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High Accuracy Indoor Visible Light Positioning Considering the Shapes of Illuminators
... Visible light communications provide an alternative, which does not penetrate walls, thus ensuring high reusability of the channels ( Figure 3). As the technology itself operates in the free band, which is currently not limited by strict standardization, it is possible to develop practically any custom system; see [41][42][43]. ...
This paper focuses on a channel feed-forward software defined equalization (FSDE) of visible light communication (VLC) multistate quadrature amplitude modulation (M-QAM) based system, implemented in the LabVIEW programming environment. A highly modular platform is introduced; the whole experiment is simulated in software and then thoroughly explored and analyzed during practical measurements in the laboratory, simulating real-world situations. The whole platform is based on modified National Instruments software defined radios (NI SDR) and a commercially available Philips light source, often used in Czech government institutions. Three FSDE algorithms were tested: least mean squares (LMS), normalized least mean squares (NLMS), and QR decomposition based RLS (QR-RLS). Based on measurements, QR-RLS provides the best results, improving measured values by up to 10%. The experiments also show that the simulated results are very similar to real measurements, thus proving the validity of the chosen approach. The whole platform manages to improve measured data simply by making changes to the software side of the testing prototype.
High-accuracy indoor positioning plays an important role in our daily life, due to the growing demand for indoor navigation, emergency rescue, product positioning in industrial environments, and other use cases. With the development of wireless communication technology, there are more options to improve indoor positioning. The time-domain channel impulse response (CIR) which contains the characteristics of multipath is an excellent input choice. In this paper, we focus on combining CIR received from new radio (NR) technology with deep learning methods to solve indoor positioning problems. We analyze some potential aspects to improve previous indoor positioning algorithms and propose new architecture. It should be mentioned that there is no need to identify line-of-sight (LoS) or non-line-of-sight (NLoS) paths when using our method. The simulation is based on a typical indoor factory scenario defined for 3GPP NR positioning enhancements study with low LoS probability. The model based on the proposed network obtains an outstanding performance with the ninety percent positioning error less than 0.5m, which is much better than typical positioning models. In addition, experiments are provided to show the efficiency of different improvement strategies.
Visible light positioning and computer vision-based localization have the potential to be cost-effective technologies for accurate indoor localization. However, the feasibility of existing methods in this domain is limited. In this paper, a novel visible light communication (VLC)-assisted perspective-four-line algorithm (V-P4L) is proposed for practical indoor localization. The basic idea of V-P4L is to jointly use VLC and computer vision techniques to achieve high localization accuracy regardless of LED height differences. In particular, the space-domain information is first exploited to estimate the orientation and coordinate information of a single rectangular LED luminaire in the camera coordinate system based on plane geometry theory and solid geometry theory. Then, by using time-domain information transmitted by VLC and the estimated luminaire information, the proposed V-P4L can estimate the position and pose of the camera using single-view geometry theory and the linear least square (LLS) method. To further mitigate the effect of height differences among LEDs on localization accuracy, a correction algorithm based on the LLS method and a simple optimization method is proposed. Due to the combination of time- and space-domain information, V-P4L can achieve accurate localization using a single luminaire without limitation on the correspondences between the features and their projections in conventional perspective-n-line (PnL) algorithms. Simulation results show that the position error caused by the proposed V-P4L algorithm is always less than 15 cm and the orientation error is always less than 4° using popular indoor luminaires. Experimental results with real hardware show that the average position error is less than 3 cm under both similar and different heights for the LEDs.
An unidirectional Visible Light Communication (VLC) can be used for an Indoor Positioning System (IPS). Mean- while, with our knowledge, most of VLC IPS are based on LED lights on, which cause energy waste when indoor lighting system is not necessary in the daytime. In this paper, we propose an IPS that uses DarkLight Visible Light Communication technique (DL-VLC). This proposal can guarantee the IPS function even when LED to be ”OFF” and makes more economic energy. With our simulation results, the average of positioning error is 5 cm by considering the shot noise and thermal noise and the LED power of DarkVLC is 1.4 mW which is lower than that of LED in normal mode (19.8 W).
Modern hospitals are beginning to adopt E-HEALTH as efficient complements to the traditional healthcare services. To support the E-HEALTH services, a locatable, radiation-free and high-capacity communication system is urgently needed in hospitals. Power line communication (PLC) systems can use the ubiquitous power line network to power the light-emitting diode (LED) lamps while serving as the backbone network for the indoor visible light communication (VLC) systems naturally. In this article, a hybrid broadband power line and visible light communication system with orthogonal frequency division multiplexing modulation is proposed for the indoor hospital applications, which gives a brand-new solution to replace the conventional wireless communication systems in hospitals. A general-purpose system model is provided and some basic techniques to enhance system performance are also investigated. Moreover, a feasible demonstration which supports over 48 Mbps data rate within a bandwidth of 8 MHz is implemented in the laboratory.
