scholarly journals Simulating Signal Aberration and Ranging Error for Ultrasonic Indoor Positioning

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3548
Author(s):  
Riccardo Carotenuto ◽  
Massimo Merenda ◽  
Demetrio Iero ◽  
Francesco G. Della Corte
Keyword(s):  
Cross Correlation ◽  
Indoor Positioning ◽  
Simulation Software ◽  
Reference Points ◽  
Signal Shape ◽  
Positioning Systems ◽  
Acoustic Simulation ◽  
Ranging Error ◽  
Acoustic Diffraction ◽  
Shape And Size

Increasing efforts toward the development of positioning techniques testify the growing interest for indoor position-based applications and services. Many applications require accurate indoor positioning or tracking of people and assets, and some market sectors are starting a rapid growth of products based on these technologies. Ultrasonic systems have already been demonstrating their effectiveness and to possess the desired positioning accuracy and refresh rates. In this work, it is shown that a typical signal used in ultrasonic positioning systems to estimate the range between the target and reference points—namely, the linear chirp—due to the effects of acoustic diffraction, in some cases, undergoes a shape aberration, depending on the shape and size of the transducer and on the angle under which the transducer is seen by the receiver. In the presence of such signal shape aberrations, even one of the most robust ranging techniques, which is based on cross-correlation, provides results affected by a much greater error than expected. Numerical simulations are carried out for a typical ultrasonic chirp, ultrasonic emitter, and range technique based on cross-correlation and for a typical office room, obtained using the academic acoustic simulation software Field II. Spatial distributions of the ranging error are provided, clearly showing the favorable low error regions. The work demonstrates that particular attention must be paid to the design of the acoustic section of the ultrasonic positioning systems, considering both the shape and size of the ultrasonic emitters and the shape of the acoustic signal used.

scholarly journals Acoustic Simulation for Performance Evaluation of Ultrasonic Ranging Systems

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1298
Author(s):  
Riccardo Carotenuto ◽  
Fortunato Pezzimenti ◽  
Francesco G. Della Corte ◽  
Demetrio Iero ◽  
Massimo Merenda
Keyword(s):  
Signal To Noise Ratio ◽  
Emerging Market ◽  
Error Distribution ◽  
Simulation Software ◽  
Indoor Navigation ◽  
Positioning Systems ◽  
Acoustic Simulation ◽  
Cumulative Error ◽  
Ranging Error ◽  
Ultrasonic Ranging

The recent growing interest in indoor positioning applications has paved the way for the development of new and more accurate positioning techniques. The envisioned applications, include people and asset tracking, indoor navigation, as well as other emerging market applications, require fast and precise positioning. To this end, the effectiveness and high accuracy and refresh rate of positioning systems based on ultrasonic signals have been already demonstrated. Typically, positioning is obtained by combining multiple ranging. In this work, it is shown that the performance of a given ultrasonic airborne ranging technique can be thoroughly analyzed using renowned academic acoustic simulation software, originally conceived for the simulation of echographic transducers and systems. Here, in order to show that the acoustic simulation software can be profitably applied to ranging systems in air, an example is provided. Simulations are performed for a typical ultrasonic chirp, from an ultrasound emitter, in a typical office room. The ranging performances are evaluated, including the effects of acoustic diffraction and air frequency dependent absorption, when the signal-to-noise ratio (SNR) decreases from 30 to −20 dB. The ranging error, computed over a point grid in the space, and the ranging cumulative error distribution is shown for different SNR levels. The proposed approach allowed us to estimate a ranging error of about 0.34 mm when the SNR is greater than 0 dB. For SNR levels down to −10 dB, the cumulative error distribution shows an error below 5 mm, while for lower SNR, the error can be unlimited.

scholarly journals A Probabilistic Approach for Optimal Design of Indoor Positioning Systems

