基于Wi-Fi即時(shí)定位與映射像素模板匹配的室內(nèi)運(yùn)動(dòng)地圖構(gòu)建與定位
doi: 10.11999/JEIT170781
-
2.
(重慶郵電大學(xué)移動(dòng)通信技術(shù)重慶市重點(diǎn)實(shí)驗(yàn)室 重慶 400065) ②(天津師范大學(xué)天津市無線移動(dòng)通信與無線電能傳輸重點(diǎn)實(shí)驗(yàn)室 天津 300387)
國家自然科學(xué)基金(61301126, 61471077),長江學(xué)者和創(chuàng)新團(tuán)隊(duì)發(fā)展計(jì)劃(IRT1299),重慶市科委重點(diǎn)實(shí)驗(yàn)室專項(xiàng)經(jīng)費(fèi),重慶市基礎(chǔ)科學(xué)與前沿技術(shù)研究項(xiàng)目(cstc2017jcyjAX0380, cstc2015jcyjBX0065),重慶市高校優(yōu)秀成果轉(zhuǎn)化資助項(xiàng)目(KJZH17117),重慶市研究生科研創(chuàng)新項(xiàng)目(CYS17221)
Indoor Mobility Map Construction and Localization Based on Wi-Fi Simultaneous Localization and Mapping Pixel Template Matching
-
2.
(Chongqing Key Laboratory of Mobile Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)
The National Natural Science Foundation of China (61301126, 61471077), The Program for Changjiang Scholars and Innovative Research Team in University (IRT1299), The Special Fund of CSTC Key Laboratory, The Fundamental Science and Frontier Technology Research Project of Chongqing (cstc2017jcyjAX0380, cstc2015jcyjBX0065), The University Outstanding Achievement Transformation Project of Chongqing (KJZH17117), Postgraduate Scientific Research and Innovation Project of Chongqing (CYS17221)
-
摘要: 傳統(tǒng)指紋定位方法由于建庫人力時(shí)間開銷大、系統(tǒng)通用性不強(qiáng)約束著指紋定位系統(tǒng)的推廣,為了解決該問題同時(shí)結(jié)合即時(shí)定位與映射(SLAM)技術(shù)的優(yōu)勢,該文提出一種新的Wi-Fi/微機(jī)電系統(tǒng)(MEMS)融合室內(nèi)運(yùn)動(dòng)地圖構(gòu)建與定位方法。首先利用行人航跡推算(PDR)、最小描述長度(MDL)原則和基于密度的空間聚類算法(DBSCAN)對眾包運(yùn)動(dòng)軌跡進(jìn)行預(yù)處理,提出基于軌跡主路徑的運(yùn)動(dòng)地圖構(gòu)建方法。之后提出基于像素模板的地圖匹配方法獲取地圖的絕對位置,并采用抗差擴(kuò)展卡爾曼濾波(EKF)對目標(biāo)位置進(jìn)行最優(yōu)估計(jì)。實(shí)驗(yàn)結(jié)果表明,所提聚類方法可以準(zhǔn)確構(gòu)建各區(qū)域運(yùn)動(dòng)地圖,在少量的人力時(shí)間開銷下實(shí)現(xiàn)較高的定位精度。
-
關(guān)鍵詞:
- Wi-Fi /
- 室內(nèi)定位 /
- 即時(shí)定位與映射 /
- 模板匹配 /
- 密度聚類
Abstract: This papers propose a novel integrated Wi-Fi and Micro Electronic Mechanical Systems (MEMS) indoor mobility map construction and localization approach. First of all, a method is proposed for constructing mobility map based on trajectory main path by applying the Pedestrian Dead Reckoning (PDR), Minimum Description Length (MDL), and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithms to the processing process of crowdsourcing trajectories. Then a pixel template matching technique is innovatively presented to obtain the absolute position of the map. Finally, the robust Extended Kalman Filter (EKF) algorithm is utilized to estimate the optimal target position. Which means the Simultaneous Localization And Mapping (SLAM) are completed. The experimental results show that the method of proposed clustering can accurately distinguish the motion regions. Also, the precision positioning can be realized with less labor and time through matching the absolute position of the motion map in the real environment successfully. -
KANG W, GAO S, WANG H, et al. Multi-modal signal propagation model based on time reversal method[C]. IEEE International Conference on Electronic Measurement Instruments, Qingdao, China, 2016: 958-963. doi: 10.1109/ ICEMI.2015.7494364. LEE J Y, KIM H S, CHOI K H, et al. Adaptive GPS/INS integration for relative navigation[J]. GPS Solutions, 2016, 20(1): 63-75. doi: 10.1007/s10291-015-0446-4. EICHHARDT I, JANKO Z, and CHETVERIKOV D. Novel methods for image-guided ToF depth upsampling[C]. IEEE International Conference on Systems, Man Cybernetics, Budapest, Hungary, 2017: 2073-2078. doi: 10.1109/SMC. 2016.7844545. ZHU D, CHOI J, and HEATH R W. Auxiliary beam pair enabled AoD and AoA estimation in mmWave FD-MIMO systems[C]. Global Communications Conference, Washington, DC USA, 2016: 1-6. doi: 10.1109/GLOCOM.2016.7841616. PAK J M, AHN C K, PENG S, et al. Distributed hybrid particle/FIR filtering for mitigating NLOS effects in TOA based localization using wireless sensor networks[J]. IEEE Transactions on Industrial Electronics, 2017, 64(6): 5182-5191. doi: 10.1109/TIE.2016.2608897. CHO H and KWON Y. RSS-based indoor localization with PDR location tracking for wireless sensor networks[J]. AEU- International Journal of Electronics and Communications, 2016, 