Method and system for location-based service using radio frequency beacons

Abstract

A method of performing a location based service and in particular a contactless check-in procedure in a public transportation vehicle, which is considered very user-friendly, but also robust, reliable and accurate. In a first aspect there is provided, a method of performing a location-based service using a radio frequency, RF, signal based positioning system, the method comprising the steps of: - broadcasting, by a mobile device, an RF signal upon approaching the location of the location based service; - receiving, by at least one RF beacon, said RF signal, wherein the RF beacon is installed at the location of the location based service; - measuring, by a processing unit, said a signal strength of the received RF signal, wherein the processing unit is in communicative connection with said at least one RF beacon; - determining, by the processing unit, a location of the mobile device within said location of the location-based service, wherein said location is determined by said measured signal strength; - forwarding, by the processing unit, said location of the mobile device to a central server over a wireless telecommunication network, for comparing the location with a predefined service location for performing a service of said location-based service to said mobile device, wherein the RF beacon comprises an array of antennas arranged for monopulse tracking to accurately determine the location of the mobile device within said predefined service location.

Description

[0001] Title

[0002] Method and system for location-based service using radio frequency beacons.

[0003] Field of the invention

[0004] The present invention generally relates to the field of location-based services, in more in particular to a method and device in which indoor and / or outdoor positioning systems are used for triggering and processing location based services. The present invention further relates to a computer program product for operating a mobile communication device and such system for location-based services.

[0005] Background of the invention

[0006] Location based services are a type of technology that uses the location of a user to provide information, services, or for example entertainment. These services provided, are based on the location of the user and can be accessed through a variety of devices, including smartphones, tablets, and GPS or radio frequency-based devices. Location based services are becoming increasingly popular, as they can help people navigate their surroundings, find nearby services, and access relevant information based on their location.

[0007] Public transportation is an excellent example of the use of a location-based service. Public transportation services, such as buses, trains, and subways, may use location-based technology to provide information to passengers about the location of vehicles, arrival times, and other relevant information.

[0008] From a technical standpoint, location-based services for public transportation typically rely on one of camera systems, GPS technology, wireless communications, or more in general radio frequency based communication. GPS technology may for example be used to track the location of vehicles, which is then transmitted wirelessly to a central server. The central server processes this data in real-time to determine the estimated time of arrival (ETA) of each vehicle at its next stop.

[0009] Conventional check-in routines in public transportation typically involves a ticketing agent or machine at a point of sale or the point of entry, where passengers purchase or validate their fare. While this system has been used for many years, it also has several challenges, including long wait times. Conventional check-in systems can lead to long wait times, particularly during peak travel periods or if there are issues with the ticketing system. This can be frustrating for passengers and can lead to inefficiencies in the overall transportation system. Typical check-in also lacks flexibility as it may not offer flexible payment options or fare structures, which can make it difficult for passengers to choose the best option for their needs. This can lead to dissatisfaction among passengers and can make it difficult to attract new riders. Conventional check-in systems typically also require more staff and infrastructure to operate, which can increase costs for transportation operators. These costs can be passed on to passengers in the form of higher fares, which can make public transportation less accessible for some riders. Conventional check-in systems may also be vulnerable to fraud, particularly if there is not adequate security or monitoring in place, which can lead to lost revenue for transportation operators and can undermine public trust in the system. Finally, conventional check-in systems may raise hygiene concerns, particularly in light of the COVID-19 pandemic. Passengers may be reluctant to touch ticketing machines or interact with ticketing agents due to concerns about the spread of germs and viruses.

[0010] Contact-less check-in systems overcome some of these drawbacks of the conventional check-in routines but may introduce different challenges that need to be addressed to ensure that the system is efficient, accessible, and sustainable over the long term.

[0011] A contact-less check-in routine for public transportation is a typical locationbased service in accordance with the present disclosure. It is however expressed, that the present disclosure is not limited to this particular example as other applications and uses of the proposed method and system may very well be highly suitable and advantageous for other types of location-based services such as any type of mobility or transportation system or any type of merchant based service such as a supermarket. The skilled person will appreciate which other uses may be suitable and advantageous.

[0012] Contactless check-in in public transportation may in general refer to a system where passengers can board a bus, train, or subway or any type of mobility such as shared scooters, bikes, cars, etc., without having to physically touch any surfaces or interact with the driver or ticketing agent. This is typically achieved using certain wireless technology, such as contactless smart cards, mobile ticketing, or automatic fare collection systems.

[0013] Contactless check-in in public transportation is considered to have several advantages over conventional check-in routines, but there still are some challenges. Amongst these challenges are that such contactless check-in requires a reliable, compatible, secure and accurate technical implementation of location detection for such location-based service to succeed. Establishing a technical infrastructure for contactless check-in can be considered challenging. This includes the installation of contactless readers or scanners, communication equipment, and software systems that can communicate with the back-end ticketing and payment systems. The contactless check-in system must also have reliable connectivity to the internet or cellular network to ensure that data can be transmitted and processed in real-time and must be designed with strong security protocols to prevent fraud or misuse. But most of all, the system should be user-friendly, robust, reliable, and accurate.

[0014] Known contactless check-in routines do not succeed, or at least not sufficiently, in fulfilling these requirements.

[0015] It is therefore an object of the present invention, to provide for a method and system for location-based service using radio frequency beacons, and in particular for contactless check-in routine suitable for public transportation and such, in which at least some of the above mentioned drawbacks are addressed.

[0016] Summary of the invention

[0017] The present disclosure, in a first aspect, addresses at least some of the above- mentioned drawbacks and provides a location based service and in particular a contactless check-in procedure in a public transportation vehicle, which is considered very user-friendly, but also robust, reliable and accurate.

[0018] In a first aspect there is provided, a method of performing a location-based service using a radio frequency, RF, signal based positioning system, the method comprising the steps of:

[0019] - broadcasting, by a mobile device, an RF signal upon approaching the location of the location based service; - receiving, by at least one RF beacon, said RF signal, wherein the RF beacon is installed at the location of the location based service; measuring, by a processing unit, said a signal strength of the received RF signal, wherein the processing unit is in communicative connection with said at least one RF beacon;

[0020] - determining, by the processing unit, a location of the mobile device within said location of the location-based service, wherein said location is determined by said measured signal strength;

[0021] - forwarding, by the processing unit, said location of the mobile device to a central server over a wireless telecommunication network, for comparing the location with a predefined service location for performing a service of said location-based service to said mobile device, wherein the RF beacon comprises an array of antennas arranged for monopulse tracking to accurately determine the location of the mobile device within said predefined service location.

[0022] Location-based services (LBS) are services that use information about the location of a device or user to provide value-added services or information. This information is typically obtained using technologies such as GPS, Wi-Fi, Bluetooth, or cellular networks.

[0023] Location-based services are becoming increasingly popular due to the widespread use of mobile devices and the internet. These services can be used for a variety of purposes, including navigation, advertising, social networking, and emergency response.

[0024] Contactless check-in is a type of location-based service that allows passengers to check-in for public transportation using their mobile devices without having to interact with any physical check-in stations. This technology has become increasingly popular in recent years, especially as it is considered highly user-friendly, but also in light of the COVID-19 pandemic.

[0025] Although throughout the description the present disclosure may refer to a contact-less check-in routine for public transportation, as being a typical locationbased service in accordance with the present disclosure, it is once more expressed, that the present disclosure is not limited to this particular example as other applications and uses of the proposed method and system may very well be highly suitable and advantageous for other types of location-based services. Hence, the present disclosure, in all aspects may also be configured specifically for, or at least suitable for a location-based service such as a merchant based service, for example in retail, or in a supermarket or such.

