• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    Interior system of location in metallic environments based on a positioning system for environments where the reception of GNSS signals is not possible or the coverage of it is not enough, and composed of a beacon network (beacons, located and oriented), at least one receiving equipment, and an inter-beacon communication system, for the self-configuration of the system, in order to determine the position of each of the beacons that make up the beacon network, by using frequency magnetic fields Extremely low (ELF), and a multiple frequency access control method by frequency division (FDMA). (Machine-translation by Google Translate, not legally binding)
    公开号:ES2674123A1
    申请号:ES201631687
    申请日:2016-12-27
    公开日:2018-06-27
    发明作者:Antonio Leopoldo RODRIGUEZ VAZQUEZ；Aintzane LUJAMBIO GENUA；Luis Miguel PARRILLA CASQUET；Joaquin BERNAL MENDEZ；Manuel FREIRE ROSALES；Maria Angeles MARTIN PRATS；Pilar RODRIGUEZ LOPEZ
    申请人:Skylife Eng S L；Skylife Engineering Sl；
    IPC主号:
    专利说明:

    Interior Location System in Metal Environments 5 OBJECT OF THE INVENTION
    The present invention relates to a high performance interior positioning system that works in metallic environments, where it is not possible to receive GNSS signals or they are very attenuated. The system is designed for use in harsh environments
    10 (metal structures) where other types of systems cannot perform their functions due to various physical limitations. It is a non-invasive system, so it is not necessary to modify the environment in which it develops its activity and, in addition to being able to self-position, it can guide the user to a specific location.
    The present invention falls within the field of telecommunications technology with a special application to the aeronautical, naval, railway and aerospace industry specifically within the production and maintenance and troubleshooting operations phases. 20 BACKGROUND OF THE STATE OF THE TECHNIQUE
    There are a large number of positioning systems designed so that they depend on the signal emitted by the satellites of the Global Navigation Satellite System (GNSS). Because GNSS signals require line of sight this works well in open environments, but 25 not in closed environments such as the interior of buildings, hangars or caves. There are some systems designed to complement or replace GNSS information at a time when the signal is degraded (the patents described below will be described below). For example, the patent described in (1) proposes the use of a broad spectrum RF system that transmits in the LORAN-C frequency: 80-120 KHz. This system, however, does not
    30 is intended as an independent GNSS system.
    The triangulation-based methods with RF signals (WIFI, GSM, IMES, Bluetooth) suffer a significant degradation of precision due to the effect of reflections and signal attenuation due to the surrounding materials. This is especially limiting when such an environment counts.
    35 with an abundance of metal surfaces, such as an aircraft assembly line.

    Unlike what happens with the electric field and with the electromagnetic signals of high frequencies, the magnetic field of OC or of low frequency is little sensitive in the presence of most of the materials (except ferromagnetic). It is therefore an ideal candidate to be used in interior locations. There are some positioning solutions that make use of the Earth's own magnetic field [2] [3]. However, most of the solutions proposed in the literature make use of the field generated by an independent issuer.
    Techniques that use OC magnetic fields have the disadvantage of avoiding the error introduced by the Earth's own magnetic field. To solve this problem in [4] the use of quasi-DC fields has been proposed. This method is focused on the location of instruments in surgical operations and uses magnetic field pulses generated by a square signal whose period is above 10ms. The use of OC magnetic fields is also proposed in [5, 6). This technique uses several beacons powered by OC currents whose polarity is periodically modified to locate the 3D position of a sensor. This same idea is proposed in [7, 8], with the difference that instead of changing the polarity periodically, in this case they change it according to pseudorandom codes, a different one for each beacon installed in the coverage area. The Ascension TrackSTAR system [9] also uses OC magnetic fields in this case pressed.
