Patent Application
20230417865
The present disclosure relates to a communication device. Furthermore, the present disclosure relates to a corresponding method of operating a communication device, and to a computer program for carrying out said method.
Ultra-wideband (UWB) communication uses a high signal bandwidth, in particular for transmitting digital data over a wide spectrum of frequency bands with very low power. For example, UWB technology may use the frequency spectrum of 3.1 to 10.6 GHz and may feature a high-frequency bandwidth of more than 500 MHz and very short pulse signals, potentially capable of supporting high data rates. The UWB technology enables a high data throughput for communication devices and a high precision for the localization of devices. In particular, UWB technology may be used for so-called ranging operations, i.e., for determining the distance between communicating devices. Therefore, UWB technology may be used to advantage in various applications, such as automotive applications.
In accordance with a first aspect of the present disclosure, a communication device is provided, comprising: a plurality of antennas configured to receive an ultra-wideband signal; a processing unit configured to determine an angle of arrival, AoA, of the ultra-wideband signal, wherein said AoA is based on a phase difference of arrival, PDoA, derived from the ultra-wideband signal; a polarization angle estimation unit configured to estimate a polarization angle of the ultra-wideband signal; wherein the processing unit is further configured to determine the AoA of the ultra-wideband signal using the polarization angle estimated by the polarization angle estimation unit.
In one or more embodiments, the antennas have different polarizations, and the polarization angle estimation unit is configured to estimate the polarization angle by measuring the ratio between the strength of the ultra-wideband signal received at a first one of said antennas and the strength of the ultra-wideband signal received at a second one of said antennas.
In one or more embodiments, the polarization of the first one of said antennas is 0° or substantially 0° and the polarization of the second one of said antennas is different from 0°.
In one or more embodiments, the first one of said antennas is configured to be used for estimating the polarization angle of the ultra-wideband signal and for deriving the PDoA from the ultra-wideband signal, and the second one of said antennas is configured to be used for estimating the polarization angle of the ultra-wideband signal and not for deriving the PDoA from the ultra-wideband signal.
In one or more embodiments, the first one of said antennas and the second one of said antennas are configured to be used for estimating the polarization angle of the ultra-wideband signal and not for deriving the PDoA from the ultra-wideband signal.
In one or more embodiments, one or more third ones of said antennas are configured to be used for deriving the PDoA from the ultra-wideband signal and not for estimating the polarization angle of the ultra-wideband signal.
In one or more embodiments, the processing unit is configured to use the polarization angle estimated by the polarization angle estimation unit to select a predetermined mapping between PDoAs and AoAs, and to use the selected predetermined mapping to determine the AoA of the ultra-wideband signal.
In one or more embodiments, the polarization angle estimation unit is configured to estimate the polarization angle by applying a pre-calibrated function on a gain ratio and different PDoAs obtained through different ones of said antennas.
In one or more embodiments, the function is a machine learning algorithm trained for a given antenna design.
In one or more embodiments, a localization system comprises a communication device of the kind set forth.
In accordance with a second aspect of the present disclosure, a method of operating a communication device is conceived, the communication device comprising a plurality of antennas, a processing unit and a polarization angle estimation unit, the method comprising: receiving, by the antennas, an ultra-wideband signal; estimating, by the polarization angle estimation unit, a polarization angle of the ultra-wideband signal; determining, by the processing unit, an angle of arrival, AoA, of the ultra-wideband signal using a phase difference of arrival, PDoA, derived from the ultra-wideband signal and the polarization angle estimated by the polarization angle estimation unit.
In one or more embodiments, the antennas have different polarizations, and the polarization angle estimation unit estimates the polarization angle by measuring the ratio between the strength of the ultra-wideband signal received at a first one of said antennas and the strength of the ultra-wideband signal received at a second one of said antennas.
In one or more embodiments, the processing unit uses the polarization angle estimated by the polarization angle estimation unit to select a predetermined mapping between PDoAs and AoAs and uses the selected predetermined mapping to determine the AoA of the ultra-wideband signal.