70(3): 250-256. doi: 10.1016/j.aeue.2015.12.004. YOUSSEF M and AGRAWALA A. The Horus WLAN location determination system[C] International Conference on Mobile Systems, Applications Services, Washington, USA, 2005: 205-218. doi: 10.1145/1067170.1067193. TIAN Z, FANG X, ZHOU M, et al. Smartphone-based indoor integrated WiFi/MEMS positioning algorithm in a multi- floor environment[J]. Micromachines, 2015, 6(3): 347-363. doi: 10.3390/mi6030347. ZHOU M, TANG Y, NIE W, et al. GrassMA: Graph-based semi-supervised manifold alignment for indoor WLAN localization[J]. IEEE Sensors Journal, 2017, 17(21): 7086-7095. doi: 10.1109/JSEN.2017.2752844. 陳嶺, 許曉龍, 楊清, 等. 基于三次樣條插值的無線信號(hào)強(qiáng)度衰減模型[J]. 浙江大學(xué)學(xué)報(bào)(工學(xué)版), 2011, 45(9): 1521-1527. doi: 10.3785 /j.issn.1008-973X.2011.09.003. CHEN Ling, XU Xiaolong, YANG Qing, et al. Wireless signal strength propagation model base on cubic spline interpolation[J]. Journal of Zhejiang University (Engineering Science), 2011, 45(9): 1521-1527. doi: 10.3785/j.issn.1008- 973X.2011.09.003. LI B, WANG Y, LEE H K, et al. Method for yielding a database of location fingerprints in WLAN[J]. IEE Proceedings Communications, 2005, 152(5): 580-586. doi: 10.1049/ip-com:20050078. DING M, WANG P, LOPEZ P D, et al. Performance impact of LoS and NLoS transmissions in dense cellular networks [J]. IEEE Transactions on Wireless Communications, 2016, 15(3): 2365-2380. doi: 10.1109/TWC.2015.2503391. ANGERMANN M and ROBERTSON P. FootSLAM: Pedestrian simultaneous localization and mapping without exteroceptive sensors hitchhiking on human perception and cognition[J]. Proceedings of the IEEE, 2012, 100(5): 1840-1848. doi: 10.1109/JPROC.2012.2189785. BRUNO L and ROBERTSON P. WiSLAM: Improving FootSLAM with WiFi[C]. International Conference on Indoor Positioning and Indoor Navigation, Guimares, Portugal, 2011: 1-10. doi: 10.1109/IPIN.2011.6071916. KOO B, LEE S, LEE M, et al. PDR/fingerprinting fusion indoor location tracking using RSS recovery and clustering[C]. International Conference on Indoor Positioning and Indoor Navigation, Alberta, Canada, 2015: 699-704. doi: 10.1109/ IPIN.2014.7275546. GOEBL S, TONCH A, BOHM C, et al. MeGS: Partitioning meaningful subgraph structures using minimum description length[C]. IEEE International Conference on Data Mining, New Orleans, USA, 2017: 889-894. doi: 10.1109/ICDM. 2016.0108. ZHOU R, ZHANG S, CHEN C, et al. A distance and density-based clustering algorithm using automatic peak detection[C]. IEEE International Conference on Smart Cloud, New York, USA, 2016: 176-183. doi: 10.1109/SmartCloud. 2016.39. ZHAO L, QIU H, and FENG Y. Analysis of a robust Kalman filter in loosely coupled GPS/INS navigation system[J]. Measurement, 2016, 80: 138-147. doi: 10.1016/j.measurement. 2015.11.008. NIWATTANAKUL S, SINGTHONGCHAI J, NAENUDORN E, et al. Using of Jaccard Coefficient for Keywords Similarity[J]. Lecture Notes in Engineering and Computer Science, 2013, 2202(1): 380-384. doi: ISBN978- 988-19251-8-3. TIAN Z, JIN Y, ZHOU M, et al. Wi-Fi/MARG integration for indoor pedestrian localization[J]. Sensors, 2016, 16(12): 2100-2013. doi: 10.3390/s16122100. LEE J G, HAN J, and WHANG K Y. Trajectory clustering: A partition-and-group framework[C]. ACM SIGMOD International Conference on Management of Data, Beijing, China, 2007: 593-604. doi: 10.1145/1247480.1247546. WU C, YANG Z, ZHOU Z, et al. Mitigating large errors in WiFi-based indoor localization for smartphones[J]. IEEE Transactions on Vehicular Technology, 2017, 66(7): 6246-6257. doi: 10.1109/TVT.2016.2630713. CHOI K H, YONG H K, YOON T S, et al. Robust least squares algorithm based position and heading estimator by using range difference measurement and heading sensor[C]. IEEE Conference on Decision and Control, Georgia, USA, 2012: 1996-2001. doi: 10.1109/CDC.2012.6425914. ZHANG X, JIN Y, TAN H X, et al. CIMLoc: A crowdsourcing indoor digital map construction system for localization[C]. IEEE Sensor Networks and Information Processing, Berlin Germany, 2014: 1-6. doi: 10.1109/ ISSNIP.2014.6827640. -
計(jì)量
- 文章訪問數(shù): 1755
- HTML全文瀏覽量: 223
- PDF下載量: 196
- 被引次數(shù): 0