[0026] As example of a typical location based service, contactless check-in works by using location-based communication technology such as RFID, NFC, GPS, Wi-Fi, UWB and Bluetooth or Bluetooth Low Energy, to determine a passenger's location and then allowing them to check-in for their trip from their mobile device. Once a passenger has checked-in, they can then board the public transport without having to show any physical tickets or interact with any staff members.

[0027] There are several advantages to using contactless check-in for public transport. It can reduce the amount of time that passengers spend waiting in line to purchase tickets or check-in. This can lead to a more streamlined and efficient boarding process, which can ultimately save time for both passengers and staff. Further, contactless check-in in public transport is a user-friendly way of checking in passengers to their respective transport vehicles without requiring them to physically touch any surface or exchange any paper tickets with the transport staff.

[0028] Moreover, contactless check-in can help to reduce the spread of infectious diseases such as COVID-19. By allowing passengers to check-in from their mobile devices, they can avoid having to touch any physical surfaces or interact with staff members, which can reduce the risk of transmission.

[0029] What is proposed is a method of performing a location-based service using Radio Frequency, RF, beacons. Hence, a location-based service or context aware service in particular a way of performing a contactless check-in into public transport which checkin routine relies on RF beacons and in particular on Bluetooth LE beacons.

[0030] The method comprises several steps, in which a RF signal is broadcasted, received, measured, compared or processed and forwarded to a central server for further handling and performing the service corresponding to the location based service that is being offered, e.g. in the preferred example, the check-in and / or financial or other transaction into the public transport such as a metro, train or bus.

[0031] The method thus comprises several subsequent steps, at least the steps indicated and described in more detail below. In the first step, the RF signal is broadcasted. The method thus in the first step is comprised of broadcasting with a mobile device such as a mobile (smart)phone, of an RF signal as it, i.e., the mobile phone, approaches the location of the locationbased service, e.g., the entrance of the metro, bus or train. The RF signal is a type of wireless signal that is used for communication between devices and is in particular one or combination of RFID, NFC, GPS, Wi-Fi, UWB and Bluetooth, but most preferably a Bluetooth or Bluetooth Low Energy, LE, signal. In this case, the mobile device is sending out an RF signal that can be picked up by RF beacons that are installed at the location of the location-based service.

[0032] Next, in the second step, the RF signal is received. The RF beacon or beacons receive the RF signal sent by the mobile device as it approaches the location of the location-based service. To this end, the RF beacon or beacons comprise at least one antenna. These RF beacons are installed at the location of the service and are designed to pick up RF signals from nearby mobile devices. As such, the location of the beacons or at least the antennas are chosen carefully, such that the signals can be received at maximum signal strength. The RF beacon can be a device or a system that has an antenna and a receiver designed to receive and analyse RF signals.

[0033] After that, in the following step, the signal strength is measured. After the RF beacon receives the RF signal sent by the mobile device, the signal strength of the received RF signal is measured by a processing unit. The processing unit is in communication with the RF beacon and can analyse the signal strength of the RF signal that was received. The signal strength is a measure of the power of the RF signal received by the RF beacon and can be used to determine the distance between the mobile device and the RF beacon.

[0034] In the next step, the location of the mobile device is determined. Using the measured signal strength, a processing unit can determine the location of the mobile device within the location of the location-based service. Hence, the processing unit can determine at which position the mobile device is positioned within the public transport. The processing unit may be, in an example, a dedicated device, to which the RF beacon is connected. The processing unit may in another alternative example however also be integrated into the RF beacon. But preferably, the RF beacon is arranged for the communication with the mobile phone, whereas the processing unit may be embodied as a dedicated device which is wired or wireless contact with the RF beacon or beacons to obtain the measured signal strength and to process or pre- process the measured data for further handling by a remote server.

[0035] The location of the mobile device is determined based on the strength of the RF signal received by the RF beacon, which indicates how close the mobile device is to the RF beacon. The processing unit uses algorithms to calculate the distance between the mobile device and the RF beacon and then determines the location of the mobile device.

[0036] To determine the position of a mobile device using Bluetooth beacons, several algorithms can be used. The implemented algorithm may be based on one or a combination of the following techniques.

[0037] Received Signal Strength Indicator (RSSI) Approach: This approach uses the strength of the Bluetooth signal received by the mobile device from multiple beacons to calculate the device's position. The RSSI is the power level of the received signal and is measured in decibels (dBm). By comparing the RSSI values from different beacons, the algorithm can calculate the distance of the mobile device from each beacon. The intersection of these distances can then be used to calculate the position of the mobile device.

[0038] Trilateration Approach: This approach uses the distance between the mobile device and at least three Bluetooth beacons to calculate the device's position. This method involves measuring the time it takes for a Bluetooth signal to travel between the beacon and the mobile device. By knowing the speed of the signal, the distance can be calculated. By using three or more beacons, the algorithm can triangulate the position of the mobile device.

[0039] Fingerprinting Approach: This approach involves mapping the signal strength of Bluetooth beacons at different locations within a given area. This creates a "fingerprint" for each location, which can be used to identify the location of a mobile device when it comes into range of the beacons. When the mobile device comes into range of the beacons, the signal strength is measured and compared to the fingerprint database to determine the device's location.

[0040] Kalman Filtering Approach: This approach involves using a Kalman filter to estimate the position of the mobile device based on the signal strength measurements of the Bluetooth beacons. A Kalman filter is a mathematical algorithm that uses a series of measurements over time to estimate the current state of a system. By combining the signal strength measurements with the device's velocity and direction of movement, the Kalman filter can estimate the device's position with greater accuracy.

[0041] In the next step, the location is forwarded to a central server. Once the location of the mobile device is determined, the processing unit forwards this information to a central server over a wireless telecommunication network. The central server is responsible for comparing the location of the mobile device with a predefined service location for performing the service of the location-based service. This comparison ensures that the user is in the correct location to receive the service.

[0042] The present disclosure is characterized by the fact that the RF beacons use an array of antennas arranged for monopulse tracking. The RF beacon used in this method comprises an array of antennas that are strategically positioned within the predefined service location. This integration ensures that the RF beacon is part of the service infrastructure, rather than a standalone device. The antennas in the array can receive RF signals along a first axis, i.e. in a one-dimensional array of antennas, and along a first and second axis, which are orthogonal to each other, i.e. with a two- dimensional array of antennas. Having such layouts of antennas arranged for employing a monopluse techniques to generate a corresponding radiation pattern, will significantly improve the accuracy of the location determination. A typical implementation could be an array disposed at or near the entrance of a location-based service area, such as a bus, train, or metro. Consequently, any passenger entering the service area will the RF signal, radiated according to the monopulse radiation pattern, allowing the device to detect the mobile device's RF signal accurately and regardless of its position on the user, such as in a pocket, bag, or hand.

[0043] Monopulse tracking is used to determine the precise direction of a target by comparing the signal received by multiple antennas. This method may involve splitting the received signal into sum and difference channels, which are then processed to obtain angular information about the target's position. The sum channel provides the total received power, while the difference channels give the angular deviations in azimuth and elevation.

[0044] In the monopulse tracking system or method, the received signals from multiple antennas may be combined using a comparator, which calculates the sum and difference of these signals. The sum signal is proportional to the total power received, and the difference signals represent the phase differences between the antennas. These phase differences are used to calculate the exact angle of arrival of the incoming signal, allowing for precise target localization.

[0045] With the monopulse tracking the accuracy and reliability of RF positioning systems is enhanced by providing real-time angle measurements with high resolution. This technique is less susceptible to signal interference and multipath effects compared to other methods, such as single-beam tracking. By utilizing the precise angular information, monopulse tracking systems can accurately determine the location of a mobile device within a service area, even in complex environments with multiple signal reflections and obstructions.

