Journal of Jilin University(Engineering and Technology Edition) ›› 2021, Vol. 51 ›› Issue (6): 2207-2215.doi: 10.13229/j.cnki.jdxbgxb20210590

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Non⁃line⁃of⁃sight identification and optimization based on virtual coordinates of anchors

Da-yang SUN1(),Xue-ying WANG1,Shuang-xue HAN1,Hui ZHONG2(),Jiang-nan DAI3   

  1. 1.College of Communication Engineering，Jilin University，Changchun 130012，China
    2.Management Center of Big Data and Network，Jilin University，Changchun 130012，China
    3.College of Software，Jilin University，Changchun 130012，China
  • Received:2021-06-30 Online:2021-11-01 Published:2021-11-15
  • Contact: Hui ZHONG E-mail:dysun@jlu.edu.cn;zhongh@jlu.edu.cn

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Abstract:

In this paper, the Non-line-of-sight (NLOS) error is identified by virtual anchor high-dimensional coordinates and its influence on positioning accuracy is weakened. In N-dimensional space, the N+1-dimensional coordinates of the anchor point are introduced, and the ranging value is modified based on the N+1-dimensional coordinates of the anchor nodes. Then the N+1-dimensional coordinates of the anchor nodes are solved by the modified value, and the positioning result of the node to be solved is optimized by iteration. The NLOS identification and localization optimization method of virtual anchor high-dimensional coordinates are tested. The results show that multiple NLOS errors can be identified by introducing virtual anchor high-dimensional components, and the localization accuracy can be effectively improved by iterative correction.

Key words: communication technology, non-line-of-sight(NLOS) identification, high dimensional coordinates, multilateration, indoor positioning

CLC Number: 

  • TP39

Fig.1

Positioning model of multilateration"

Fig.2

Non-line-of-sight identification model of virtual anchor high dimensional coordinates"

Fig.3

Flow chart of location optimization algorithm for virtual anchor point in high dimensional coordinates"

Table 1

Four anchor points and one edge are introduced into the NLOS positioning scene"

锚点编号锚点坐标/m待求点到锚点理论距离/m待求点到锚点仿真距离/m
1（0，4）45
2（4，0）44
3（4，8）44
4（8，4）44

Fig.4

Single NLOS positioning result"

Fig.5

Single NLOS positioning error changingprocess with iteration times"

Fig.6

Single NLOS positioning anchor z coordinate changing process with iteration times"

Table 2

Four anchor points and two edge areintroduced into the NLOSpositioning scene"

锚点编号锚点坐标/m待求点到锚点理论距离/m待求点到锚点仿真距离/m
1（0，4）3.1623.162
2（2，1）2.2364
3（4，4）1.4144
4（7，1）4.4724.472

Fig.7

Multiple NLOS positioning result"

Fig.8

Multiple NLOS positioning error changingprocess with iteration times"

Fig.9

Multiple NLOS positioning anchor z coordinate changing process with iteration times"

Table 3

Five anchor points and two edge areintroduced into the NLOS positioning scene"

锚点编号锚点坐标/m待求点到锚点理论距离/m待求点到锚点仿真距离/m
1（0，4）3.1623.162
2（2，1）2.2364
3（4，4）1.4145
4（7，1）4.4724.472
5（6，2）3.16233.1623

Table 4

Six anchor points and two edge are introduced into the NLOS positioning scene"

锚点编号锚点坐标/m

待求点到锚

点理论距离/m

待求点到锚

点仿真距离/m

1（0，4）3.1623.162
2（2，1）2.2364
3（4，4）1.4145
4（7，1）4.4724.472
5（6，2）3.16233.1623
6（1，5）2.82842.8284

Table 5

Seven anchor points and two edge are introduced into NLOS positioning scene"

锚点编号锚点坐标/m

待求点到锚

点理论距离/m

待求点到锚

点仿真距离/m

1（0，4）3.1623.162
2（2，1）2.2364
3（4，4）1.4145
4（7，1）4.4724.472
5（6，2）3.16233.1623
6（1，5）2.82842.8284
7（5，6）3.60563.6056

Table 6

Five anchor points and one edge areintroduced into the NLOS positioningscene in three-dimensional space"

锚点编号锚点坐标/m待求点到锚点理论距离/m待求点到锚点仿真距离/m
1（5，5，0）56
2（5，5，10）55
3（0，5，5）55
4（10，5，5）55
5（5，0，5）55

Fig.10

Single NLOS positioning result"

Fig.11

Single NLOS positioning error changing process with iteration times"

Fig.12

Single NLOS positioning anchor z coordinate changing process with iteration times"

Fig.13

Multiple NLOS positioning result"

Table 7

Six anchor points and two edge are introduced into the NLOS positioning scene inthree-dimensional space"