Broadcasting signals have been recognized as promising candidates for navigation and positioning needs. However, in most single frequency broadcasting networks, the transmitter confusion problem poses a huge obstacle. Not holding the transmitter identities, the receiver cannot determine the distance to the transmitters, let alone its own position. What's worse, considering the existence of multipath propagation, the receiver is unable to distinguish line of sight (LOS) components from non line of sight components, which makes positioning even harder. In this paper, a two-step method is proposed to solve the positioning problem in single frequency networks (SFNs) under multipath propagation yet with direct path. First, a probability approach is proposed to identify all LOS components iteratively. Then, it is proved in this paper that a receiver can determine its position when receiving LOS signals from at least five transmitters without the knowledge of transmitter identities. Detailed analysis is carried out in this paper to derive error bounds and performance limits from different perspectives. Simulation results show that the proposed algorithm can achieve high accuracy of positioning across multiple environments. Besides, the proposed methodology is general, which can be used in any SFN or other wireless networks for positioning needs. IEEE
Considering the complex propagation of RSSI signal along with perturbations, the accuracy of RSSI based indoor location cannot be guaranteed and it cannot achieve accurate positioning. To address this issue, this study proposes a filtering algorithm to process the RSSI signal. In particular, the CC2540 chip of TI company is used as the transmitter station. Then, a platform is constructed using the BLE low-power dissipation based Bluetooth technology. Subsequently, the RSSI signal can be collected under different environment and different locations from the station. Thereby, the formula of distance measuring can be obtained based on the parameters determined using the linear regression. Consequently, the RSSI signal is processed using the Gauss-Kalman filtering algorithm. Simulation results show that the performance of the proposed filtering algorithm is improved with respect to the perturbation rejection and accuracy as well as stability.
In this study, theoretical limits are obtained for the accuracy of range (distance) estimation in visible light positioning (VLP) systems. In particular, the Ziv-Zakai bound (ZZB) and the weighted Cramér-Rao bound (WCRB) are derived for range estimation based on received signal strength (RSS) measurements. Also, the maximum a posteriori probability (MAP) and the minimum mean-squared error (MMSE) estimators are obtained for RSS based range estimation, and compared against the theoretical limits.
This letter addresses the problem of localization in a quasi-synchronous network using time-of-arrival (TOA) measurements. The object to be localized is passive, i.e., it is neither a transmitter nor a receiver. Unlike prior TOA-based algorithms, no perfect synchronization between the transceivers is assumed here. A two-step linear algorithm is proposed to jointly estimate the location of the passive object and the unknown time offset between the transceivers. The Bayesian Cramer-Rao lower bound (BCRB) for quasi-synchronous networks is then given for comparison. It is shown that the proposed algorithm can achieve the BCRB and significantly outperform the algorithms using time-difference-of-arrival (TDOA) and differential TOA (DTOA) measurements.
A hybrid time-difference-of-arrival/angle-of-arrival (TDOA/AOA) positioning technique for indoor ultra wideband (UWB) systems is presented in this paper. The non line-of-sight (NLOS) propagation error is considered one of the major error sources in location systems; therefore, NLOS identification and mitigation technique with Kalman filters are utilized to reduce the NLOS time-of-arrival (TOA) errors in indoor UWB environments. To deal with the effects of inaccurate NLOS AOA data, an AOA selection process is included. An adjustable extended Kalman filter (EKF) structure is used to process the formulated TDOA and selected AOA measurements for mobile positioning and tracking. The simulation results show that the proposed hybrid scheme can effectively respond to the NLOS/LOS changes in the UWB environment, and improve the position accuracy
An RF-based indoor precise positioning system being developed for fire fighters is discussed in this paper. The paper will discuss system level overview of the RF prototype and will discuss the NLOS field tests and indoor positioning results using this RF prototype. The position estimation algorithm used is based on Time Difference of Arrival (TDOA) for a multicarrier signal. An error budget for such an RF-based indoor positioning system is presented in this paper with more insight to the sources of errors. Multipath and NLOS conditions indoors are well known error sources but there also exists another not so well known but major sources of error which are due to dielectric properties of the building materials. Basic simulations are presented to better understand the effect of the dielectric properties of building materials on indoor position estimates.
Hybrid T-DOA/AOA Indoor Positioning and Tracking Using Extended Kalman Filters
- Yi-Jing Chin-Der Wann
- Chih-Sheng Yeh
- Hsueh
Impact and feasibility of darklight LED on indoor visible light positioning system
- huang