能終端平臺上,提出了一種基于運(yùn)動狀態(tài)判別的多樓層室內(nèi)環(huán)境中行人航位推算算法。該算法主要包括兩個部分:第一,利用智能終端采集的加速度數(shù)據(jù)模值的極值差與無線接入點(diǎn)信號強(qiáng)度值數(shù)據(jù)來判別行人在運(yùn)動過程中的不同狀態(tài)。實(shí)際驗(yàn)證表明,本文算法運(yùn)動狀態(tài)誤判率均值為3.74%,相比傳統(tǒng)基于均值與方差特征的判別算法在準(zhǔn)確率方面有顯著提高;第二,根據(jù)運(yùn)動狀態(tài)判別結(jié)果,針對傳統(tǒng)行人航位推算算法中步伐數(shù)目檢測、步伐長度估算與航向角估算等步驟作優(yōu)化與調(diào)整,實(shí)現(xiàn)了其基于行人運(yùn)動狀態(tài)的調(diào)整以及從二維平面向三維空間的擴(kuò)展。實(shí)際驗(yàn)證表明,本文算法軌跡推算結(jié)果中坐標(biāo)誤差小于1.5m的步伐點(diǎn)比例高于85%以上,精確度較高。(3)針對本文提出的行人軌跡推算算法,分別搭建了以Shimmer傳感節(jié)點(diǎn)為平臺的行人慣性導(dǎo)航系統(tǒng)與以安卓智能手機(jī)為平臺的行人多樓層室內(nèi)定位系統(tǒng)作驗(yàn)證。系統(tǒng)實(shí)現(xiàn)過程主要由可穿戴傳感節(jié)點(diǎn)校準(zhǔn)、傳感節(jié)點(diǎn)間數(shù)據(jù)通信、智能手機(jī)數(shù)據(jù)采集發(fā)送、地圖頁面定位顯示等步驟組成。實(shí)際驗(yàn)證結(jié)果表明系統(tǒng)在精確度與穩(wěn)定性方面均有優(yōu)越表現(xiàn)。
[Abstract]:In recent years, with the rapid development of location-based service (Location Based Service,LBS) applications and the continuous improvement of Micro-Electro-Mechanical System,MEMS technology, Pedestrian inertial navigation and track tracking technology based on inertial sensor has been paid more and more attention and favor by more and more researchers because of its wide application environment strong ability of resisting external interference and no hindrance to users. However, the cumulative error caused by the continuous quadratic integral operation seriously restricts the positioning accuracy of the inertial navigation algorithm, and the correction of the cumulative error in the calculation process becomes the key to improve the performance of the algorithm. In addition, with the updating and upgrading of intelligent terminal hardware, its embedded micro-sensor unit makes it possible to implement inertial navigation and trajectory tracking algorithm. Nowadays, pedestrian indoor track tracking and location algorithm based on new intelligent terminal has become a hot research field. In this paper, the inertial sensor as the main research object, the wearable sensor node and intelligent terminal in the two platforms of pedestrian inertial navigation and track tracking algorithm to achieve improvement and innovation. The main research results are as follows: (1) on the wearable sensor node platform, the accumulative errors caused by the continuous quadratic integration of the traditional strapdown inertial navigation system are discussed. In this paper, a segmented trajectory estimation algorithm based on pedestrian steps is proposed. The algorithm first divides and discriminates the pedestrian step status, and then calculates the rotation angle, horizontal displacement and yaw angle of pedestrian foot body in different states in each step cycle. Finally, the position coordinates of pedestrians are updated step by step and their motion tracks are restored. The experimental results show that the mean values of the estimation errors of the end point and the total distance are 0.74m and 1.41mrespectively. Compared with the traditional strapdown inertial navigation algorithm, the accuracy of the algorithm is significantly improved. (2) on the platform of intelligent terminal, a new algorithm based on motion state discrimination is proposed to calculate the pedestrian position in multi-floor indoor environment. The algorithm mainly consists of two parts: first, using the extreme value difference of the acceleration data collected by the intelligent terminal and the signal intensity data of the wireless access point to distinguish the different states of the pedestrian in the process of motion. The actual verification shows that the average error rate of motion state of this algorithm is 3.74, which is significantly higher than the traditional discriminant algorithm based on the feature of mean and variance. Secondly, according to the result of motion state discrimination, the steps such as step number detection, step length estimation and heading angle estimation are optimized and adjusted in the traditional footpath reckoning algorithm. It is based on the adjustment of pedestrian motion state and the expansion from two-dimensional plane to three-dimensional space. The actual verification shows that the proportion of step points whose coordinate error is less than 1.5 m is more than 85%, and the accuracy is high. (3) aiming at the proposed algorithm, The pedestrian inertial navigation system based on Shimmer sensor node and the multi-floor indoor positioning system based on Android smart phone are built. The system is mainly composed of wearable sensor node calibration, sensor node data communication, smart phone data acquisition and transmission, map page location and display, and so on. The experimental results show that the system is superior in accuracy and stability.
