SIA OpenIR  > 工业控制网络与系统研究室
An Improved Kalman Filtering Method for Indoor Location
Guo TT(郭廷廷); Liu MZ(刘明哲); Qiao F(乔枫); Xu AD(徐皑冬); Liu QN(刘秦宁); Zhang N(张凝)
Department工业控制网络与系统研究室
Conference Name2016 2nd IEEE International Conference on Computer and Communications (ICCC 2016)
Conference DateOctober 14-17, 2016
Conference PlaceChengdu, China
Source Publication2016 2nd IEEE International Conference on Computer and Communications (ICCC 2016)
PublisherIEEE
Publication PlaceNew York
2016
Pages1747-1751
Indexed ByEI ; CPCI(ISTP)
EI Accession number20172303742204
WOS IDWOS:000411576803005
Contribution Rank1
ISSN1095-2055
ISBN978-1-4673-9026-2
KeywordIndoor Location Non-line Of Sight (Nlos) Location Algorithm Kalman Filtering Location Accuracy
AbstractIndoor real time location technology is widely used in large indoor space, and the location algorithm is the key part of the technology. For the signal interference problems in non-line of sight (NLOS) environment and the deficiency of the existing algorithms, an improved indoor wireless location algorithm based on Kalman filtering was proposed and the experimental tests are carried out. The experimental results show that the result of the two correction of Kalman filtering algorithm based on the discarded measurement method and the gain back method is closest to expectations. By using the two correction of Kalman filtering method, the experimental platform is set up to carry out the location test. The test results show that the location precision of the proposed method is very high, and the results are highly consistent with the experimental results.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/19508
Collection工业控制网络与系统研究室
Corresponding AuthorGuo TT(郭廷廷)
Affiliation1.Faculty of Information and Control Engineering, Shenyang Jianzhu University (SJZU), Shenyang, China
2.Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang, China
Recommended Citation
GB/T 7714
Guo TT,Liu MZ,Qiao F,et al. An Improved Kalman Filtering Method for Indoor Location[C]. New York:IEEE,2016:1747-1751.
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