In one or more embodiments, the polarization angle estimation unit estimates the polarization angle by applying a pre-calibrated function on a gain ratio and different PDoAs obtained through different ones of said antennas.
In accordance with a third aspect of the present disclosure, a computer program is provided, comprising executable instructions which, when executed by a communication device, cause said communication device to carry out a method of the kind set forth.
Embodiments will be described in more detail with reference to the appended drawings.
As mentioned above, UWB communication uses a high signal bandwidth, in particular for transmitting digital data over a wide spectrum of frequency bands with very low power. For example, UWB technology may use the frequency spectrum of 3.1 to 10.6 GHz and may feature a high-frequency bandwidth of more than 500 MHz and very short pulse signals, potentially capable of supporting high data rates. The UWB technology enables a high data throughput for communication devices and a high precision for the localization of devices. In particular, UWB technology may be used for so-called ranging operations, i.e., for determining the distance between 35 communicating devices. Therefore, UWB technology may be used to advantage in various applications, such as automotive applications.
In particular, UWB technology—also referred to as impulse-radio ultra-wideband (IR-UWB)—is an RF communication technology that uses pulses having a short duration for data communication. An important feature of IR-UWB technology is that it can be used for secure and accurate distance measurements between two or more devices. Typical distance measurement methods are the so-called single-sided two-way ranging (SS-TWR) method and the double-sided two-way ranging (DS-TWR) method.
Because UWB technology has an accurate distance measurement capability, it may be used to advantage in access systems in which the position of devices should be determined to enable access to an object. For instance, a vehicle access system may comprise a user's smart device (e.g., key fob) and another smart device (e.g., an anchor embedded in the vehicle). To enable access to the vehicle, the user's smart device must have a predefined range relative to the other smart device. Typically, the user's smart device should be within a predefined number of meters from the other smart device. Therefore, UWB transceivers are typically configured to operate in a ranging mode. In another example, UWB technology may be used for accessing a building or a predefined space within a building.
In the ranging mode of operation, so-called UWB frames (i.e., UWB signals) will typically be exchanged between two devices via at least one antenna on each device, and at least a SS-TWR operation will be carried out (which may also be referred to as a ping-pong operation). In particular, channel impulse responses (CIRs) are estimated on both devices, timestamps will be generated based on the CIRs on both devices, and those timestamps are exchanged. Then, a time of flight (ToF) is calculated based on the timestamps and a range (i.e., a distance) is calculated based on the ToF. Alternatively, a DS-TWR operation may be carried out (which may also be referred to as a ping-pong-ping operation). The angle-of-arrival (AoA) mode of operation is similar to the ranging mode, but it involves at least two antennas on one device. In particular, in the AoA mode of operation, two phase values associated with at least two CIRs are calculated on one device. Then, a phase difference of arrival (PDoA) is calculated based on the two-phase values, and an AoA is calculated based on the PDoA. The AoA mode of operation may facilitate a more accurate determination of the position of an object and may thus complement ranging operations performed in the ranging mode. As used in this description, the ranging mode of operation may therefore be extended to include the AoA mode of operation, in the sense that when a device operates in the ranging mode, it may optionally perform additional operations which are typically performed in the AoA mode of operation.
Accordingly, a benefit of using an IR-UWB system is that a channel impulse response, as determined by a responder using a received UWB frame, can be used to determine not only the distance (i.e., the range) to an initiator but also the angle of arrival of the incoming radio-frequency (RF) wave from the initiator, which allows the system to use both range and angle for precise localization. It is noted that the format of UWB frames is defined in the technical standard IEEE 802.15.4z-2020 (IEEE Standard for Low-Rate Wireless Networks, Amendment 1: Enhanced Ultra Wideband (UWB) Physical Layers (PHYs) and Associated Ranging Techniques). AoA estimation an important feature of UWB-based communication systems. For instance, AoA estimates can be used for direction finding, localization, and remote control of smart gadgets.
