{"id":1676,"date":"2021-07-19T09:24:35","date_gmt":"2021-07-19T09:24:35","guid":{"rendered":"https:\/\/www.kios.ucy.ac.cy\/evai\/?p=1676"},"modified":"2022-11-17T13:50:01","modified_gmt":"2022-11-17T13:50:01","slug":"real-time-relative-positioning-system-implementation-employing-signals-of-opportunity-inertial-and-optical-flow-modalities","status":"publish","type":"post","link":"https:\/\/www.kios.ucy.ac.cy\/evai\/publications\/real-time-relative-positioning-system-implementation-employing-signals-of-opportunity-inertial-and-optical-flow-modalities\/","title":{"rendered":"Real-Time Relative Positioning System Implementation Employing Signals of Opportunity, Inertial, and Optical Flow Modalities"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"1676\" class=\"elementor elementor-1676\" data-elementor-settings=\"{&quot;ha_cmc_init_switcher&quot;:&quot;no&quot;}\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-9ad9da3 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"9ad9da3\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;_ha_eqh_enable&quot;:false}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-ca728b9\" data-id=\"ca728b9\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1594d08 elementor-widget elementor-widget-heading\" data-id=\"1594d08\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">Real-Time Relative Positioning System Implementation Employing Signals of Opportunity, Inertial, and Optical Flow Modalities\n<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-f1ff36b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f1ff36b\" data-element_type=\"section\" data-settings=\"{&quot;_ha_eqh_enable&quot;:false}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-78771b0\" data-id=\"78771b0\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5e8e993 elementor-widget elementor-widget-heading\" data-id=\"5e8e993\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<span class=\"elementor-heading-title elementor-size-default\">Abstract<\/span>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5072ea2 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"5072ea2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Current navigation technologies are relying on global navigation satellite system (GNSS) information. As in terms of reliability and precision next-generation autonomous vehicle requirements cannot be fully satisfied by GNSS, a sensor information fusion must be employed, leading to the exploration of new positioning methods. In this work, a reliable relative positioning solution in GNSS-challenged areas is investigated, using a combination of signals of opportunity (SOPs), inertial, and optical flow data. The proposed real-time relative positioning system exploits the fused data in the absence of GNSS signals for localization, employing a tracking algorithm to estimate the agent\u2019s trajectory in space and time. Extensive outdoor experiments employing an Unmanned Aerial Vehicle (UAV) are carried out to demonstrate the applicability of the proposed technique, validating its performance against various positioning approaches, including GNSS.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-609ae55 elementor-widget elementor-widget-heading\" data-id=\"609ae55\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<span class=\"elementor-heading-title elementor-size-default\">Introduction<\/span>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-dcb3fe8 elementor-widget elementor-widget-text-editor\" data-id=\"dcb3fe8\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Vehicular technology is developing rapidly in order to achieve higher levels of automation. A navigation system that is reliable and accurate is an absolute need for the implementation of autonomous vehicle technology and the development of intelligent transportation infrastructure. GNSS positioning, even though the main localization technology utilized nowadays, can in some instances suffer from interference, jamming, or spoofing attacks, or it can even become unavailable at certain locations. Various localization solutions, such as the utilization of inertial navigation systems (INS), and various sensors (e.g., light, and range sensors) have been proposed to localize a vehicle in GNSS-challenged areas. A number of issues with the aforementioned solutions, such as degradation of data and signal loss due to multipath and antenna obstruction, have resulted in the further exploration of alternative localization methods. An indicative taxonomy of such techniques, including the proposed system (optical flow-relative positioning system \u2013 OF-RPS), is presented in the figure below.<\/p><p>Apart from the aforementioned localization techniques, SOPs (e.g., AM\/FM radio, cellular, TV signals, etc.) can also be utilized for location estimation, since they are freely available and are usually transmitted at high powers. A number of works in the literature have investigated SOPs for positioning purposes, mainly assuming that a priori knowledge of the receiver\u2019s reference position and the transmitter\u2019s location is available.<\/p><div class=\"wp-block-image\"><figure class=\"aligncenter\"><img decoding=\"async\" src=\"https:\/\/ieeexplore.ieee.org\/mediastore_new\/IEEE\/content\/media\/9476247\/9476672\/9476841\/9476841-fig-1-source-small.gif\" alt=\"Fig. 1: - Broad classification of positioning techniques.\" \/><figcaption><strong>Broad classification of positioning techniques.<\/strong><\/figcaption><\/figure><\/div><p>\u00a0<\/p><p>This work complements these studies, extending our previous work, as it introduces a real-time relative positioning system, utilizing fused information without the use of any GNSS information. Specifically, the main contributions include:<\/p><ul><li>A novel real-time relative positioning system (denoted as OF-RPS) that localizes the agent by fusing SOP information with inertial and optical flow measurements, requiring no information about the transmitters\u2019 location or any GNSS signal information. An extended Kalman filter (EKF) solution is utilized to improve the localization performance and a frequency selection algorithm (FSA) is employed to reduce the processing time requirements.<\/li><li>A prototype implementation of the proposed solution, including extensive testing in a real-world outdoor environment to demonstrate the feasibility of the developed framework. Experimental results assess and validate its performance thoroughly, and indeed show that relative positioning can be achieved using only the fused information and without the use of any GNSS data.<\/li><\/ul><p>The structure of this paper is as follows. Related work is included in\u00a0<a>Section II<\/a>, and the description of the methodology employed is described in\u00a0<a>Section III<\/a>.\u00a0<a>Section IV<\/a>\u00a0elaborates on the system\u2019s framework, while experimental results are illustrated in\u00a0<a>Section V<\/a>. Finally, concluding remarks are presented in\u00a0<a>Section VI<\/a>.<\/p><p><strong><a href=\"https:\/\/ieeexplore.ieee.org\/document\/9476841\" target=\"_blank\" rel=\"noreferrer noopener\">IEEE Publication<\/a><\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Real-Time Relative Positioning System Implementation Employing Signals of Opportunity, Inertial, and Optical Flow Modalities Abstract Current navigation technologies are relying on global navigation satellite system (GNSS) information. As in terms of reliability and precision next-generation autonomous vehicle requirements cannot be fully satisfied by GNSS, a sensor information fusion must be employed, leading to the exploration 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