[0046] The monopulse tracking antenna array is a sophisticated design to enhance location accuracy by differentiating the signal phases received at multiple antenna elements. Each antenna in the array may operate collectively to analyse the direction from which the RF signal is being emitted, allowing for precise determination of the mobile device's position. Preferably, the system may utilize an architecture and design comprising two-element array antennas along with phase shifters, which adjust the beam tracking angle effectively within a specified range. This structure not only simplifies the design by using microstrip and slot lines but also enhances the directivity and focus of the beam, which is beneficial for reducing the error in location tracking.

[0047] In an embodiment, time-modulated antenna arrays may be employed, which provide useful further benefits. Time modulation introduces an additional degree of freedom in beam formation, which can mitigate common issues such as beam imbalance and phase errors. This approach allows for simultaneous generation of sum and difference beams, improving the system's ability to handle off-boresight targets effectively.

[0048] In another embodiment, adaptive beamforming techniques may be employed that dynamically adjust the antenna patterns based on environmental feedback and signal conditions. This will not only improve the resilience of the positioning system against physical and electronic interferences but also optimize the power consumption and operational efficiency of the system.

[0049] In another embodiment machine learning algorithms may be implemented to predict signal distortion and automatically recalibrate the antenna parameters which boost the accuracy and reliability of the monopulse tracking system, providing a more robust and scalable location-based services.

[0050] Known location-based services rely typically on one single RF beacon layout or maybe a RF beacon layout having multiple beacons or multiple antennas but in a configuration wherein each antenna or beacon is operated independently. What that means is, that for example triangulation may be used to determine the location of a mobile device in a triangle of three different RF beacons, but that in such a configuration the distance between each individual beacon and the mobile device is used without any correction for errors in the measurement due to the impact of the human body on the signal.

[0051] The human body is made up of approximately 60% water, which is an excellent conductor of electricity. Therefore, when a Bluetooth signal travels through the human body, it can cause the signal to scatter, reflect, or absorb the energy of the signal. This phenomenon may be referred to as the human body effect, and it can cause a decrease in the signal strength or RSSI.

[0052] When a Bluetooth signal encounters a human body, it can be scattered or reflected in various directions due to the complex structure of the body. This scattering and reflection can cause the signal to lose energy, resulting in a decrease in the RSSI. Additionally, the signal can be absorbed by the human body, which further reduces the signal strength.

[0053] It has been found that this human body effect can be particularly significant when the Bluetooth beacon and receiver are in close proximity to the human body, such as when a user carries a mobile device in their pocket or wears a smartwatch on their wrist. In these scenarios, the human body can create a barrier between the beacon and receiver, causing the signal to be attenuated or blocked. As a result, the RSSI can fluctuate or become unstable, which can make it difficult to accurately determine the position of the mobile device.

[0054] To mitigate the effects of the human body on Bluetooth signals, in accordance with the present method, steps and algorithms are developed and proposed in which location detection is enhanced using a monopulse beam and monopulse tracking. These algorithms may rely on statistical models to estimate the position of the mobile device based on the RSSI readings and can account for fluctuations caused by the human body effect. However, what is proposed is to use Bluetooth beacons with multiple antennas and preferably directional antennas to transmit the signal, which can reduce the impact of the human body effect by directing the signal towards the receiver and avoiding obstacles. With such a configuration of an array of antennas employing monopulse tracking, it is possible to mitigate effects of the human body.

[0055] The array of antennas may also comprise subgroups or subarrays of antennas which are configured in groups of for example four, eight or sixteen individual antennas. The array may also comprise a complete group of two, four, eight, sixteen, thirty-two, sixty four, one hundred twenty eight, or two hundred sixty four individual antennas. The antennas may preferably have linear or circular antenna layouts, may comprise a single antenna layer, having multiple layers, and may preferably be water resistant. The antenna design is preferably that of a patch type, a spiral shape or patch truncated, or a combination thereof. The antenna may have radiation pattern that is omnidirectional, which radiates energy equally in all directions, creating a spherical radiation pattern. An example of such an antenna uses this pattern is a dipole antenna, which is commonly used in Wi-Fi routers and other similar applications. The antenna may also be arranged, in a preferred configuration, for generating a directional pattern. This type of pattern radiates energy in a specific direction, creating a beam-like radiation pattern. Examples of antennas that use this pattern include Yagi and parabolic antennas, which are commonly used in long-range communication applications. Finally, the antenna may have sectoral radiation pattern, which radiates energy in a specific sector or angle, creating a wedge-shaped radiation pattern. Examples of antennas that use this pattern include sectoral antennas, which are commonly used in wireless networks and other similar applications. According to a preferred example, the antennas are arranged or configured to provide a radiation pattern which is non-uniform and has a main lobe which is highly directional.

[0056] For the present system and method, and for any implementation thereof as a Bluetooth beacon-based positioning systems, an antenna radiation pattern could be omnidirectional pattern. Since Bluetooth beacons are designed to transmit their signal in all directions, an omnidirectional antenna would be the typical choice to ensure that the signal is transmitted equally in all directions. It is suggested that this would provide for a more accurate and reliable positioning system since the signal strength would be consistent regardless of the location of the receiver. However, since the location of the user can be estimated with a certain level of accuracy, and the antennas can be chosen strategically, i.e. in a rectangular setup, directing towards a certain area where the user is expected to be, the system in a preferred embodiment, comprises an array of directional pattern radiating antennas employing monopulse radar technology, which is, as indicated above, a type of radar system that can measure the direction to a target with high accuracy. It does this by comparing the received signal from multiple closely spaced antennas or antenna feeds. The main feature of monopulse radar is that it can determine the angle to a target using a single pulse, rather than relying on multiple pulses to average out the measurements.

[0057] The monopulse radar technique is implemented into a Bluetooth beacon, resulting in enabling to transmit precise directional signals, i.e. information in addition to or compared to the regular BLE signals. This BLE with monopulse technique combination allows for more accurate determination of the position, especially useful in complex environments like indoor settings.

[0058] The radiation pattern of the monopulse-based Bluetooth beacon may be defined by one of the following factors of antenna design, frequency and / or beamforming.

[0059] For the antenna design, the antenna array used in the monopulse radar system plays a crucial role in shaping the radiation pattern. Such systems may use an array of antennas configured to receive signals from different angles. The pattern will generally have a main lobe pointing in the desired direction with multiple side lobes.

[0060] For the frequency, the Bluetooth beacon operates typically on the 2.4 GHz ISM band. The radiation pattern at this frequency will be a function of the antenna design and the environment.

[0061] For the beamforming, the monopulse systems may employ beamforming techniques, which electronically steer the beam towards the target. This results in a narrow, directed main lobe with minimized side lobes, enhancing the accuracy of angle measurements.

[0062] The system may have radiation pattern with specific characteristics for the main lobe. The primary lobe of the radiation pattern will be highly directional, focusing the majority of the transmitted energy in a specific direction. This ensures that the beacon's signal is strong and clear in the intended direction.

[0063] The system may have radiation pattern with specific characteristics for the side lobes as well. Side lobes are smaller beams of radiation emitted at angles away from the main lobe. In a well-designed monopulse system, these side lobes are minimized to reduce interference and inaccuracies in angle measurement.

[0064] The radiation pattern may also have characterising nulls or diffs. These are regions where the signal strength is significantly reduced, minimal or even absolute or approximately 0. Monopulse systems can create nulls in specific directions to improve accuracy by distinguishing between signals received from different angles, e.g. the SUM regions. Accordingly the contrast between the SUM and diff signals may be very high, which increases the accuracy substantially.