    Other ox: Proposed ions use very low frequency magnetic fields, such as the one described in [10] which uses a mobile transmitter of 387 kHz frequency that is monitored by several receivers in the coverage area. AC magnetic fields are also the basis of the operation of two commercial products, Liberty de Polhemus [11] for medical applications and UGPS24 of Infrasurvey [12] for positioning in mines, caves or chasms, ultimately underground. Also within the scope of low frequency magnetic fields, [13] describes a technique to locate an object that emits a rotating magnetic field. This technique, although it is suitable for indoor environments, requires several receivers, and like the rest of the mentioned techniques that use AC magnetic fields, it focuses more on the location of an object than on providing a method to a mobile device to determine Your own position. A technique used to achieve this objective is the provision of a beacon system, usually turns or windings, which emit a magnetic field that can be detected and processed by the mobile [14] (15). For example, in [14] a technique is proposed in which the signals of the different beacons are distinguished by the modulation of a 13.36 MHz signal. However, at that frequency the interaction of magnetic fields with metallic materials is not in
    absolute negligible, so in the description of the method it is recommended to keep the beacons and sensors away from metal surfaces. The method described in [15] proposes to distinguish the beacon signals by a modulation index or by emission frequency, for which it proposes frequencies between 20kHz and 100kHz. The magnetic field of this frequency easily penetrates non-metallic materials, so the method is useful for the interior of offices and, in general, buildings, but it is not feasible to use it in the presence of large metal surfaces.
    References: [1). .Robust Low-Frequency spread-spectrum navigation system. ("Navigation system
    robust in amptio low frequency spectrum "). US201 01 03989 (A 1).
    [2]. Andrei Papliatseyeu, Niko Kotilainen, Oscar Mayora, and Venet Osmani. FINDR: Low-Cost Indoor Positioning Using FM Radio. ("Low cost positioning technique using FM radio signals"). In Jean-Marie Bonnin, Carla Giannelli, and Thomas Magedanz, editors, MobileWireless Middleware, Operating Systems, and Applications, volume 7 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, pages 15--26. Springer Berlin Heidelberg, Berlin,
    Heidelberg, 2009. ISBN 978-3-642-01801 -5. doi: 10.1007 / 978-3-642-01802-2.
    [3). Applying indoor magnetic fields for acquiring movement information, ("Application of magnetic fields in closed environments for movement data acquisition").
    US2015141050 (A1).
    [4]. Position tracking using quasi-DC magnetic fields, ("Position tracking using
    quasi-DC magnetic fields "), US2006293593 (A1).
    [5]. Jbrg Blankenbach and Abdelmoumen Norrdine. Position estimation using artificial generated magnetic fields. ("Position estimation using artificially generated magnetic fields"). In 2010 International Conference on Indoor Positioning and Indoor
    Navigation, IPIN 2010 -Conference Proceedings, 2010. ISBN 9781424458646. doi: 1 0.1109 / IPIN.201 0.5646739. [6]. Joerg Blankenbach, Abdelmoumen Norrdine, and Hendrik Hellmers. A robust and precise 3D
    indoor positioning system for harsh environments. ("Robust and precise system for positioning in closed environments for complex environments"). In 2012 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2012 -Conference Proceedings, number November, 2012. ISBN 9781467319546. doi:
    10.1109 / IPIN.2012.6418863.
    [7]. Eric A. Prigge and Jonathan P. How. Signal architecture for a distributed magnetic local positioning system. ("Signal architecture for a distributed local positioning system"). IEEE Sensors Journal, 4 (6): 864-873, 2004. ISSN 1530437X. doi: 10.1109 / JSEN. 2004.833512.
    5 [8]. Eric A. Prigge A positioning system with no line-of-sight restrictions for cluttered environments. ("Positioning system that does not require line of sight for complex environments"). PhD thesis, 2005.
    [9]. Ascension Technology Corporation. STAR Track lNVIfIN.ascension-tech.com, September 2016.
    10 [10). Darmindra D. Arumugam, Joshua D. Griffin, and Daniel D. Stanci !. Experimental demonstration of complex image theory and application to position measurement. ("Experimental demonstration of complex image theory and its application to positioning"). IEEE Antennas and Wireless Propagation Le "ers, 10: 282-285, 2011. ISSN 15361225. doi: 10.11 09 / LAWP.2011.2136370.
