Wi-Fi RTT/RSS fusion localization CRLB derivation and optimal access points layout design

doi:10.11947/j.AGCS.2024.20230220.

Abstract

Abstract:

The fine time measurement (FTM) protocol-based Wi-Fi RTT positioning is currently a research spotlight in the community. However, the performance evaluation methods of localization algorithms are relatively simplistic and lack theoretical basis. Furthermore, the impact of Wi-Fi access points (AP) layout on positioning accuracy has not been thoroughly studied. This paper focuses on smartphone-based Wi-Fi FTM as the research object. It derives the Cramer-Rao lower bound (CRLB) of the Wi-Fi RTT/RSS hybrid positioning method and clarifies the theoretical CRLB relationships of the single and hybrid positioning methods, which establishes a theoretical foundation for algorithm performance evaluation. The influence of Wi-Fi AP deployments on the localization accuracy of the RTT/RSS fusion positioning is studied, and an optimal access point layout approach for Wi-Fi RTT/RSS hybrid positioning is designed based on the enhanced genetic algorithm (EGA) and CRLB. Research shows that Wi-Fi RSS/RTT fusion localization is also an efficient FTM positioning method. The proposed EGA and CRLB-based optimal layout approach for Wi-Fi APs can quickly produce the optimal access point deployment strategy for the positioning area. The experimental results reveal that under the optimal layout of 7 Wi-Fi APs, the theoretical accuracy of Wi-Fi RSS, RTT, and RSS/RTT fusion positioning in the testing site of this manuscript is 0.92, 1.07 and 0.61 m, respectively. The research work provides theoretical support for evaluating the performance of Wi-Fi FTM positioning and offers practical strategies for deploying Wi-Fi APs effectively, thereby reducing positioning investment.

Key words: indoor positioning and navigation, Wi-Fi fine time measurement, smartphone-based positioning, Wi-Fi AP layout, Cramer-Rao lower bound, enhanced genetic algorithm

CLC Number:

P228

Meng SUN, Yunjia WANG, Qianxin WANG, Guoliang CHEN, Zengke LI. Wi-Fi RTT/RSS fusion localization CRLB derivation and optimal access points layout design[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(10): 1993-2006.

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定位方法	NLoS/LoS识别	测距补偿	测试场景	定位精度
Wi-Fi FTM+地图^[6-7]	否	无	试验室办公环境(>1000 m²)	<2 m (90%)
Wi-Fi FTM+GPS+里程计^[10]	否	有/多径补偿	市区街道/住宅区/郊区环境	1.3 m/2.1 m/0.8 m
Wi-Fi FTM+RSS测距^[15]	否	有/钟差补偿	室内房间(16.7 m×12.14 m)	1.44 m
Wi-Fi FTM+RSS测距+PDR^[16]	否	有/RSS测距	建筑楼/办公室	0.58 m(50%)
Wi-Fi RSS测距+FTM+PDR^[17]	否	有/RSS测距	2层试验室环境(33 m×9 m)	<1.1 m(67.5%)
Wi-Fi RSS测距+FTM+PDR^[18]	无	有/RSS测距	室内办公环境(约126 m²)	0.39 m
时空约束的Wi-Fi FTM定位^[19]	无	无	办公室环境	<1 m (80%)
基于高斯模型的Wi-Fi FTM定位^[22]	是	无	试验室办公环境(20 m×8 m)	<1 m
基于高斯过程回归的Wi-Fi FTM定位^[23]	是	有/NLOS误差补偿	试验室办公环境(20 m×8 m)	<1 m
Wi-Fi FTM+PDR^[24]	是	有/测距误差补偿	试验室办公环境(20 m×8 m)	0.98 m
Wi-Fi FTM+Encoder+INS^[25]	否	无	LoS/NLoS环境	0.54 m/0.77 m
Wi-Fi FTM+地图+MEMS^[26]	是	无	2层试验室环境	<1 m (94%)

定位方法	最小值	最大值	平均值	75 th	90 th
RSS	0.16	3.42	1.16	1.56	2.06
RTT	0.47	3.08	1.35	1.76	2.11
RSS/RTT	0.10	2.12	0.74	0.93	1.20

AP数量	统计量	RSS/m	RTT/m	RSS/RTT/m
3	均值	2.05	2.32	1.20
	75 th	2.52	2.87	1.37
	90 th	3.61	3.78	2.03
4	均值	1.88	2.13	1.09
	75 th	2.42	2.80	1.25
	90 th	3.51	3.71	1.94
5	均值	1.78	1.97	1.00
	75 th	2.35	2.62	1.19
	90 th	3.46	3.55	1.78

定位方法	最小值	最大值	平均值	75 th	90 th
RSS	0.41	1.72	0.92	1.05	1.18
RTT	0.75	1.89	1.07	1.13	1.35
RSS/RTT	0.17	1.23	0.61	0.68	0.77