[0065] With the monopulse tracking the system benefits from overlapping antenna beams and instantaneous sum-and-difference processing to deliver sub-beamwidth angular accuracy from a single pulse. In the proposed system and method, an antenna array, and more preferably a compact phased-array or dual-horn reflector antenna feeds a Z (sum) channel and orthogonal A (difference) channels via low-loss hybrid couplers; the ratio A / Z yields real-time azimuth and elevation errors without mechanical scanning. A digital ratio demodulator linearizes this signal around boresight, while calibration routines correct amplitude and phase imbalances caused by vehicle mounting or multipath. The resulting error voltages may preferably employ beamforming or drive a high-bandwidth servo loop (as a more mechanical beamformer, although the system preferably employs an electronic beamformer) to maintain lock on the target device, enabling sub-meter position updates for automatic check-in services. Phase-comparison variants further enhance noise performance, and wideband LFM pulses allow concurrent range estimation, all without user intervention or satellite dependency.

[0066] Additionally, the system may include a comparator network and signalprocessing chain: wherein Z and A ports are generated by balanced hybrid couplers or magic-tee assemblies designed to preserve phase congruence; their outputs are digitized, preferably by high-dynamic-range ADCs and processed in an FPGA or DSP or similar hardware that enables and implements A / Z ratio demodulation, dead-zone linearization via lookup tables, and digital filtering to suppress noise and multipath artifacts. The system, in an example, supports both amplitude-comparison and phasecomparison modalities, the former offering simpler analog front-end hardware, the latter using phase-detection loops across sub-apertures to improve low-SNR performance. Calibration is performed at startup and periodically in-service using known pilot tones or reference beacons to compensate for drift, antenna element mismatches, and installation variances without user involvement.

[0067] A servo-control subsystem or similar electronic beamforming comprised in the system may adapt its loop bandwidth to expected motion profiles: a wide-loop bandwidth (\~100 Hz) tracks fast maneuvers (e.g. taxi turns), while automatic bandwidth reduction minimizes jitter in static or slow-moving scenarios. Alternatively, an electronic beamformer can null the A error digitally, avoiding mechanical actuators. For security and robustness, sum and difference channels may be authenticated via cross-channel correlation checks to detect jamming or spoofing attempts. Wideband LFM chirp transmission / reception further enables simultaneous range tracking by matched filtering, yielding independent distance estimates that fuse with angle data to refine 3D positioning, which may preferably be contained in a compact module suitable for integration into a vehicle-mounted unit.

[0068] In addition, it is also proposed, in an example, to implement further techniques of using algorithms to reduce the human body effect, which techniques take into account the estimated attenuation caused by the human body. For instance, it is proposed to use an algorithms based on machine learning to learn the effect of the human body on signal strength based on historical data and use this information to estimate the receiver's position.

[0069] In further addition or as alternative, further advanced techniques can use the characteristics of the signal to estimate the position of the receiver, i.e. the mobile device. For example, an algorithms is proposed to analyse the phase difference between the signal received by the receiver from different antennas of the same Bluetooth beacon. Since the phase difference is affected by the distance travelled by the signal, it can be used to estimate the position of the receiver, even if the signal strength is affected by the human body.

[0070] The Bluetooth beacon transmits a signal that is received by multiple antennas on the receiver. As the signal travels from the beacon to the receiver, it can experience changes in phase due to interference from objects in the environment, such as walls, furniture, and other people. By analysing the phase difference between the signals received by each antenna, the system can calculate the distance between the mobile device and the beacon, and therefore determine the position of the device. The phase difference can be measured in a variety of ways. One approach is to use multiple antennas on the receiver that are spaced apart by a known distance. By comparing the phase difference between the signals received by each antenna, the system can calculate the distance to the beacon. Another approach is to use phaseshift keying (PSK) modulation, which encodes data onto the phase of the signal. By analysing the phase difference between the signals received by the different antennas, the system can determine the phase shift and therefore the distance to the beacon.

[0071] Overall, the phase difference between the signals received by different antennas of the same Bluetooth beacon is considered an effective way of accurately determining the position of a mobile device in a Bluetooth positioning system such as in the proposed location base service like in public transport. By analysing the phase difference, the system can overcome the challenges posed by the human body and other environmental factors and accurately determine the position of the device.

[0072] In an example, the array of antennas is configured for a directional radiation directed in an predefined direction, which may correspond to the entrance of the public transport vehicle, e.g. in the direction of the door of the bus, or near or close to the driver of the bus, or corresponding to a virtual line or axis which users need to pass when entering the vehicle.

[0073] Instead of using unidirectional antennas, the array preferably comprises directional antennas with a radiation direction directed towards a specific direction of where most likely the mobile device is located. Hence, this has the effect that the it may increase the range, accuracy, and thus signal strength as well as reduce the interference and also indirectly improve security as the range of the signal is limited such that it is more difficult for unauthorized users to intercept and manipulate the signal.

[0074] In an example, the array of antennas comprises at least two antennas spaced apart by a distance approximately equal to half the wavelength (0.5A) of the operating frequency of the RF signal.

[0075] In an example, determining the location of the mobile device comprises estimating an angle of arrival (AoA) of the RF signal based on the array of antennas.

[0076] In an example, determining the location of the mobile device comprises mitigating multipath effects by exploiting spatial diversity provided by the array of antennas. In an example, the array of antennas provides antenna diversity to improve link quality and range of the RF signal reception.

[0077] In an example, the RF beacon is a Bluetooth Low Energy (BLE) beacon operating in the 2.4 GHz ISM band.

[0078] In an example, the array of antennas comprises a two-dimensional array, the two-dimensional array comprising: a first set of at least two antennas arranged along a first axis; and a second set of at least two antennas arranged along a second axis, the second axis being orthogonal to the first axis.

[0079] In a further example, determining the location of the mobile device comprises estimating an azimuth angle and an elevation angle of arrival of the RF signal based on the two-dimensional array of antennas.

[0080] In an example, the two-dimensional array of antennas provides enhanced spatial diversity and multipath mitigation in both horizontal and vertical planes.

[0081] In an example, the array of antennas comprises a one-dimensional array of at least two antennas arranged along a single axis, the one-dimensional array generating a curtain-like RF signal pattern.

[0082] In a further example, the curtain-like RF signal pattern is used as a detection trigger to identify when the mobile device enters or exits the predefined service location.

[0083] In an example, said location based service is a contactless check-in into a public transportation, wherein said location of the location based service is any location within a vehicle of said public transportation, and wherein said predefined service location is the entrance of said vehicle of said public transportation.

[0084] One aspect of the present invention relates to an array of antennas for a Bluetooth beacon. An array of antennas may be understood as a configuration of multiple antennas arranged in a specific geometric pattern to improve signal reception and transmission characteristics. A Bluetooth beacon may be understood as a device that uses Bluetooth Low Energy (BLE) technology to broadcast signals to nearby Bluetooth-enabled devices, typically for the purpose of location tracking or proximity sensing.

[0085] It may be provided that the array of antennas comprises at least two antennas spaced apart by a distance approximately equal to half the wavelength (0.5A) of the operating frequency of the RF signal. An antenna may be understood as a transducer that converts electrical power into radio waves, and vice versa, while the wavelength (A) may be understood as the distance over which the wave's shape repeats. This arrangement allows for improved phase difference measurement between the received signals, enhancing the accuracy of angle of arrival (AoA) estimation, thereby improving the precision of mobile device location tracking.

[0086] It may be provided that determining the location of the mobile device comprises estimating an angle of arrival (AoA) of the RF signal based on the array of antennas. The angle of arrival (AoA) may be understood as the angle at which a wavefront from the mobile device arrives at the antennas. This arrangement allows for precise directional information to be obtained, enabling accurate triangulation and positioning of the mobile device.

[0087] It may be provided that determining the location of the mobile device comprises mitigating multipath effects by exploiting spatial diversity provided by the array of antennas. Multipath effects may be understood as the phenomenon where signals take multiple paths to reach the receiver, causing interference. Spatial diversity may be understood as the use of multiple antennas at different locations to receive the signal. This arrangement helps in distinguishing between direct and reflected signals, thus improving the reliability and accuracy of location determination.