    15 (11). Polhemus Liberty 'N oVW.polhemus.com, December 2016. (12). InfrasulVey. UGPS IN Nw.infrasurvey.ch/en, December 2016. (13). Magneto-Inductive positioning using a rotating magnetic field, ("Positioning
    magneto-inductive by means of a rotating magnetic field "), US2013226512 (A1). (14). Indoor location using magnetic fields, (US2015204649 (A1). (15). System and Method for determining position, ("System and method for determining position"). US8855671 (81).
    The positioning system proposed with the present invention mainly has a series of advantages over the previously known:
    one) A direct line of sight between sender and receiver is not required.
    2) Use in adverse environments (metal structures).
    3) Its installation does not require a modification of theenvironment in which the
    30 application.
    4) Plug & Play
    5) Ability to operate with several devices in the coverage area.

    EXPLANATION OF THE INVENTION
    The patent presented is based on a positioning system intended for environments where the reception of GNSS signals is not possible or the coverage of it is not sufficient. The positioning system consists of a beacon network and one or several receivers. It is based on the use of extremely low frequency (ELF) magnetic fields, that is, below 300Hz. The low frequency magnetic field is very little altered by the presence of materials usually present in indoor locations such as buildings, structures. underground, industrial buildings. In particular, unlike the electric field or high frequency electromagnetic signals, the sufficiently low frequency magnetic field is little disturbed by the presence of eddy currents that are induced in conductors, since this effect is pro¡: Klrcional at the frequency This feature makes the use of low frequency magnetic fields particularly suitable for localization in environments where the presence of metal materials such as interiors of trains, aircraft or their manufacturing and assembly lines is abundant. The use of ELF enables the system to be used without a direct line of sight between the beacon network and the receiver. The coverage area will depend on the deployment of the beacon structure, and it is possible to cover a large area.
    The beacon network consists of a series of beacons emitting magnetic field, located and oriented to cover the entire area where you want to develop the application. The implemented protocol uses a method of multiple frequency access control to the medium by frequency division (FOMA), allowing several transmitters to be integrated simultaneously. This method a¡: Klrta robustness against asynchronous transmitters, the main disadvantage of systems that use code division multiple access (COMA) as a medium access technique. The coding methodology developed, makes possible the univocal identification of each of the beacon elements by the receiver, which can discriminate a minimum of 2.3 Hz spaced carriers. Additionally, it integrates an inter-beacon communication system, capable of performing a self-configuration of the system, being determined the position of each of the beacons that make up the beacon network.
    The equipment: The receiver is a mobile device capable of calculating its own position through the reception and processing of signals from the beacon network. The implemented location algorithm, based on the multidimensional Newton-Raphson method, allows the position and attitude to be estimated from the data coming from the triaxial magnetic field sensors. To increase the accuracy of the self-positioning task is implemented
    a data fusion algorithm based on a Kalman Extended Filter (EKF) adapted to the
    inertial sensors and system dynamics.
    5 DESCRIPTION OF THE FIGURES
    Figure 1 shows the main elements that make up the location system.
    Figure 2 shows a scheme of the beacons.
    tO Figure 3 shows a scheme of the receiving equipment.
    The elements referenced in the figures represent:
    t 5 1. Surface of the metal shielding structure.
    2. Beacon.
    3. Receiving equipment
    Four. Inter-beacon link.
    5. ELF coverage signal.
    20 6. Transmitter equipment communications module.
    A. Inter-beacon communications module
    B. RF antenna for communications module of transmitter equipment.
    7. Transmitter equipment processing module.
    8. ELF transmitter module.
    25 9. Antenna Transmission of ELF signals.
    10. Digital communications module in Transmitter.
    eleven. Sensing stage.