2020 ◽  
Author(s):  
Bráulio Henrique O. U. V. Pinto ◽  
Horácio A. B. F. de Oliveira ◽  
Eduardo Souto
Keyword(s):  
Indoor Positioning ◽  
Location Estimation ◽  
Reference Points ◽  
Location Based Services ◽  
Design Parameters ◽  
Area Network ◽  
Localization Error ◽  
Positioning Systems ◽  
Access Points ◽  
The Impact

Indoor Positioning Systems (IPSs) are designed to provide solutions for location-based services. Wireless local area network (WLAN)-based positioning systems are the most widespread around the globe and are commonly found to have a ready-to-use infrastructure composed mostly of access points (APs). They provide useful information on signal strength to be processed by adequate location algorithms, which are not always capable of achieving the desired localization error only by themselves. In this sense, this paper proposes a new method to improve the accuracy of IPSs by optimizing some of their most relevant infrastructure components. Included are the arrangement of APs over the environment, the number of reference points (RPs), and the number of samples per location estimation test. A simulation environment is also proposed, in which the impact of key influencing factors on system accuracy is analyzed. Finally, a case study is simulated to validate an optimal combination of design parameters and its compliance with the requirements of localization error and the limited number of access points. Our simulation results clearly show that the desired localization accuracy, which is set as a goal, can be achieved while maintaining the factors already mentioned at minimal levels, which decreases both system deployment costs and computational effort.

scholarly journals Algorithm for Dynamic Fingerprinting Radio Map Creation Using IMU Measurements

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2283
Author(s):  
Peter Brida ◽  
Juraj Machaj ◽  
Jan Racko ◽  
Ondrej Krejcar
Keyword(s):  
Dead Reckoning ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Reference Points ◽  
Location Based Services ◽  
Position Information ◽  
Vast Number ◽  
Positioning Systems ◽  
Time Required ◽  
Radio Map

While a vast number of location-based services appeared lately, indoor positioning solutions are developed to provide reliable position information in environments where traditionally used satellite-based positioning systems cannot provide access to accurate position estimates. Indoor positioning systems can be based on many technologies; however, radio networks and more precisely Wi-Fi networks seem to attract the attention of a majority of the research teams. The most widely used localization approach used in Wi-Fi-based systems is based on fingerprinting framework. Fingerprinting algorithms, however, require a radio map for position estimation. This paper will describe a solution for dynamic radio map creation, which is aimed to reduce the time required to build a radio map. The proposed solution is using measurements from IMUs (Inertial Measurement Units), which are processed with a particle filter dead reckoning algorithm. Reference points (RPs) generated by the implemented dead reckoning algorithm are then processed by the proposed reference point merging algorithm, in order to optimize the radio map size and merge similar RPs. The proposed solution was tested in a real-world environment and evaluated by the implementation of deterministic fingerprinting positioning algorithms, and the achieved results were compared with results achieved with a static radio map. The achieved results presented in the paper show that positioning algorithms achieved similar accuracy even with a dynamic map with a low density of reference points.

scholarly journals Fingerprinting Indoor Positioning Method Based on Kernel Ridge Regression with Feature Reduction

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yanfen Le ◽  
Shijialuo Jin ◽  
Hena Zhang ◽  
Weibin Shi ◽  
Heng Yao
Keyword(s):  
Ridge Regression ◽  
Local Area Network ◽  
Indoor Positioning ◽  
Location Estimation ◽  
Feature Reduction ◽  
Reference Points ◽  
Area Network ◽  
Positioning Accuracy ◽  
Positioning Systems ◽  
Positioning Method