[0088] It may be provided that the array of antennas provides antenna diversity to improve link quality and range of the RF signal reception. Antenna diversity may be understood as using multiple antennas to receive the same signal, which can be combined to improve the overall quality and strength of the received signal. This arrangement reduces the probability of signal fading and dropouts, enhancing the overall robustness and performance of the Bluetooth beacon system.

[0089] It may be provided that the RF beacon is a Bluetooth Low Energy (BLE) beacon operating in the 2.4 GHz ISM band. The 2.4 GHz ISM band may be understood as the industrial, scientific, and medical (ISM) radio band reserved internationally for the use of radio frequency (RF) energy for industrial, scientific, and medical purposes. This arrangement ensures compatibility with a wide range of Bluetooth-enabled devices, providing efficient and low-power wireless communication.

[0090] It may be provided that the array of antennas comprises a two-dimensional array, the two-dimensional array comprising a first set of at least two antennas arranged along a first axis and a second set of at least two antennas arranged along a second axis, the second axis being orthogonal to the first axis. A two-dimensional array may be understood as an arrangement of antennas in a plane with two orthogonal axes. This arrangement allows for improved spatial resolution and directional accuracy in both horizontal and vertical planes, enhancing the precision of location tracking.

[0091] It may be provided that determining the location of the mobile device comprises estimating an azimuth angle and an elevation angle of arrival of the RF signal based on the two-dimensional array of antennas. The azimuth angle may be understood as the angle measured clockwise from a reference direction on the horizontal plane, while the elevation angle may be understood as the angle between the horizontal plane and the line of sight to the signal source. This arrangement enables comprehensive three- dimensional positioning of the mobile device.

[0092] It may be provided that the two-dimensional array of antennas provides enhanced spatial diversity and multipath mitigation in both horizontal and vertical planes. This arrangement ensures that signals received from different paths can be effectively separated and analyzed, significantly reducing errors caused by multipath interference and improving the accuracy of the tracking system.

[0093] It may be provided that the array of antennas comprises a one-dimensional array of at least two antennas arranged along a single axis, the one-dimensional array generating a curtain-like RF signal pattern. A one-dimensional array may be understood as an arrangement of antennas along a single straight line. This arrangement creates a focused signal pattern, which can be used for precise detection within a specific area.

[0094] It may be provided that the curtain-like RF signal pattern is used as a detection trigger to identify when the mobile device enters or exits the predefined service location. A detection trigger may be understood as a mechanism that initiates an action when a specific condition is met. This arrangement allows for efficient and automated monitoring of device presence within a designated area, facilitating applications such as access control or attendance tracking.

[0095] It may be provided that said location-based service is a contactless check-in into public transportation, wherein said location of the location-based service is any location within a vehicle of said public transportation, and wherein said predefined service location is the entrance of said vehicle of said public transportation. A location- based service may be understood as a service that uses geographic data to provide information or functions. This arrangement enables seamless and automatic check-in for passengers, improving convenience and efficiency in public transportation systems.

[0096] A highly suitable application for the proposed method is the use as contactless check-in into public transport, and with such a degree that the ease of use is very high. Typical contactless check-in in public transport make use of tapping or touching a device, smart card of mobile phone on a dedicated surface, such that a transaction is performed. With the present system effortless check-in is achieved. What that means is, that the user does not need to place the mobile device onto such a touch or tap surface when checking-in, but can leave their mobile device in their pocket, bag or what ever and the system is that accurate that the location of the person can be determined to such level of accuracy that distinction can be made between mobile devices which are near the vehicle of the public transportation, and those who are actually in them and thus use public transport, and should be ticketed accordingly. Hence, for which the transport with the vehicle is the service of the location based service of the present disclosure. To this end, the array of antenna’s may be disposed at the entrance of the public transportation vehicle, e.g. at the doors of a train, bus, metro or the like. The array of antenna’s may also and alternatively be disposed at the entrance or near the driver of the vehicle, and preferably to such extent that the array is directed in accordance with the RF signal to be directed along the

[0097] In an example, the step of forwarding comprises: transmitting the location of the mobile device to said central server, being a central ticketing and payment system of said public transportation; and debiting an appropriate fare amount from an account of the user of said mobile device, wherein said fare corresponds with a duration of use in the public transportation.

[0098] In an example, the method further comprising: adjusting the signal strength of the RF signal based on the number of mobile devices in proximity to the RF beacon; and dynamically optimizing the RF signal strength to reduce interference and improve accuracy of location measurements. In an example, the RF beacon is arranged for one of RFID, NFC, GPS, Wi-Fi, UWB, Bluetooth and preferably Bluetooth Low Energy, for said RF signal to comprise an RFID, NFC, GPS, Wi-Fi, UWB, Bluetooth and preferably Bluetooth Low Energy signal.

[0099] In an example, the step of determining, by the processing unit, comprise: determining, by the processing unit, a location of the mobile device within said location of the location based service, wherein said location is determined by said measured signal strength as Received Signal Strength Indicator.

[0100] In an example, the step of determining, by the processing unit, comprise: determining, by the processing unit, a location of the mobile device within said location of the location based service, wherein said location is determined by trilateration, using a distance between said mobile device and each antenna of the array of antennas.

[0101] In an example, the step of determining, by the processing unit, comprise: determining, by the processing unit, a location of the mobile device within said location of the location based service, wherein said location is determined by from a signal fingerprinting comprising mapping signal strength of RF beacon at through each antenna of the array of antennas.

[0102] In an example, the step of determining, by the processing unit, comprise: determining, by the processing unit, a location of the mobile device within said location of the location based service, wherein said location is determined by kalman filtering, using a combined signal strength from a series of measurements over time between said mobile device and each antenna of the array of antennas, wherein said combined signal strength is preferably calculated from an average of said series of measurements, or a sum of said series of measurement.

[0103] In an example, the method further comprising the step of: calibrating, by the processing unit, said RF beacon, based on a received signal strength of a reference RF signal received from each antenna of the array of antennas.

[0104] In an example, the step of calibrating comprises: calibrating, by the processing unit, said RF beacon, based on received signal strengths of a plurality of reference RF signals received historical data from each antenna of the array of antennas.

[0105] In an example, the step of calibrating comprises: calibrating, by the processing unit, said RF beacon according to a calibration algorithm, based on received signal strengths of a plurality of reference RF signals received historical data from each antenna of the array of antennas, and wherein the calibration algorithm is defined from a machine learning algorithm.

[0106] In an example, the machine learning algorithm is defined by: obtaining a plurality of historical received signal strengths for a given RF signal of said RF beacon and said array of antennas; pre-processing said plurality of historical received signal strengths to extract relevant features; training said machine learning algorithm using the extracted features and corresponding RF signal strengths; applying the trained machine learning algorithm to new received signal strengths to calibrate the RF signal strength; wherein the trained machine learning algorithm is able to learn a relationship between the extracted features and the corresponding RF signal strengths, for said calibrated RF signal strength to provide a more accurate measure of the true signal strength.

[0107] Machine learning algorithms can be used to calibrate Received Signal Strength Indicator Bluetooth signals between a mobile device and a Bluetooth beacon by analysing the RSSI data to build a model that accurately predicts the distance between the mobile device and the beacon. This calibration is beneficial because RSSI values may vary depending on environmental factors such as walls and obstacles, and therefore benefit for calibration, giving more accurate measures of distance as compared to without calibration.

[0108] At least the following machine learning algorithms may be used, including:

[0109] K-Nearest Neighbors (KNN): This algorithm uses the distance between data points to make predictions. In the context of RSSI calibration, KNN can be used to find the closest points in the training data to the RSSI data collected from the mobile device and beacon, and use their distance as a prediction of the distance between the mobile device and the beacon.

