FILA: Fine-grained indoor localization

By Kaishun Wu, Jiang Xiao, Youwen Yi, Min Gao, Lionel Ming-shuan Ni. 2012 Proceedings IEEE INFOCOM, 2012

385 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/3c5a3d5b01696e0cdc10cd25567bbc3e537bb50c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Shiwen Mao
2. Xuyu Wang
3. Lingjun Gao
4. Zheng Yang
5. Yunhao Liu
6. Chenshu Wu
7. Kyle Jamieson
8. Zimu Zhou

In Ocean Engineering

1. Shiwen Mao
2. Xuyu Wang
3. Lingjun Gao
4. Zheng Yang
5. Yunhao Liu
6. Chenshu Wu
7. Zimu Zhou
8. Kyle Jamieson

Citations in the corpus

• A Survey on Wireless Indoor Localization from the Device Perspective (2016, methodology): “As such, FILA is the first attempt at leveraging CSI for modeling-based indoor localization.”
• CSI-Based Fingerprinting for Indoor Localization: A Deep Learning Approach (2016, methodology): “model to obtain the relationship between the effective CSI and distance [39].”
• Electronic frog eye: Counting crowd using WiFi (2014, methodology): “Recently, Channel State Information (CSI) was used for localization [22], [23], [24].”
• LiFS: low human-effort, device-free localization with fine-grained subcarrier information (2016, methodology): “Otherwise, LiFS uses the scheme proposed in FILA [39], which is given by:”
• Non-Invasive Detection of Moving and Stationary Human With WiFi (2015, background): “A promising alternative is to exploit wireless signals to detect breathing unobtrusively by capturing chest motions during breathing [19] utilizing costly radar infrastructure.”
• WiFall: Device-free fall detection by wireless networks (2017, methodology): “After CSI has been leveraged for device-based indoor localization such as FILA [9], [29] and MODLoc [30], more efforts have been paid in device-free scenarios.”
• Precise Power Delay Profiling with Commodity Wi-Fi (2015, methodology): “A power delay profile fully characterizes a multipath channel, and has been recently used in various motion- or location-based applications [9, 17, 27, 28, 35, 37, 38, 46] — multipath channel dynamics can be unveiled from consecutive measures of the power delay profile, e.”
• From RSSI to CSI (2013, methodology): “…and devices, the past two decades have witnessed extensive wireless indoor localization techniques, including acoustic signals [Peng et al. 2007; Yang et al. 2011], ultrasound [Harter et al. 1999; Priyantha et al. 2000], FM [Chen et al. 2012], infrared This work is supported in part by the…”
• SpotFi: Decimeter Level Localization Using WiFi (2015, methodology): “RSSI based approaches: This class of systems measures the RSSI from the target at multiple APs, combines them via triangulation along with a propagation model to locate the target [3, 10, 4, 5, 11, 12, 13].”
• Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons (2016, neutral): “Some other emerging fields of Wi-Fi fingerprint-based localization may include: Channel state information (CSI) is an emerging technique to replace RSSI information [195]–[197].”
• Dynamic-MUSIC: accurate device-free indoor localization (2016, methodology): “In the last few years, fine-grained CSI was used for location estimation [31, 44, 51].”
• Wi-Sleep: Contactless Sleep Monitoring via WiFi Signals (2014, background): “to estimate the number of human beings within a region), and indoor localization [18].”
• Wireless Sensing for Human Activity: A Survey (2020, background): “[84], [85] re-defined the indoor propagation model based on a modified free space path loss propagation model to capture the relationship between the effective CSI readings (i.”
• Avoiding multipath to revive inbuilding WiFi localization (2013, methodology): “FILA [27] attempts to utilize the CSI to reduce the error from RSSI based ranging, but stops short of identifying the key issues with multipath and LoS/NLoS ambiguities.”