    12. Inertial sensors.
    13. Receiver equipment processing module. 30 14. Communications module on receiving equipment.
    A. Communications module between receiver and transmitter equipment.
    B. RF antenna for communications module of the receiving equipment.
    15. Power unit of the receiving equipment.
    16. Display 35 17. Transmission pulse shaper block.
    18. Modulator block that uses a different frequency for each channel.
    19. Signal demodulator block
    twenty. Channel coefficient estimation
    twenty-one. Carrier Mixer
    5 22. Low Pass Filter: LPF: Low Pass Filter.
    2. 3. Adapted filter
    24. Value of the measured magnetic field.
    25. Estimation of the radii of the field spheres.
    26. Block of ¡: K) positioning with estimated initial position with spherical ampos. 10 27. Unit of Calculation of the vector of functions and the Jacobian matrix.
    28. Unit of Solution of the system of equations and position advance.
    29. Iteration process to minimize error.
    30 Initial Position after completing block 26.
    31. Positioning calculation block with real field expressions.
    15 32. Estimated final position of the positioning algorithm You will complete blocks 26 and 31.
    33. Position of the beacons given by 6.
    3. 4. Estimation of the theoretical expressions of cam¡: K) magnetic in the estimated final position (32).
    20 35. Conformation of the correlation matrix based on the cam measurements: K) in the receiving equipment and theoretical field values.
    36. Analysis of singular values (SVD).
    37. Rotation matrix estimation.
    38. Estimated orientation of the sensor.
    25 Figure 4. represents a scheme of signal generation and modulation of the transmitter system.
    Figure 5. The AWGN channel model is shown.
    30 Figure 6. Diagram of Demodulation and estimation in the equi¡: K) receiver.
    Figure 7. Simplified block diagram of the algorithm implemented to estimate the position of the sensor.
    Figure 8. Block diagram of the algorithm implemented to estimate the orientation of the
    sensor.
    EXAMPLE OF PREFERRED EMBODIMENT
    A. Indoor positioning in a metallic environment.
    The technologies based on GNSS or RF used as a solution when it comes to facilitating positioning and location tracking present indoor difficulties under the strong
    The presence of metallic structures or surfaces, since they show a great attenuation due to eddy currents induced in the conductors. In this case, the most unfavorable for the mentioned methods, since the attenuation increases with frequency is the object of study of the present invention. Other factors that can reduce the performance of positioning solutions are:
    • Location signals suffer great attenuation and dispersion.
    • Multitude of reflections in the environment, multi-path effect that deteriorate the performance and performance of the system.
    • Transmitter and receiver do not have direct visibility (NoLoS, Non Line-of-Sight).
    20 • The environment is highly variable due to the presence of people and ferromagnetic materials.
    • The space is smaller than for other outdoor navigation applications and therefore the accuracy must be greater.
    25 As described in Figure 1, the location system consists of a beacon network formed by at least 3 beacons (2), to achieve 2D positioning or 4 beacons (2) for 3D positioning and one or more equipment receivers (3).
    The beacons form a network of transmitters whose position is known and shared through the
    30 implementation of an inter-beacon communication system that allows establishing the relative position of each of them, subsequently transmitting said information to the receiving system in a first configuration phase.
    The installation of the beacons (2) can be carried out both inside and outside the metal shielding surface (1), on which the receiving equipment (3) is located.
    The beacons described in Figure 2, are responsible for transmitting the coverage signal to the
    Receiving modules, as well as estimating their relative position within the system. The signals transmitted by the beacons will employ extremely low frequency magnetic fields, which are capable of avoiding attenuation caused by the presence of conductive surfaces.
    Each transmitter or beacon element consists of the following elements:
    • An inter-beacon communications module (6.A) where the communications architecture necessary for the inter-beacon information transmission is implemented and with the receiver in the initial configuration or calibration phase. It has an RF antenna (6.B) adapted to the communication needs between the beacons.
    • A processing module (7) responsible for generating the ELF signal (5) at the frequency
    desired for later transmission by the transmitting antenna (9). This module is also responsible for estimating the position of the beacon based on the data collected ¡: Klr the communications module (6.A) that provide information on the ¡: Klsition relative to the rest of the beacons (2) of the system.