【學(xué)位授予單位】：南京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN96;TP212
本文編號：2351482
[Abstract]:In recent years, with the rapid development of location-based service (Location Based Service,LBS) applications and the continuous improvement of Micro-Electro-Mechanical System,MEMS technology, Pedestrian inertial navigation and track tracking technology based on inertial sensor has been paid more and more attention and favor by more and more researchers because of its wide application environment strong ability of resisting external interference and no hindrance to users. However, the cumulative error caused by the continuous quadratic integral operation seriously restricts the positioning accuracy of the inertial navigation algorithm, and the correction of the cumulative error in the calculation process becomes the key to improve the performance of the algorithm. In addition, with the updating and upgrading of intelligent terminal hardware, its embedded micro-sensor unit makes it possible to implement inertial navigation and trajectory tracking algorithm. Nowadays, pedestrian indoor track tracking and location algorithm based on new intelligent terminal has become a hot research field. In this paper, the inertial sensor as the main research object, the wearable sensor node and intelligent terminal in the two platforms of pedestrian inertial navigation and track tracking algorithm to achieve improvement and innovation. The main research results are as follows: (1) on the wearable sensor node platform, the accumulative errors caused by the continuous quadratic integration of the traditional strapdown inertial navigation system are discussed. In this paper, a segmented trajectory estimation algorithm based on pedestrian steps is proposed. The algorithm first divides and discriminates the pedestrian step status, and then calculates the rotation angle, horizontal displacement and yaw angle of pedestrian foot body in different states in each step cycle. Finally, the position coordinates of pedestrians are updated step by step and their motion tracks are restored. The experimental results show that the mean values of the estimation errors of the end point and the total distance are 0.74m and 1.41mrespectively. Compared with the traditional strapdown inertial navigation algorithm, the accuracy of the algorithm is significantly improved. (2) on the platform of intelligent terminal, a new algorithm based on motion state discrimination is proposed to calculate the pedestrian position in multi-floor indoor environment. The algorithm mainly consists of two parts: first, using the extreme value difference of the acceleration data collected by the intelligent terminal and the signal intensity data of the wireless access point to distinguish the different states of the pedestrian in the process of motion. The actual verification shows that the average error rate of motion state of this algorithm is 3.74, which is significantly higher than the traditional discriminant algorithm based on the feature of mean and variance. Secondly, according to the result of motion state discrimination, the steps such as step number detection, step length estimation and heading angle estimation are optimized and adjusted in the traditional footpath reckoning algorithm. It is based on the adjustment of pedestrian motion state and the expansion from two-dimensional plane to three-dimensional space. The actual verification shows that the proportion of step points whose coordinate error is less than 1.5 m is more than 85%, and the accuracy is high. (3) aiming at the proposed algorithm, The pedestrian inertial navigation system based on Shimmer sensor node and the multi-floor indoor positioning system based on Android smart phone are built. The system is mainly composed of wearable sensor node calibration, sensor node data communication, smart phone data acquisition and transmission, map page location and display, and so on. The experimental results show that the system is superior in accuracy and stability.
【學(xué)位授予單位】：南京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN96;TP212
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