[0110] Random Forest: This algorithm uses an ensemble of decision trees to make predictions. In the context of RSSI calibration, a Random Forest can be trained on the RSSI data collected from the mobile device and beacon, and used to predict the distance between the two.

[0111] Support Vector Machine (SVM): This algorithm is used to find the hyperplane that separates the data into different classes. In the context of RSSI calibration, SVM can be used to find the hyperplane that best separates the RSSI data collected from the mobile device and beacon, and use the distance to the hyperplane as a prediction of the distance between the two.

[0112] Artificial Neural Networks (ANN): This algorithm is modelled after the structure of the human brain, and can be used to make predictions based on a large amount of input data.

[0113] In a second aspect, there is provided positioning system for performing a location based service using a radio frequency, RF, signal based positioning system, the system comprising: a mobile device arranged for broadcasting an RF signal upon approaching a location of the location based service; an RF beacon arranged for receiving said RF signal, wherein the RF beacon is installed at the location of the location based service; a processing device arranged for measuring, said a signal strength of the received RF signal, and wherein the processing unit is in communicative connection with said at least one RF beacon, and said processing device being arranged for determining a location of the mobile device within said location of the location based service, wherein said location is determined by said measured signal strength, and said processing device being arranged for forwarding said location of the mobile device to a central server over a wireless telecommunication network; a central server arranged for receiving said location for comparing said location with a predefined service location for performing a service of said location based service to said mobile device; wherein the RF beacon comprises an array of antennas arranged for monopulse tracking to accurately determine the location of the mobile device within said predefined service location.

[0114] In an example, the positioning system is configured as a system for contactless check-in into a public transport vehicle, and said location based service being said check-in into said public transport vehicle. In an example, the RF beacon is arranged for one of RFID, NFC, GPS, Wi-Fi, UWB, Bluetooth and preferably Bluetooth Low Energy, for said RF signal to comprise an RFID, NFC, GPS, Wi-Fi, UWB, Bluetooth and preferably Bluetooth Low Energy signal.

[0115] In a third aspect, there is provided a computer program product loadable into the internal memory of a computer comprising computer program code portions for performing a location based service using a radio frequency, RF, signal based positioning system by performing the steps according to any of the previous claims 1- 17, when said computer program product is executed by one or more cores of said computer.

[0116] The method may be effectively performed by a suitable programmed processor or programmable controller, such as a micro-processor or micro controller provided with a communication device such as a smartphone, tablet, portable (laptop) computer, smartwatch or the like.

[0117] As such, the present disclosure is also directed to a computer program product, comprising a readable storage medium, comprising instructions which, when executed on at least one processor, cause the at least one processor to carry out the method according to any of the embodiments as disclosed above.

[0118] The present invention's location-based service finds diverse applications across various sectors. In public transportation, it enables automated check-in / check-out via wireless protocols, offering seamless journey registration and eliminating manual validation. Dynamic route optimization leverages GPS and cellular data to recommend transit options, adjust routes in real-time, and integrate schedules. Proximity-based service activation initiates fare calculations or triggers access to mobility solutions upon boarding. Location-aware attendance tracking utilizes geofencing, QR codes, or beacons for workforce management and event participation. Resource allocation and fleet coordination optimize dispatch and routing by monitoring real-time positions of assets. Contextual notifications, triggered by geographic locations, promote nearby services or guide navigation. Spatial matching algorithms facilitate social and commercial networking, connecting users with peers or vendors within a defined radius. Integrating sensors, loT devices, and cloud-based analytics processes spatial data, authenticates users, and executes actions autonomously. Interfacing with third- party platforms enhances accuracy and interoperability, enabling adaptable deployment in transportation, logistics, retail, and smart-city ecosystems for improved efficiency and user convenience.

[0119] In any aspect of the present invention, the location-based service may comprise one or more of: automated transit check-in / check-out, such as trains, trams, metro’s, busses, taxi’s, but also dynamic route optimization, proximity-based service activation, location-aware attendance tracking, resource allocation and fleet coordination, contextual notifications, social or commercial networking, personnel tracking within secure facilities (e.g., hospitals, factories), optimized delivery routing for logistics, geofenced reminders for task management, and location-based advertising tailored to user proximity.

[0120] It is expressed that any advantage or effect of any of the examples of the first aspect may also apply to those of the second and third aspect of the present disclosure. Hence, the examples of the first aspect may also apply for the second and third aspect respectively.

[0121] Brief description of the Drawings

[0122] The invention will be further elucidated on the basis of non-limiting examples shown in the figures, wherein:

[0123] Figure 1 shows the steps of the method of calibration of a positioning system according to the present disclosure;

[0124] Figure 2 shows a location based service according to an aspect of the present disclosure which is implemented as a contactless check-in into a public transport vehicle;

[0125] Figure 3 shows the amplitudes of the radiated RF signals emitted by a positioning system according to the present disclosure;

[0126] Figure 4 shows a PCB with antennas of a positioning system according to the present disclosure;

[0127] Figure 5 shows the radiation patterns of both a SUM and DIFF of RF signals emitted by a positioning system according to the present disclosure; Detailed description

[0128] Fig. 1 shows a method 10 of performing a location based service using a radio frequency, RF, signal based positioning system, the method comprising the steps of: broadcasting 11 , by a mobile device, an RF signal upon approaching the location of the location based service; receiving 12, by at least one RF beacon, said RF signal, wherein the RF beacon is installed at the location of the location based service; measuring, by a processing unit, said a signal strength of the received RF signal, wherein the processing unit is in communicative connection with said at least one RF beacon; determining 13, by the processing unit, a location of the mobile device within said location of the location based service, wherein said location is determined by said measured signal strength; forwarding 14, 15, by the processing unit, said location of the mobile device to a central server over a wireless telecommunication network, for comparing the location with a predefined service location for performing a service of said location based service to said mobile device; wherein the RF beacon comprises an array of antennas arranged for monopulse tracking to accurately determine the location of the mobile device within said predefined service location.

[0129] The method 10 may be performed by a computer program product loadable into the internal memory of a computer, for example of the mobile phone 23 and / or central server 28, i.e. a service located near, close or in the area of the service to be provided, or more preferably in a cloud environment. The computer program product comprises computer program code portions for performing the steps of the method 10, when the computer program product is executed by one or more cores of the computer.

[0130] Fig. 2 shows a positioning system 20 for performing a location based service using a radio frequency, RF, signal based positioning system, wherein the RF signal is preferably a Bluetooth Low Energy signal. The example shown in Fig. 2 is a bus 21 which is the location of the location based service. The location based service in this example is a check-in or ticketing routine in which the check-in is not only contactless, but also effortless as it does not require the user to take his or her mobile device, in the example shown here a mobile phone 23, out of their bag, pocket or what so ever. The mobile phone 23 can stay where it is, as long as it is carried by the user, e.g. on or close to their body. In such a way there is a clear link between the actual position of the user, and the mobile phone 23.

[0131] The system 20 comprises several components, being the mobile device 23, or in particular the mobile phone. The phone is arranged to broadcast an RF signal. In particular, this signal is a Bluetooth and more preferably, a Bluetooth Low Energy, LE, signal. As such, the mobile phone 23 should at least have Bluetooth enabled. If the processing device 26 cannot detect any signal, it may conclude that there is no source of RF signal radiation and thus the mobile phone does not transmit a Bluetooth signal. This may be due to a dead battery, but also on purpose, to tamper with the system, e.g. in an attempt of fare dogging. This may be signalled to the bus driver, e.g. by a auditive and / or visual signal.