    • An ELF Transmission Module (8): Power stage that amplifies the ELF signal to adapt the voltage level based on the current values required for the transmission. The frequency range of the cam¡: Kl magnetic ELF is generated between 10Hz and 100Hz.
    • Antenna Transmission of ELF signals (9): It is based on a spiral-type conductor with high directionality to facilitate goniometry and radiolocation tasks. The signal it transmits comes from the transmitter module (8), after conditioning. Digital communications module (10). Module focused on communicating the beacon or transmitter element (2) with a digital communications interface. Allows to download to the processing module (7) configurable patterns from an external computer
    As a medium access technique, FDMA (Multiple Frequency Multiplexing Access) is used and a frequency band of the available spectrum is assigned to each beacon so that the radiated signals do not overlap each other. The channel bandwidth is 2.3 Hz, starting from baseband up to 102.35 Hz. Reuse techniques of frequencies or channels per coverage area will also be used.
    Figure 4 shows the FDMA modulator scheme with the basic pulse conformation of
    transmission g (t) in the pulse shaping block (17), which is a raised cosine pulse.
    Each of these waveforms is modulated with a different carrier frequency in the module
    or modulator block (18), to then be transmitted independently to the channel through the ELF signal transmission antenna (9).
    The communications channel will add all these signals, each attenuated by a different coefficient depending on the distance it is. It has been considered as an instant channel and due to the characteristics of the ELF coverage signal (5) there are no multi-path effects or 10 fading. The noise will be modeled as a white Gaussian AWGN additive process. The
    ,
    Channel coefficients are: mean O and variance (Tw. Figure 5 illustrates the channel model.
    The receiving equipment described in Figure 6 will be responsible for performing the position estimation. From the signals received by the sensing stage (11), composed of receivers of
    15 triaxial magnetic field, the equipment is able to uniquely identify the origin of these signals. From the received magnetic field value, it performs a triangulation, with which it is possible to make a first estimate of the position. It is necessary that the receiving team has a coverage of at least 3 beacons.
    20 The receiving equipment (Figure 3) is composed of the following modules:
    • Sensing stage (11): Triaxial magnetic camlXl receivers (magneto-resistive and / or inductive) that allow to measure the module and the direction of the ELF magnetic field from the different beacons. It includes a stage of adaptation of the signal of the
    25 sensor consisting of amplification and noise elimination.
    • Inertial sensors (12): Accelerometers and gyroscopes. Through the data fusion algorithm they provide precision in the task of self-positioning of the receiver equilXl.
    • Processing module in receiving equipment (13): Responsible for processing the data
    coming from the magnetic and inertial sensors through the implementation of the 30 algorithms of location and fusion of data.
    • Communications module in receiving equipment (14.A): Module that allows sending orders to the beacons for the configuration of different functionalities such as self-calibration and hibernation. DislXlne of an RF antenna (14.8) adapted to the communication needs between the beacons and the receiving equipment.
    • Display (16): Touch screen where the result of the positioning represented on maps or plans of the work environment is displayed.
    The processing module in receiving equipment (13) processes the data of the inertial sensors (12) that provide complementary information when making the final estimate of the relative position of the receiver with respect to the beacon network. The information obtained will be represented on the display (16) of the receiving equipment through a user interface designed for the positioning system. The receiver processing module (13) implements a receiver: ion method, illustrated in Figure 6, whose function is to recover the signals corresponding to each transmitting node, that is, demodulate the N signals found combined in the received waveform x (t). This method consists of a system of multiple access to the medium by frequency division (FDMA) of N branches, which will multiply the signal received by each of the subcarriers, with the aim of lowering them to baseband. Next, a low pass filter eliminates the high frequency spurious harmonics that have been generated with multiplication. Subsequently, a convolution (filtering) is carried out to pass through the filter adapted to the basic pulse g (t), obtaining at its output a waveform whose maximum coincides with the channel coefficient of that transmitter (estimated). Thus, if the pulses are normalized, the estimate of .3; (t) is to calculate the maximum of the received pulse. A complete outline of the reception method is shown in Figure 6, including channel estimation. The architecture of the receiver system is composed of a signal demodulator block (19), in turn composed of N branches of an FDMA demodulator, where the received signal is multiplied by each of the subcarriers in the carrier mixer (21) with in order to lower the frequency to baseband. It is subsequently passed through a low pass filter (LPF: Low Pass Filter) (22) that eliminates high frequency spurious. The output is then sent to an adapted filter (23) to obtain a waveform whose maximum coincides with the channel coefficient of the transmitter. Thus, if the pulses are normalized, the estimation of channel coefficients (20) consists in calculating the maximum of the received pulse, giving rise to the measured magnetic field value (24).