锚点编号锚点坐标/m待求点到锚点理论距离/m待求点到锚点仿真距离/m
1（5，5，0）59
2（5，5，10）59
3（0，5，5）55
4（10，5，5）55
5（5，0，5）55
6（6，4，6）1.73211.7321

Table 8

Seven anchor points and two edge areintroduced into the NLOS positioningscene in three-dimensional space"

锚点编号锚点坐标/m待求点到锚点理论距离/m待求点到锚点仿真距离/m
1（5，5，0）59
2（5，5，10）59
3（0，5，5）55
4（10，5，5）55
5（5，0，5）55
6（6，4，6）1.73211.7321
7（3，3，3）3.46413.4641

Table 9

Eight anchor points and two edge are introduced into the NLOS positioning scene in three-dimensional space"

锚点编号锚点坐标/m待求点到锚点理论距离/m待求点到锚点仿真距离/m
1（5，5，0）59
2（5，5，10）59
3（0，5，5）55
4（10，5，5）55
5（5，0，5）55
6（6，4，6）1.73211.7321
7（3，3，3）3.46413.4641
8（4，6，5）1.4141.414
1 孙大洋,章荣炜,李赞. 室内定位技术综述[J].无人系统技术, 2020, 3(3): 32-46.
Sun Da-yang, Zhang Rong-wei, Li Zan. Survey of indoor localization[J]. Unmanned Systems Technology, 2020, 3(3): 32-46.
2 Zhao S H, Zhang X P, Cui X W, et al. A new toa localization and synchronization system with virtually synchronized periodic asymmetric ranging network[J]. IEEE Internet of Things Journal, 2021, 8(11): 9030-9044.
3 Deng Z L, Zheng X Y, Zhang C Y, et al. A tdoa and pdr fusion method for 5g indoor localization based on virtual base stations in unknown areas[J]. IEEE Access, 2020, 8:225123-225133.
4 Ma Y T, Wang B B, Pei S Y, et al. An indoor localization method based on AOA and PDOA using virtual stations in multipath and NLOS environments for passive UHF RFID[J]. IEEE Access, 2018, 6: 31772-31782.
5 刘富, 权美静, 王柯, 等. 仿蝎子振源定位机理的位置指纹室内定位方法[J]. 吉林大学学报: 工学版, 2019, 49(6): 2076-2082.
Liu Fu, Quan Mei-jing, Wang Ke, et al. Indoor positioning method based on location fingerprinting of imitating mechanism of scorpion vibration source[J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(6): 2076-2082.
6 Cheng L, Wu H, Wu C D, et al. Indoor mobile localization in wireless sensor network under unknown NLOS errors[J]. International Journal of Distributed Sensor Networks, 2013,9(2): 4338-4348.
7 Momtaz A A, Behnia F, Amiri R, et al. NLOS identification in range-based source localization: Statistical approach[J]. IEEE Sensors Journal, 2018, 18(9): 3745-3751.
8 Yang X F. NLOS mitigation for UWB localization based on sparse pseudo input Gaussian process[J]. IEEE Sensors Journal, 2018, 18(10): 4311-4316.
9 Ma Y T, Wang B B, Pei S Y, et al. An indoor localization method based on AOA and PDOA using virtual stations in multipath and NLOS environments for passive UHF RFID[J]. IEEE Access, 2018, 6: 31772-31782.
10 Shrivastava A, Bharti P. Localization techniques in wireless sensor networks[J]. International Journal of Computer Applications, 2015,116(12):13-18.
11 Choi J S, Lee W H, Lee J H, et al. Deep learning based NLOS identification with commodity WLAN devices[J]. IEEE Transactions on Vehicular Technology, 2018, 67(4): 3295-3303.
12 Ramadan M, Sark V, Gutierrez J,et al. NLOS identification for indoor localization using random forest algorithm[C]∥In Proc 22nd Int ITG Workshop Smart Antennas, Bochum, Germany, 2018:1-5.
13 肖竹, 宋宝相, 孙宛, 等. 基于UWB定位误差统计特性分析的NLOS鉴别[J]. 吉林大学学报: 工学版, 2010, 40(5): 1381-1385.
Xiao Zhu, Song Bao-Xiang, Sun Wan, et al. NLOS identification based on statistic analysis of UWB localization error[J]. Journal of Jilin University(Engineering and Technology Edition), 2010, 40(5): 1381-1385.
14 Jiang C H, Shen J C, Chen S, et al. UWB NLOS/LOS classification using deep learning method[J]. IEEE Communications Letters, 2020, 24(10): 2226-2230.
15 Zhu Y H, Ma T F, Li Z J, et al. NLOS identification and correction based on multidimensional scaling and quasi-accurate detection[J]. IEEE Access, 2019, 7: 53977-53987.
16 Mass-Sanchez J, Vargas-Rosales C, Ruiz-Ibarra E, et al. Localization based on probabilistic multilateration approach for mobile wireless sensor networks[J]. IEEE Access, 2020, 8: 54994-55011.
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