نتایج جستجو برای: time difference of arrival tdoa
تعداد نتایج: 21280699 فیلتر نتایج به سال:
This article addresses the underwater acoustical localization problem by using time-difference-of-arrival (TDOA) and bearing-angle-of-arrival (BAOA) measurements. For acoustic equipment, such as ultrashort baseline system (USBL), whose bearing measurements are different from traditional angle-of-arrival (AOA) model, a closed-form solution for hybrid TDOA/BAOA-based source is developed. However,...
Recently, mobile location estimate problem is a significant issue in many industrial fields such as radar, wireless communication, target tracking, and various types of location based services. Time difference of arrival (TDOA) and angle of arrival (AOA) are typical geolocation techniques for estimation of mobile location. In this paper, we suggest a hybrid TDOA/AOA geolocation equation as a si...
In this paper, we investigate the non-line-of-sight (NLOS) propagation identification and correction for time difference of arrival (TDOA) based mobile user location in wireless communication systems. Based on the defined TDOA residual, an NLOS base station identification algorithm is proposed. Different choices of the reference location for the residual calculation are compared via simulation....
In many passive localization applications, the reference waveform of received electromagnetic signals is partly known. The in such scenarios are formulated by modelling relationship between data and known signal parameters interest, as time-difference-of-arrival (TDOA) frequency-difference-of-arrival (FDOA). By exploiting prior information carried signal, negative impact random noise can be sig...
This white paper discusses the most common methods deployed to build up Real Time Location Systems (RTLS). These include Time of Arrival (ToA), Time Difference of Arrival (TDoA), Received Signal Strength (RSS), Time of Flight (ToF), and Round Trip Time (RTT). A special case of RTT, SDS-TWR, is described which offers a solution to the complexity, high power consumption, and high cost of most RTL...
The Complex Ambiguity Function (CAF) used in emitter location measurement is a 2-dimensional complex-valued function of time-difference-of-arrival (TDOA) and frequency-difference-of-arrival (FDOA). In classical TDOA/FDOA systems, pairs of sensors share data (using compression) to compute the CAF, which is then used to estimate the TDOA/FDOA for each pair; the sets of TDOA/FDOA measurements are ...
The estimation of time difference of arrival (TDOA) plays an important role in acoustic source localization, blind source separation, acoustic sound control, and improved speech communication. However, when multiple sources are active in a reverberant environment, the TDOA estimates are known to suffer from the multipath and multiple source ambiguity, and hence are less reliable. In a previous ...
In this paper, we investigate the mobile node localization problem in an underwater positioning system using multiple surface beacons, where time synchronization between beacons and nodes is not required. First, propose a Time-Difference-of-Arrival-based (TDoA-based) method. proposed method, as receives messages from more than or equal to three belonging same grid at one epoch, it calculates lo...
Low-power devices such as cell phones, and wireless routers are commonly used to control Improvised Explosive Devices (IEDs) and as the communication nodes for the sake of command and control. Quickly locating the source of these signals is ambitious, specifically in a metropolitan environment where buildings and towers may cause intervention. This presents a geolocation system that compounds t...
This paper revisits the problem of locating a signal-emitting source from time-difference-of-arrival (TDOA) measurements under non-line-of-sight (NLOS) propagation. Many currently fashionable methods for NLOS mitigation in TDOA-based localization tend to solve their optimization problems by means convex relaxation and, thus, are computationally inefficient. Besides, previous studies show that m...
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