Single access point based indoor localization technique for augmented reality gaming for children

Kumar, Chanchal; Poovaiah, Ravi; Sen, Ajanta; Ganadas, Priya

doi:10.1109/techsym.2014.6808052

Cited by 17 publications

(6 citation statements)

References 4 publications

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“…A is the state transition matrix, H is the observation matrix, and I is a 3 × 3 identity matrix. Z (t) is the actual measurement at the current moment, and its data are the tag's coordinate data calculated by the geometric localization model in Equation (15). Referring to the tests of UWB and BMP sensors in Section 3, the process noise covariance matrix Q in the Kalman filter is set to diag([1 × 10 −4 , 1 × 10 −4 , 1 × 10 −3 ]), and the measurement noise covariance matrix R is set to diag([4 × 10 −4 , 4 × 10 −4 , 5 × 10 −3 ]).…”

Section: Optimization Of Location Estimation Based On Kalman Filteringmentioning

confidence: 99%

An Enhanced Indoor Three-Dimensional Localization System with Sensor Fusion Based on Ultra-Wideband Ranging and Dual Barometer Altimetry

Bao,

Li,

Lee

et al. 2024

Sensors

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Accurate three-dimensional (3D) localization within indoor environments is crucial for enhancing item-based application services, yet current systems often struggle with localization accuracy and height estimation. This study introduces an advanced 3D localization system that integrates updated ultra-wideband (UWB) sensors and dual barometric pressure (BMP) sensors. Utilizing three fixed UWB anchors, the system employs geometric modeling and Kalman filtering for precise tag 3D spatial localization. Building on our previous research on indoor height measurement with dual BMP sensors, the proposed system demonstrates significant improvements in data processing speed and stability. Our enhancements include a new geometric localization model and an optimized Kalman filtering algorithm, which are validated by a high-precision motion capture system. The results show that the localization error is significantly reduced, with height accuracy of approximately ±0.05 m, and the Root Mean Square Error (RMSE) of the 3D localization system reaches 0.0740 m. The system offers expanded locatable space and faster data output rates, delivering reliable performance that supports advanced applications requiring detailed 3D indoor localization.

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Section: Optimization Of Location Estimation Based On Kalman Filteringmentioning

confidence: 99%

An Enhanced Indoor Three-Dimensional Localization System with Sensor Fusion Based on Ultra-Wideband Ranging and Dual Barometer Altimetry

Bao,

Li,

Lee

et al. 2024

Sensors

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show abstract

“…This method is suitable for indoor positioning [41,42], but not for the airport surroundings where the electromagnetic signal is complex. In addition, TOF [43,44], TDOA [45][46][47][48], and AOA [49][50][51][52][53] are used to locate RFI. In addition to using a single method for positioning, there is also a joint positioning method.…”

Section: Related Workmentioning

confidence: 99%

Aerial Locating Method Design for Civil Aviation RFI: UAV Monitoring Platform and Ground Terminal System

Zhou

Xiong

Zeng

et al. 2021

J Intell Robot Syst

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A key open question in the aerial locating method is ensure that parameters that identify the location of the radio frequency interference (RFI) are monitored, and to make sure that the locating algorithm is unbiased. Furthermore, the transmission of parameters to the ground for real-time analysis and display of the RFI location is important as it provides insight into the performance advantages of the aerial location method. The main contributions of the article are four points: the first is the introduction of the angle of arrival (AOA) algorithm to civil aviation RFI location, and the integration of algorithm characteristics with unmanned aerial vehicle (UAV) operations proposing an aerial monitoring method for civil aviation RFI. Simulation results show that the two-point cross-location method obtains effective information on the location parameters of the RFI. The second is to build a UAV monitoring platform, which is as light as possible to make sure the direction finding and digital transmission devices meet the airworthiness requirements, so that the UAV can complete the data acquisition task within a safety margin. Thirdly, a ground analysis system was designed to receive information on the UAV’s parameters, enabling software manipulation to ensure safe operation under non-visual conditions. In addition to this, the monitoring data is processed in real time and algorithms are used to resolve the location of interference sources and display them on a map. The fourth one is to verify the implementation of the aerial positioning method by setting up different test scenarios. Compared with portable direction-finding equipment and ground monitoring, the test results show that the UAV-based RFI monitoring method performances better in monitoring radius and positioning accuracy with a small direction-finding error, and the advantages of the ground analysis system are highly integrated and intuitive display.

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“…The RSSI value of 1m is estimated using 2m to 5m values. The effects of variation of A (RSSI value at 1m) and n (Propagation Loss) must be studied to calculate correct distances by using RSSI signals [5][12]. Table 3 shows two cases.…”

Section: 2mentioning

confidence: 99%

Analysis of Selected Indoor Location APs for in Wi-Fi Environments

Park

Hong

Zhu³

et al. 2016

Advanced Science and Technology Letters

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Abstract. Real-time indoor positioning systems based on Wi-Fi signal strength are studied. This study is about how to decide specific three target APs based on Wi-Fi RSSI signals from several APs(access point), and calculate the distance from a mobile object to the selected reference APs by ChipconCO formula. Calculated three distances are used to position the mobile object by using the triangulation method. To overcome the positioning errors, a topology which has five Aps in a square area is proposed and analyzed.

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Single access point based indoor localization technique for augmented reality gaming for children

Cited by 17 publications

References 4 publications

An Enhanced Indoor Three-Dimensional Localization System with Sensor Fusion Based on Ultra-Wideband Ranging and Dual Barometer Altimetry

An Enhanced Indoor Three-Dimensional Localization System with Sensor Fusion Based on Ultra-Wideband Ranging and Dual Barometer Altimetry

Aerial Locating Method Design for Civil Aviation RFI: UAV Monitoring Platform and Ground Terminal System

Analysis of Selected Indoor Location APs for in Wi-Fi Environments

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