    The location of the sensor will be determined in two steps. First, the sensor will be positioned within the space using a multi-variable optimization algorithm represented in Figure 7. Next, its orientation will be estimated by solving a least squares problem, see Figure 8.

    Figure 7 shows a block diagram of the algorithm implementation for the estimation of the sensor position. The determination of the position of the receiving equipment (3) will be done in two stages: positioning block with estimated initial position with spherical amps
    (26) and positioning calculation block with real field expressions (31). It is based on the value of the measured magnetic fields (24) and the radii of the field spheres in the block (25) are estimated. Subsequently, together with the position of the beacons (33) the process of calculating the estimated initial position with spherical fields (26) begins, which is subdivided into the calculation of the vector of functions of the Jacobian matrix (27) and the solution of the system of equations and position advance (28). The processes carried out by the unit of calculation of the Jacobian matrix and function vector (26) and the solution unit of the system of equations and position advance (27) are iterated through the iteration process to minimize the error (29) in the initial position (30). The positioning calculation block with real field expressions
    (31) Estimate the precise position based on the position of the beacons (33) and the initial position (30). The processes carried out by the unit of calculation of the function vector and Jacobian matrix (26) And by the solution unit of the system of equations and position advancement (27) are also used for the calculation of the precise positioning solution in the position calculation block with real field expressions (31). These processes are performed iteratively to minimize the error (29) in the estimated final position (32).
    Once the position of the sensor within the coordinate system is found, it is possible to evaluate the theoretical field expressions at that point to have an estimate of their value in the reference system of the beacons and thus determine the orientation of the sensor. Figure 8 shows a simplified block diagram of the operation of the sensor orientation estimation algorithm.
    First, the theoretical expressions of the magnetic field (34) in the final position provided by the positioning algorithm (32) with respect to the position of the beacons (33) are estimated. This result, together with the amplitude of the magnetic field measured by the sensors (24), serve as input to a minimum square resolution process, whose output will be the estimated orientation of the sensor (38). This process is mainly based on the conformation of the correlation matrix (35) of the input values, the analysis of singular values (SVD) (36) and the estimation of the rotation matrix (36) that relates the density vectors of magnetic field in the reference system of the sensor and of the beacons.
    B. Indoor positioning outside metal environment.
    The current example is a particular case of the preferred embodiment example A (Indoor positioning in a metal environment) - and consists of positioning in indoor environments where there are no large metal surfaces or structures where the
    5 user The current example B differs from A, in that the operating environment is different. In B, a metal shielding structure or envelope is not present, the characteristics of the system remaining unchanged. In this way, the indoor positioning system presented in this invention is executed with and without the presence of a metal envelope.
    权利要求:
    Claims (1)
    [1]
    1.-Internal location system in metallic environments through the use of extremely low frequency magnetic fields, characterized by being the following 5 elements:
    A. A network of beacons, conveniently located and oriented, in which each beacon consists of:
    10 • An inter-beacon communications module where the communications architecture is implemented for the transmission of interbalized information and with the receiver in the initial configuration or calibration phase; This communication is carried out on an RF channel and for which it also incorporates an RF antenna.
    15 • A processing module responsible for generating the ELF signal for subsequent transmission by the transmitting antenna, as well as estimating the position of the beacon based on the data collected by the communications module that provide information on the relative position of the rest of the system beacons.
