A three-dimensional robust ridge estimation positioning method for UWB in a complex environment

Li, Shuaixin; Li, Guangyun; Wang, Li; Zhou, Yue; Peng, Yifan; Fu, Jingyang

doi:10.1016/j.asr.2017.10.040

Cited by 20 publications

(7 citation statements)

References 21 publications

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“…1 Ultrawide band (UWB) technology is widely used in indoor navigation, personnel tracking, underground positioning, unmanned transportation, and other related fields because of high positioning accuracy, low power consumption, good penetration, and strong anti-interference ability. 2,3 At present, the most common UWB positioning algorithms include the time of arrival (TOA) and the time difference of arrival (TDOA). 4 The TOA positioning algorithm calculates the distance between the tag and the base station by recording the transmission time and reception time of the signal between the tag and the base station.…”

Section: Introductionmentioning

confidence: 99%

Posture algorithm for mobile robot based on ultrawide band

Sun

Xie

Xiong

et al. 2022

International Journal of Advanced Robotic Systems

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Inertial measurement unit or other navigation devices are used to obtain the posture information of most mobile robots based on ultrawide band. However, problems, such as zero drift, temperature drift, and error increasing with time, exist in inertial measurement unit and other navigation devices. To overcome these problems, a posture algorithm for mobile robot based on ultrawide band is proposed in this article. Real-time posture information can be obtained by the posture algorithm without using inertial measurement unit and other navigation devices. Simulated results show that the mean absolute error and root mean square error of posture angle in the global coordinate system are 0.951° and 1.169°, respectively. Both the simulated and experimental trajectories show good agreement with the ideal trajectory. The results indicate that the posture data can be obtained accurately by the posture algorithm and the accuracy can meet the requirements for most mobile robots. This article is expected to be of great guiding significance for the development of mobile robots.

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Section: Introductionmentioning

confidence: 99%

Posture algorithm for mobile robot based on ultrawide band

Sun

Xie

Xiong

et al. 2022

International Journal of Advanced Robotic Systems

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show abstract

“…The shortcoming is that the position of transmitters must be known. The usual algorithms of multilateral positioning include LS [14,20], weighted least squares (WLS) [21,22], and trilateration [21,23]. However, the range-finding method based on RSS is easily affected by the environment, and its ranging accuracy is very low.…”

Section: Introductionmentioning

confidence: 99%

WiFi RTT Indoor Positioning Method Based on Gaussian Process Regression for Harsh Environments

Cao

Wang

et al. 2020

IEEE Access

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A novel two-way ranging approach was introduced into the Wireless Fidelity (WiFi) standard, and its ranging accuracy reached one meter in a low multipath environment. However, in harsh environments due to multipath or non-line of sight (NLOS), the range measurement based on the WiFi round trip time (RTT) usually has low accuracy and cannot maintain the one-meter accuracy. Thus, this paper proposes an indoor positioning method based on Gaussian process regression (GPR) for harsh environments. There are two stages in the proposed method: construction of a positioning model and location estimation. In the model construction stage, based on known positions of access points (APs), we can determine the position coordinates of some ground points and the reference distances between them and the APs, and the offline ranging difference fingerprints can be generated by the reference distances, which means that there is no need to collect data. Gaussian process regression (GPR) utilizes offline ranging difference fingerprints based on the reference distance to establish a positioning model, and the particle swarm optimization (PSO) algorithm is employed to estimate the GPR hyperparameters. In the location estimation stage, the gathered actual range measurements generate the online ranging difference fingerprint, which is the input data of the positioning model. The output of the model is the estimated position of the smartphone. Experimental results show that the mean errors (MEs) of the proposed method and Least Squares (LS) algorithm are 1.097 and 3.484 meters, respectively, in a harsh environment, and the positioning accuracy of the proposed method improved by 68.5% compared with the LS algorithm.

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“…UWB positioning technology has advantages that other positioning technologies cannot match. It has strong antiinterference ability, high transmission rate, high security, strong penetrating ability, high multipath resolution, and relatively simple system structure [9,10]. Communication with nanosecond narrow pulses does not require carrier signal modulation, and its positioning accuracy can reach centimeter level [11].…”

Section: Introductionmentioning

confidence: 99%

Research on Wavelet Threshold Denoising Method for UWB Tunnel Personnel Motion Location

Liu

Zhang

et al. 2020

Mathematical Problems in Engineering

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In the process of tunnel construction, the problems of strong sealing, inconvenient communication, and harsh environment pose a serious threat to the personal safety of construction workers. erefore, personnel positioning technology has important application value in tunnel safety construction. A special environment for tunnel personnel positioning and the ultrawideband (UWB) positioning system are affected by personnel movement, which leads to the problem of lowering positioning accuracy. A wavelet threshold denoising method for motion positioning of people in tunnels is proposed. e positioning algorithm of the method adopts a three-sided positioning algorithm based on symmetric double-sided two-way ranging. e wavelet analysis is used to decompose the motion signal of the personnel in the tunnel, and the low frequency coefficient and high frequency coefficient of the signal are decomposed to determine the influence of the motion noise of the personnel on the UWB positioning. e soft threshold function and the hard threshold function are, respectively, selected to perform wavelet threshold denoising on the motion positioning result in the tunnel. According to the denoising effect, the db5 wavelet 5-layer decomposition, under the heuristic threshold estimation criterion, the soft threshold function denoising is the best denoising method. e verification by the positioning experiment shows that the method is suitable for tunnel personnel positioning. e wavelet threshold denoising method can weaken the influence of outliers in the motion positioning of UWB personnel and improve the positioning accuracy.

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A three-dimensional robust ridge estimation positioning method for UWB in a complex environment

Cited by 20 publications

References 21 publications

Posture algorithm for mobile robot based on ultrawide band

Posture algorithm for mobile robot based on ultrawide band

WiFi RTT Indoor Positioning Method Based on Gaussian Process Regression for Harsh Environments

Research on Wavelet Threshold Denoising Method for UWB Tunnel Personnel Motion Location

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