[0132] The system 20 further comprises at least one device with a RF beacon 25. The beacon may be embodied in a specific housing 25, or may also be positioned and integrated into a housing part of the vehicle. The housing 25 may be integrated into or attached to the ceiling of the vehicle, or may be integrated or attached elsewhere. The PCT with the antennas 40 may also be attached to the ceiling or integrated into the ceiling of the vehicle, and preferably near or path where the passengers pass and enter the bus, e.g. at or adjacent the driver and / or at or in close proximity of the door and more preferably the front door of the bus. Hence, most preferably the PCT with antennas 40 is attached to the ceiling or integrated into the ceiling at the front door of the bus or at the bus driver where the passengers pass the driver. Preferably, the beacon is an RF Bluetooth signal radiating beacon. The beacon is connected through wiring with an array of antennas 24a-24d, disposed on for example a PCB 40 and may be attached in or behind a wall part of other part of the housing of the vehicle. The antennas 24a, 24b, 24c, 24d are preferably distributed according to a certain pattern as shown in Fig. 4. The antennas are arranged to generate a monopole radiation pattern and are thus preferably directional antennas which radiate in a direction upward towards the estimated location of the mobile device 23. In Fig. 5 a radiation pattern is shown of the SUM and the diff signals which clearly indicate that the SUM is maximized in the direction of the arrow, which represents a certain direction, e.g. approximately 0 degrees which is the direction in which the mobile device 23 is detect. The diff signal is clearly approximately null hence, there is a clear contrast and efficient direction detection achieved with such a monopole radiation pattern. The pattern shown in Fig. 5 corresponds to the sum and difference beams 30 shown in Fig. 3, which are the result of the radiation of the RF signals emitted by the antennas 24a, 24b, 24c, 24d disposed on the PCB 40. These antennas 24a, 24b belong to a first subset for a first direction of detection, and the other antennas 24c, 24d belong to a second subset for a second direction of detection, orthogonal to the first. The antennas have specific distance between them, indicated by the distances 29a, 29b and may preferably be approximately 1 A, 2 A, or most preferably 0.5 A.

[0133] The beacon may be is connected to a processing device, which is preferably housed in the housing 25 and is arranged for measuring the signal strength of the received RF signal from each antenna 24a-24d of the beacon. The processing unit is in communicative connection with the at least one RF beacon, and the processing device is arranged to determine a location of the mobile device 23 within the location of the bus 21. The location is determined by the measured signal strength, and the processing device forwards the location of the mobile device 23 to a central server 28 over a wireless telecommunication network. The server 28 is preferably a cloud based server 28 which is arranged for further processing the fare ticketing and debiting the fare amount on a debiting account of the user of the mobile device.

[0134] Clauses

[0135] 1. A method (10) of performing a location based service using a radio frequency, RF, signal based positioning system, the method comprising the steps of: broadcasting (11), by a mobile device, an RF signal upon approaching the location of the location based service; receiving (12), by at least one RF beacon, said RF signal, wherein the RF beacon is installed at the location of the location based service; measuring, by a processing unit, said a signal strength of the received RF signal, wherein the processing unit is in communicative connection with said at least one RF beacon; determining (13), by the processing unit, a location of the mobile device within said location of the location based service, wherein said location is determined by said measured signal strength; forwarding (14, 15), by the processing unit, said location of the mobile device to a central server over a wireless telecommunication network, for comparing the location with a predefined service location for performing a service of said location based service to said mobile device; wherein the RF beacon comprises an array of antennas arranged for monopulse tracking to accurately determine the location of the mobile device within said predefined service location.

[0136] 2. The method (10) of performing a location based service according to any of the previous claims, wherein the array of antennas may also comprise subgroups or subarrays of antennas which are configured in groups of for example four, eight or sixteen individual antennas, preferably two, four, eight, sixteen, thirty-two, sixty four, one hundred twenty eight, or two hundred sixty four individual antennas.

[0137] 3. The method (10) of performing a location based service according to any of the previous claims, wherein the RF beacon is arranged for one of RFID, NFC, GPS, WiFi, UWB, and preferably Bluetooth and more preferably Bluetooth Low Energy, for said RF signal to comprise an RFID, NFC, GPS, Wi-Fi, UWB, and preferably Bluetooth and more preferably Bluetooth Low Energy signal.

[0138] 4. The method (10) of performing a location based service according to any of the previous claims, wherein the array of antennas is configured for a directional radiation directed in an predefined direction, which may correspond to the entrance of a public transport vehicle.

[0139] 5. The method (10) of performing a location based service according to any of the previous claims, wherein the array of antennas comprises at least two antennas spaced apart by a distance approximately equal to half the wavelength (0.5A) of the operating frequency of the RF signal. 6. The method (10) of performing a location based service according to any of the previous claims, wherein determining the location of the mobile device comprises estimating an angle of arrival (AoA) of the RF signal based on the array of antennas.

[0140] 7. The method (10) of performing a location based service according to any of the previous claims, wherein determining the location of the mobile device comprises mitigating multipath effects by exploiting spatial diversity provided by the array of antennas.

[0141] 8. The method (10) of performing a location based service according to any of the previous claims, wherein the array of antennas provides antenna diversity to improve link quality and range of the RF signal reception.

[0142] 9. The method (10) of performing a location based service according to any of the previous claims, wherein the RF beacon is a Bluetooth Low Energy (BLE) beacon operating in the 2.4 GHz ISM band.

[0143] 10. The method (10) of performing a location based service according to any of the previous claims, wherein the array of antennas comprises a two-dimensional array, the two-dimensional array comprising: a first set of at least two antennas arranged along a first axis; and a second set of at least two antennas arranged along a second axis, the second axis being orthogonal to the first axis.

[0144] 11. The method (10) of performing a location based service according to claim 10, wherein determining the location of the mobile device comprises estimating an azimuth angle and an elevation angle of arrival of the RF signal based on the two-dimensional array of antennas.

[0145] 12. The method (10) of performing a location based service according to any of the previous claims, wherein the two-dimensional array of antennas provides enhanced spatial diversity and multipath mitigation in both horizontal and vertical planes. 13. The method (10) of performing a location based service according to any of the previous claims, wherein the array of antennas comprises a one-dimensional array of at least two antennas arranged along a single axis, the one-dimensional array generating a curtain-like RF signal pattern.

[0146] 14. The method (10) of performing a location based service according to claim 13, wherein curtain-like RF signal pattern is used as a detection trigger to identify when the mobile device enters or exits the predefined service location.

[0147] 15. The method (10) of performing a location based service according to any of the previous claims, wherein said location of the location based service is any location within a vehicle of said public transportation, and wherein said predefined service location is the entrance of said vehicle of said public transportation.

[0148] 16. The method (10) of performing a location based service according to any of the previous claims, wherein said location based service is a contactless check-in into a public transportation, wherein said location of the location based service is any location within a vehicle of said public transportation, and wherein said predefined service location is the entrance of said vehicle of said public transportation.

[0149] 17. The method (10) of performing a location based service according to claim 3, wherein the step of forwarding (14, 15) comprises: transmitting (14) the location of the mobile device to said central server, being a central ticketing and payment system of said public transportation; and debiting (15) an appropriate fare amount from an account of the user of said mobile device, wherein said fare corresponds with a duration of use in the public transportation.

[0150] 18. The method (10) of performing a location based service according to any of the previous claims, the method further comprising: adjusting the signal strength of the RF signal based on the number of mobile devices in proximity to the RF beacon; and dynamically optimizing the RF signal strength to reduce interference and improve accuracy of location measurements.

[0151] 19. The method (10) of performing a location based service according to any of the previous claims, wherein the RF beacon is arranged for one of RFID, NFC, GPS, WiFi, UWB, Bluetooth and preferably Bluetooth Low Energy, for said RF signal to comprise an RFID, NFC, GPS, Wi-Fi, UWB, Bluetooth and preferably Bluetooth Low Energy signal.