An important goal of indoor positioning systems is to improve positioning accuracy as well as reduce power consumption. In this paper, we propose an indoor positioning method based on the received signal strength (RSS) fingerprint. The proposed method used a certain criterion to select fixed access points (FPs) in an offline phase instead of an online phase for location estimation. Principal component analysis (PCA) was applied to reduce the features of the RSS measurements but retain the most information possible for establishing the positioning model. Then, a kernel-based ridge regression method was used to obtain the nonlinear relationship between the principal components of the RSS measures and the position of the target. We thoroughly investigated the performance of the proposed method in realistic wireless local area network (WLAN) and wireless sensor network (WSN) indoor environments and made comparisons with recently developed methods. The experimental results indicated that the proposed method was less dependent on the density of the reference points and had higher positioning accuracy than the commonly used positioning methods, and it adapts to different application environments.

scholarly journals Factor Optimization for the Design of Indoor Positioning Systems Using a Probability-Based Algorithm

2021 ◽  
Vol 10 (1) ◽  
pp. 16
Author(s):  
Bráulio Henrique O. U. V. Pinto ◽  
Horácio A. B. F. de Oliveira ◽  
Eduardo J. P. Souto
Keyword(s):  
Wireless Local Area Network ◽  
Local Area Network ◽  
Indoor Positioning ◽  
Test Point ◽  
Reference Points ◽  
Location Based Services ◽  
Area Network ◽  
Positioning Systems ◽  
Positioning Algorithm ◽  
The Impact

Indoor Positioning Systems (IPSs) are designed to provide solutions for location-based services. Wireless local area network (WLAN)-based positioning systems are the most widespread around the globe and are commonly found to have a ready-to-use infrastructure composed mostly of access points (APs). They advertise useful information, such as the received signal strength (RSS), that is processed by adequate location algorithms, which are not always capable of achieving the desired localization error only by themselves. In this sense, this paper proposes a new method to improve the accuracy of IPSs by optimizing the arrangement of APs over the environment using an enhanced probability-based algorithm. From the assumption that a log-distance path loss model can reasonably describe, on average, the distribution of RSS throughout the environment, we build a simulation framework to analyze the impact, on the accuracy, of the main factors that constitute the positioning algorithm, such as the number of reference points (RPs) and the number of samples of RSS collected per test point. To demonstrate the applicability of the proposed solution, a real-world testbed dataset is used for validation. The obtained results for accuracy show that the trends verified via simulation strongly correlate to the verified in the dataset processing when allied with an optimal configuration of APs. This indicates our method is capable of providing an optimal factor combination—through early simulations—for the design of more efficient IPSs that rely on a probability-based positioning algorithm.

scholarly journals High-Precision RTT-Based Indoor Positioning System Using RCDN and RPN

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3701
Author(s):  
Ju-Hyeon Seong ◽  
Soo-Hwan Lee ◽  
Won-Yeol Kim ◽  
Dong-Hoan Seo
Keyword(s):  
High Precision ◽  
Distance Estimation ◽  
Sampling Period ◽  
Multipath Fading ◽  
Indoor Positioning ◽  
Positioning System ◽  
Positioning Systems ◽  
Positioning Errors ◽  
Location Determination ◽  
Indoor Positioning System

Wi-Fi round-trip timing (RTT) was applied to indoor positioning systems based on distance estimation. RTT has a higher reception instability than the received signal strength indicator (RSSI)-based fingerprint in non-line-of-sight (NLOS) environments with many obstacles, resulting in large positioning errors due to multipath fading. To solve these problems, in this paper, we propose high-precision RTT-based indoor positioning system using an RTT compensation distance network (RCDN) and a region proposal network (RPN). The proposed method consists of a CNN-based RCDN for improving the prediction accuracy and learning rate of the received distances and a recurrent neural network-based RPN for real-time positioning, implemented in an end-to-end manner. The proposed RCDN collects and corrects a stable and reliable distance prediction value from each RTT transmitter by applying a scanning step to increase the reception rate of the TOF-based RTT with unstable reception. In addition, the user location is derived using the fingerprint-based location determination method through the RPN in which division processing is applied to the distances of the RTT corrected in the RCDN using the characteristics of the fast-sampling period.

Sign in / Sign up

Export Citation Format

Share Document