    20 • An ELF transmission module where the ELF signal is amplified to adapt it to the voltage levels of the signal to be transmitted in a magnetic field range between 10Hz and 100Hz.
    • Transmission antenna of ELF signals from the transmitter module after
    its conditioning, consisting of a spiral-type conductor with a high directionality to facilitate the tasks of goniometry and radiolocation.
    • Digital communications module in order to be able to communicate the beacon with a digital communications interface, allowing configurable patterns to be downloaded to the processing module from an external computer.
    30 B. At least one mobile receiving device where the demodulation of ELF signals, position estimation, data fusion with inertial systems and their representation is carried out, consisting of the following modules or elements:
    35 • Triaxial magnetic field receivers (magneto-resistive and / or inductive) as a sensing stage, which allow to measure the module and the direction of the ELF magnetic field from the different beacons and includes a signal adaptation stage of the sensor consisting of amplification and noise elimination.
    • Inertial sensors consisting of accelerometers and gyroscopes, in order to
    5 ensure the corresponding accuracy in the self-positioning taskof the receiving equipment, using the data fusion algorithm.
    • Processing module in receiving equipment, in order to process the data coming from the magnetic and inertial sensors making use of the corresponding algorithms of location and fusion of data.
    10 • Communications module in receiving equipment, in order to be able to send the corresponding orders to the beacons for the configuration of different functionalities such as self-calibration and hibernation, it also makes it possible to download configurable patterns from an external computer into the processing module .
    15 • A touch screen or display showing the result of the positioning represented on maps or plans of the work environment.
    C. An inter-beacon communication system, for the self-configuration of the system.
    20 2. Procedure for using the "Internal location system in metallic environments" described in claim 1, characterized by its operation based on the following sequence of operations:
    A. Each of the beacons available on the network, emits a magnetic wave
    25 continuous low frequency and constant amplitude. Thus, the control loop on said frequency and amplitude, as well as the calibration is performed automatically in the beacon itself, although it can be assisted by inter-beacon or receiver-beacon communications.
    B. The receiver carries out the position estimation, identifying the origin of
    30 ELF signals received from each of the beacons. Specifically, the method of multiple access control to the medium is carried out by frequency division, which makes it possible for the receiver to carry out a unique identification of each of the beaconing elements.
    C. Then, the analog sensing stage installed in the receiving equipment is
    35 is responsible for capturing and adapting these signals to be subsequently digitized. Said stage consists of a triaxial magnetic sensor, amplifiers and a
    filter chain composed of rejected band and antialiasing filters for
    each axis To compensate for the mismatch between the filter chains of
    each axis, the receiver has implemented a self-calibration function in which
    he himself generates a known signal, injects it into the adaptation stage and
    5 Calculate the coefficients that will be applied later in the digital domain.
    D. The ELF signals, already adapted, are converted to the digital domain using a
    Low frequency and high precision digital analog converter.
    AND. The digitized signal is subsequently processed in the module
    processing to obtain the amplitude values of the ELF signals
    10 transmitted. The digital processing consists of a continuous and elimination filter
    equalization, a quadrature mixer and an averaging filter for calculation
    of the amplitude of the signal. While the former eliminates the component of
    continue the signal and undo the disappearance introduced by the stage
    analog, the second allows the processing of baseband signal by
    fifteen A mixture of direct conversion. The calculation of the amplitude of the received signal is
    performed using an infinite response filter of least squares.
    F. Once the amplitude values are obtained, the position estimation is made
    using the multidimensional Newton-Raphson algorithm.
    G. Finally, and once the position estimation data is obtained, the system
    twenty makes use of an extended Kalman filter for merging position data
    estimated together with the inertial sensor data, with the aim of increasing
    The accuracy of the positioning task.
    H. The information obtained is represented on the display of the receiving device through
    of a user interface designed for the system.
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    ES2674123B1|2019-05-10|
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    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    CN205450257U|2016-03-11|2016-08-10|成都理想境界科技有限公司|Space positioning system|
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