[0152] 20. The method (10) of performing a location based service according to any of the previous claims, wherein the step of determining, by the processing unit, comprise: determining, by the processing unit, a location of the mobile device within said location of the location based service, wherein said location is determined by said measured signal strength as Received Signal Strength Indicator.

[0153] 21. The method (10) of performing a location based service according to any of the previous claims, wherein the step of determining, by the processing unit, comprise: determining, by the processing unit, a location of the mobile device within said location of the location based service, wherein said location is determined by trilateration, using a distance between said mobile device and each antenna of the array of antennas.

[0154] 22. The method (10) of performing a location based service according to any of the previous claims, wherein the step of determining, by the processing unit, comprise: determining, by the processing unit, a location of the mobile device within said location of the location based service, wherein said location is determined by from a signal fingerprinting comprising mapping signal strength of RF beacon at through each antenna of the array of antennas.

[0155] 23. The method (10) of performing a location based service according to any of the previous claims, wherein the step of determining, by the processing unit, comprise: determining, by the processing unit, a location of the mobile device within said location of the location based service, wherein said location is determined by kalman filtering, using a combined signal strength from a series of measurements over time between said mobile device and each antenna of the array of antennas, wherein said combined signal strength is preferably calculated from an average of said series of measurements, or a sum of said series of measurement.

[0156] 24. The method (10) of performing a location based service according to any of the previous claims, the method further comprising the step of: calibrating, by the processing unit, said RF beacon, based on a received signal strength of a reference RF signal received from each antenna of the array of antennas.

[0157] 25. The method (10) of performing a location based service according to claim 24, wherein the step of calibrating comprises: calibrating, by the processing unit, said RF beacon, based on received signal strengths of a plurality of reference RF signals received historical data from each antenna of the array of antennas.

[0158] 26. The method (10) of performing a location based service according to claim 24, wherein the step of calibrating comprises: calibrating, by the processing unit, said RF beacon according to a calibration algorithm, based on received signal strengths of a plurality of reference RF signals received historical data from each antenna of the array of antennas, and wherein the calibration algorithm is defined from a machine learning algorithm.

[0159] 27. The method (10) of performing a location based service according to claim 26, wherein the machine learning algorithm is defined by: obtaining a plurality of historical received signal strengths for a given RF signal of said RF beacon and said array of antennas; pre-processing said plurality of historical received signal strengths to extract relevant features; training said machine learning algorithm using the extracted features and corresponding RF signal strengths; applying the trained machine learning algorithm to new received signal strengths to calibrate the RF signal strength; wherein the trained machine learning algorithm is able to learn a relationship between the extracted features and the corresponding RF signal strengths, for said calibrated RF signal strength to provide a more accurate measure of the true signal strength.

[0160] 28. A positioning system (20) for performing a location based service using a radio frequency, RF, signal based positioning system, the system comprising: a mobile device (23), arranged for broadcasting an RF signal upon approaching a location of the location based service; an RF beacon (27), arranged for receiving said RF signal, wherein the RF beacon is installed at the location of the location based service; a processing device (26), arranged for measuring, said a signal strength of the received RF signal, and wherein the processing unit is in communicative connection with said at least one RF beacon, and said processing device being arranged for determining a location of the mobile device within said location of the location based service, wherein said location is determined by said measured signal strength, and said processing device being arranged for forwarding said location of the mobile device to a central server over a wireless telecommunication network; a central server (28), arranged for receiving said location for comparing said location with a predefined service location for performing a service of said location based service to said mobile device; wherein the RF beacon comprises an array of antennas arranged for monopulse tracking to accurately determine the location of the mobile device within said predefined service location.

[0161] 29. The positioning system (20) of claim 28, wherein the positioning system is configured as a system for contactless check-in into a public transport vehicle (21), and said location based service being said check-in into said public transport vehicle (21).

[0162] 30. A computer program product loadable into the internal memory of a computer comprising computer program code portions for performing a location based service using a radio frequency, RF, signal based positioning system (20) by performing the steps according to any of the previous claims 1-27, when said computer program product is executed by one or more cores of said computer.

Claims

CLAIMS1. A method (10) of performing a location based service using a radio frequency, RF, signal based positioning system, the method comprising the steps of: broadcasting (11), by a mobile device, an RF signal upon approaching the location of the location based service; receiving (12), by at least one RF beacon, said RF signal, wherein the RF beacon is installed at the location of the location based service; measuring, by a processing unit, said a signal strength of the received RF signal, wherein the processing unit is in communicative connection with said at least one RF beacon; determining (13), by the processing unit, a location of the mobile device within said location of the location based service, wherein said location is determined by said measured signal strength; forwarding (14, 15), by the processing unit, said location of the mobile device to a central server over a wireless telecommunication network, for comparing the location with a predefined service location for performing a service of said location based service to said mobile device; wherein the RF beacon comprises an array of antennas arranged for monopulse tracking to accurately determine the location of the mobile device within said predefined service location.

2. The method of claim 1 , wherein determining the location comprises estimating an angle-of-arrival of the RF signal by A / Z ratio processing using the antenna array, and exploiting spatial diversity of the array to mitigate multipath effects and provide antenna diversity for improved link quality.

3. The method of claim 1 , wherein the antenna array is a two-dimensional array comprising at least two elements along a first (azimuth) axis and at least two elements along an orthogonal second (elevation) axis, whereby both azimuth and elevation angles of arrival are estimated.

4. The method of claim 1 , further comprising calibrating the RF beacon based on reference RF signals received at each antenna of the array to correct amplitude and phase imbalances.

5. The method of claim 4, wherein the calibration is performed by a trained machine-learning algorithm that learns a relationship between historical received signal strengths and corresponding true signal strengths to provide a more accurate calibrated signal measure.

6. The method of claim 1 , further comprising dynamically adjusting the transmitted RF signal strength of the beacon based on the number of proximate mobile devices to reduce interference and optimize location-measurement accuracy.

7. The method of claim 1 , wherein the step of forwarding comprises transmitting the determined location to a central ticketing and payment system and debiting an appropriate fare from a user account based on duration of travel.

8. The method of claim 1 , further comprising transmitting and receiving wideband linear-frequency-modulated pulses to perform matched-filter range estimation concurrently with angular determination for refined three-dimensional positioning.

9. The method of claim 1 , wherein the antenna array comprises subarrays of four, eight, sixteen, thirty-two, sixty-four, one-hundred-twenty-eight or two-hundred-sixty- four individual elements arranged as groups to enhance beam-forming flexibility.

10. The method of claim 1 , wherein at least two antennas of the array are spaced apart by approximately half a wavelength (0.5 A) of the operating RF frequency.

11. The method of claim 1 , wherein the antenna array is configured to produce a directional beam toward a predefined direction and / or a curtain-like pattern to detect entry and exit of the mobile device into the service area.

12. The method of claim 1 , wherein the RF signal comprises one or more of RFID, NFC, GPS, Wi-Fi, UWB, Bluetooth, and preferably Bluetooth Low Energy in the 2.4 GHz ISM band.

13. A positioning system for performing the method of any one of claims 1 to 12, the system comprising:- a mobile device arranged to broadcast an RF signal upon approaching a service location;- an RF beacon installed at said location and arranged to receive said RF signal via an antenna array for monopulse tracking;- a processing device in communicative connection with the beacon, configured to measure signal strength, determine the location of the mobile device, and forward the location to a central server; and- a central server arranged to compare the forwarded location with a predefined service area for triggering the location-based service.

14. The system of claim 13, wherein the location-based service is a contactless check-in for public transportation, and said predefined service area corresponds to an entrance of a bus, metro, train or taxi.

15. A computer-readable medium comprising program code which, when executed by one or more processors, causes the processors to perform the steps of the method of any one of claims 1 to 12.

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