A two phase hybrid algorithm for estimating the location of a mobile node, which has the capability of measuring signal strength, azimuth, and elevation, in a smart space environment over the visible light channel is proposed. In contrast to conventional triangulation approaches which are performed in a simplified plane, the smart room architecture requires a non-planar solution due to the illumination requirement. Furthermore, conventional triangulation approaches can at times produce numerically ill-defined solutions, thereby prohibiting a notion of target location. Instead of solely relying on triangulation, the mobile node estimate their locations through a two phase approach in which they firstly exploit the signal strength observables with unique IDs to establish a coarse estimate, and secondly use the azimuth and elevation observables to establish a fine estimate. In many cases, the fine estimate will improve upon the coarse estimate; however when triangulation fails, the algorithm yield the coarse estimate rather than a localization failure. Since the environment model relies on the primary requirement of adequate illumination, the number of LED anchors and transmit power for communication functions are determined. Simulation results confirm the effectiveness of the hybrid two phase localization approach in a smart space indoor environment by having a median coarse phase accuracy of 34.88 cm and a fine phase median accuracy of 13.95 cm

A two phase hybrid RSS/AoA algorithm for indoor device localization using visible light

Robust received signal strength (RSS)-based cooperative wireless localization using a linear least squares (LLS) method is proposed. We first extend the LLS methods to the cooperative case. To make the proposed algorithm robust, dynamic path loss models are utilized to describe the changing environments; the path loss constants are updated based on the estimated positions of the client nodes. Furthermore, anchor nodes (reference nodes) calibration is considered to deal with the anchor node position errors. The simulation results are given for the proposed methods. Compared with the RSS-based non-cooperative LLS type methods, robust and better performance are obtained.

Received Signal Strength-Based Robust Cooperative Localization With Dynamic Path Loss Model

Collision avoidance and platooning applications require vehicle localization at cm-level accuracy and at least 50 Hz rate for full autonomy. The RADAR/LIDAR and camera based methods currently used for vehicle localization do not satisfy these requirements, necessitating complementary technologies. Visible light positioning (VLP) is a highly suitable complementary technology due to its high accuracy and high rate, exploiting the line-of-sight propagation feature of the visible light communication (VLC) signals from LED head/tail lights. However, existing vehicular VLP algorithms impose restrictive requirements, e.g., use of high-bandwidth circuits, road-side lights and certain VLC modulation strategies, and work for limited relative vehicle orientations, thus, are not feasible for general use. This paper proposes a VLC-based vehicle localization method that eliminates these restrictive requirements by a novel VLC receiver design and associated vehicular VLP algorithm. The VLC receiver, named QRX, is low-cost/size, and enables high-rate VLC and high-accuracy angle-of-arrival (AoA) measurement, simultaneously, via the usage of a quadrant photodiode. The VLP algorithm estimates the positions of two head/tail light VLC transmitters (TX) on a neighbouring vehicle by using AoA measurements from two QRXs for localization. The algorithm is theoretically analyzed by deriving its Cramer-Rao lower bound on positioning accuracy, and simulated localization performance is evaluated under realistic platooning and collision avoidance scenarios. Results demonstrate that the proposed method performs at cm-level accuracy and up to 250 Hz rate within a 10 m range under realistic harsh road and channel conditions, demonstrating its eligibility for collision avoidance and safe platooning.

Visible Light Communication Based Vehicle Localization for Collision Avoidance and Platooning

This paper presents a framework of hybrid models based on multilateral radio localization estimators that use the received signal strength (RSS), the time of arrival (TOA), the time difference of arrival (TDOA) and the angle of arrival (AOA) measurements of signals traveling from a mobile station (MS) to a set of base stations (BSs) in broadband wireless systems. The accuracy of hybrid localization is analyzed based on the Cramer-Rao lower bound, the Taylor-series approximation and the multi-step least square estimator. Explicit formulas that provide the link among RSS, TOA, TDOA or AOA methods is analytically explained. Numerical simulations show that a simple and efficient hybrid estimation scheme combining RSS, TOA, TDOA and AOA data achieves higher positioning precision than that of the RSS-only, the TOA-only, the TDOA-only or AOA-only methods.

A Hybrid Framework for Radio Localization in Broadband Wireless Systems

Recently with the advancement of solid state lighting and the application thereof to Visible Light Communications (VLC), the concept of Visible Light Positioning (VLP) has been targeted as a very attractive indoor positioning system (IPS) due to its ubiquity, directionality, spatial reuse, and relatively high modulation bandwidth. IPSs, in general, have four major components: (1) a modulation, (2) a multiple access scheme, (3) a channel measurement, and (4) a positioning algorithm. A number of VLP approaches have been proposed in the literature and primarily focus on a fixed combination of these elements and moreover evaluate the quality of the contribution often by accuracy or precision alone. In this article, we provide a novel two-phase indoor positioning algorithmic framework that is able to increase robustness when subject to insufficient anchor luminaries and also incorporate any combination of the four major IPS components.

/pdf/two-phase-framework-for-indoor-positioning-systems-using-140sblgo2c.pdf

Two-Phase Framework for Indoor Positioning Systems Using Visible Light.

Localization of passive wireless sensors poses new challenges due to the lack of processing power on sensor devices. In this paper, a derivation of the algorithms and an analysis of their performance are presented for localization in passive Wireless Sensor Networks (WSN). A wide-sense three-step least square (LS) location estimator for the proposed hybrid localization model combining benefits of three widely used methods has been developed. Numerical results demonstrate that the proposed hybrid localization can provide high resolution positioning of passive sensors with centimeter accuracy.

High-resolution hybrid localization in passive wireless sensor nets

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A Hybrid Framework for Radio Localization in Broadband Wireless Systems

High-resolution hybrid localization in passive wireless sensor nets