An indoor location algorithm based on Kalman filter fusion of ultra-wide band and inertial measurement unit

Li, Beibei; Hao, Zhanjun; Dang, Xiaochao

doi:10.1063/1.5117341

Cited by 11 publications

(21 citation statements)

References 34 publications

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“…The methods were tested by measuring CIR in a self-localized network of 10 Decawave TREK100 UWB evaluation kits, and the results confirmed better localization performance and less human effort compared to the narrowband DFL. The accurate positioning in complex environments was achieved by combining advantages of UWB and inertial measurement units (IMU) in [ 51 ]. First, the signal transmission law was obtained by distinguishing LoS and NLoS environment followed by eliminating the NLoS influence using maximum likelihood estimation algorithm, and finally the extended Kalman filter information fusion strategy was used.…”

Section: Related Workmentioning

confidence: 99%

UWB Radio-Based Motion Detection System for Assisted Living

Bregar

Hrovat

Mohorčič

2021

Sensors

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Because of the ageing population, the demand for assisted living solutions that can help prolonging independent living of elderly at their homes with reduced interaction with caregivers is rapidly increasing. One of the most important indicators of the users’ well-being is their motion and mobility inside their homes, used either on its own or as contextual information for other more complex activities such as cooking, housekeeping or maintaining personal hygiene. In monitoring users’ mobility, radio frequency (RF) communication technologies have an advantage over optical motion detectors because of their penetrability through the obstacles, thus covering greater areas with fewer devices. However, as we show in this paper, RF links exhibit large variations depending on channel conditions in operating environment as well as the level and intensity of motion, limiting the performance of the fixed motion detection threshold determined on offline or batch measurement data. Thus, we propose a new algorithm with an online adaptive motion detection threshold that makes use of channel impulse response (CIR) information of the IEEE 802.15.4 ultra-wideband (UWB) radio, which comprises an easy-to-install robust motion detection system. The online adaptive motion detection (OAMD) algorithm uses a sliding window on the last 100 derivatives of power delay profile (PDP) differences and their statistics to set the threshold for motion detection. It takes into account the empirically confirmed observation that motion manifests itself in long-tail samples or outliers of PDP differences’ probability density function. The algorithm determines the online threshold by calculating the statistics on the derivatives of the 100 most recent PDP differences in a sliding window and scales them up in the suitable range for PDP differences with multiplication factors defined by a data-driven process using measurements from representative operating environments. The OAMD algorithm demonstrates great adaptability to various environmental conditions and exceptional performance compared to the offline batch algorithm. A motion detection solution incorporating the proposed highly reliable algorithm can complement and enhance various assisted living technologies to assess user’s well-being over long periods of time, detect critical events and issue warnings or alarms to caregivers.

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Section: Related Workmentioning

confidence: 99%

UWB Radio-Based Motion Detection System for Assisted Living

Bregar

Hrovat

Mohorčič

2021

Sensors

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“…Hence, most researchers concentrate on correcting pedestrian location by fusing MEMS and UWB system localization results directly [5], [26], [27], [31], which need high density UWB anchor deployment accompanied with high costs. It is the tradeoff between set costs and localization accuracy.…”

Section: Problem Statementmentioning

confidence: 99%

“…In outdoor scenarios, the Chinese BeiDou Navigation System (BDS), the Russian Gronus (GLONASS), the American Global Positioning System (GPS), and the European Galileo positioning and navigation system can provide comparatively high-quality location service [4]. However, due to the building and urban canyon blocking effect, the electromagnetic satellite signals will be attenuated or distorted under indoor environment [5]. Moreover, people spend most of time staying in room, it has great research potentiality and commercial value in indoor location system development.…”

Section: Introductionmentioning

confidence: 99%

“…Qigao Fan et al designed a Double-State Adaptive Kalman Filter (DSAKF) algorithm based on Sage-Husa adaptive Kalman filter and fading adaptive Kalman filter to fuse INS and UWB localization results [27]. In order to extract useful information from UWB ranging results under NLoS environment, Beibei Li et al used the maximum likelihood estimation algorithm to eliminate the influence of NLoS on the transmitted signal for better UWB system localization, and adopted the extended Kalman filter to fuse INS and UWB position result [5]. It could be seen that current indoor position researches are mostly concentrating on information fusion between INS and UWB localization system with multiple anchors.…”

Section: Introductionmentioning

confidence: 99%

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Single UWB Anchor Aided PDR Heading and Step Length Correcting Indoor Localization System

et al. 2021

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“…Cao et al [ 31 ] designed a UWB ranging and IMU fusion algorithm which used UWB ranging and heading (provided by IMU) to calculate target speed, and an extended Kalman filter to fuse IMU and UWB ranging constricted by estimated speed. Li et al [ 32 ] used an extended Kalman filter to fuse a UWB localization system (not ranging) and IMU, and they also discussed the fusion system under LoS and NLoS environments. Shi et al [ 33 ] used commercial IMU and UWB ranging to calculate anchor coordinates which simplified the deployment of the UWB system, after which the UWB measurements and inertial measurements were fused by a tightly-coupled error-state Kalman filter.…”

Section: Related Workmentioning

confidence: 99%

A CSI-Based Indoor Positioning System Using Single UWB Ranging Correction

Long

Kong

Zhang

et al. 2021

Sensors

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A fingerprint-based localization system is an economic way to solve an indoor positioning problem. However, the traditional off-line fingerprint collection stage is a time-consuming and laborious process which limits the use of fingerprint-based localization systems. In this paper, based on ubiquitous Wireless Fidelity (Wi-Fi) equipment and a low-cost Ultra-Wideband (UWB) ranging system (with only one UWB anchor), a ready-to-use indoor localization system is proposed to realize long-term and high-accuracy indoor positioning. More specifically, in this system, it is divided into two stages: (1) an initial stage, and (2) a positioning stage. In the initial stage, an Inertial Measure Unit (IMU) is used to calculate the position using Pedestrian Dead Reckon (PDR) algorithm within a preset number of steps, and the location-related fingerprints are collected to train a Convolutional Neural Network (CNN) regression model; simultaneously, in order to make the UWB ranging system adapt to the Non-Line-of-Sight (NLoS) environment, the increments of acceleration and angular velocity in IMU and the increments of single UWB ranging measures are correlated to pre-train a Supported Vector Regression (SVR). After reaching the threshold of time or step number, the system is changed into a positioning stage, and the CNN predicts the position calibrated by corrected UWB ranging. At last, a series of practical experiments are conducted in the real environment; the experiment results show that, due to the corrected UWB ranging measures calibrating the CNN parameters in every positioning period, this system has stable localization results in a comparative long-term range. Additionally, it has the advantages of stability, low cost, anti-noise, etc.

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An indoor location algorithm based on Kalman filter fusion of ultra-wide band and inertial measurement unit

Cited by 11 publications

References 34 publications

UWB Radio-Based Motion Detection System for Assisted Living

UWB Radio-Based Motion Detection System for Assisted Living

Single UWB Anchor Aided PDR Heading and Step Length Correcting Indoor Localization System

A CSI-Based Indoor Positioning System Using Single UWB Ranging Correction

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