AoAhorizontal=ƒ(pdoa1,pdoa2) (Eq. 1)
AoAvertical=g(pdoa1,pdoa2) (Eq. 2)
Equations (1) and (2) simplify the physical RF measurement system by using only pdoa1 and pdoa2 as input for the AoA estimation algorithm or mapping method. In a real-world scenario, however, it may not be possible to accurately determine the angle of arrival of the incoming signal 108 using only these PDoA values, because the incoming signal 108 may have different polarization angles. This variance in polarization angles may result in significant errors in the estimation of the angle of arrival.
Now discussed are a communication device and a corresponding method of operating a communication device, which facilitate increasing the accuracy of angle of arrival (AoA) estimations.
It is noted that the polarization angle of a signal, or in other words the polarization of an electromagnetic wave, is defined by the direction of the electric field vector. For a linear polarization the field vector moves along a line which has a defined angle in space. For example, a vertical polarization means that the electric field vector is vertically aligned, i.e., points up or down at an angle of 90°, and a horizontal polarization means that the electric field vector is horizontally aligned, i.e., points left or right at an angle of 0°. The skilled person will appreciate that the electric field vector can also be aligned at any arbitrary angle, for example 45°. Furthermore, it is noted that most antennas are built to receive signals with a given polarization. For instance, a simple dipole antenna which is vertically aligned receives vertically polarized EM waves much better than horizontally polarized waves. In this case, a better reception means that the antenna gain for this type of polarization is higher, or in other words that the power received by the antenna relative to the power of the incident wave is higher. Consequently, if two dipole antennas are used, one of which is horizontally oriented and the other vertically oriented, the polarization angle of an incoming electromagnetic wave can be estimated by looking at the ratio of the powers output by the two antennas. This is possible because for instance a linearly polarized EM wave with a polarization angle of 45° can be represented as two superpositioned electromagnetic waves with polarization angles of 0° and 90°, respectively, and magnitude 1/sqrt (2). Furthermore, it is noted that the same principles extend to circular polarization, which includes the case that the two field vectors that are summed are not in phase.
In one or more embodiments, the antennas have different polarizations, and the polarization angle estimation unit is configured to estimate the polarization angle by measuring the ratio between the strength of the ultra-wideband signal received at a first one of said antennas and the strength of the ultra-wideband signal received at a second one of said antennas. In this way, the estimation of the polarization angle of the incoming ultra-wideband signal is facilitated. In a practical implementation, the polarization of the first one of said antennas is 0° or substantially 0° and the polarization of the second one of said antennas is different from 0°. It is noted that an optimal polarization of the second one of said antennas is 90°.
In one or more embodiments, the first one of said antennas is used for estimating the polarization angle of the ultra-wideband signal and for deriving the PDoA from the ultra-wideband signal, and the second one of said antennas is used for estimating the polarization angle of the ultra-wideband signal and is not used for deriving the PDoA from the ultra-wideband signal. Since one of the antennas is configured to be used for two purposes, the hardware cost of the implementation may be reduced. Alternatively, the first one of said antennas and the second one of said antennas are configured to be used for estimating the polarization angle of the ultra-wideband signal and not for deriving the PDoA from the ultra-wideband signal. Since both antennas are configured to be used only for estimating the polarization angle, the accuracy of this estimation may be increased. Furthermore, in one or more embodiments, one or more third ones of said antennas are configured to be used for deriving the PDoA from the ultra-wideband signal and not for estimating the polarization angle of the ultra-wideband signal. Since these antennas are configured to be used only for deriving the PDoA from the ultra-wideband signal, the PDoA derivation and consequently the AoA estimation may be optimized more easily.
In one or more embodiments, the processing unit is configured to use the polarization angle estimated by the polarization angle estimation unit to select a predetermined mapping between PDoAs and AoAs, and to use the selected predetermined mapping to determine the AoA of the ultra-wideband signal. This results in a practical implementation, in which the estimated polarization angle of the incoming ultra-wideband signal is taken into account for determining its angle of arrival. Furthermore, in one or more embodiments, the polarization angle estimation unit is configured to estimate the polarization angle by applying a pre-calibrated function on a gain ratio and different PDoAs obtained through different ones of said antennas. In this way, the estimation of the polarization angle of the incoming ultra-wideband signal is facilitated, in particular for antenna designs which cannot easily be optimized. In a practical implementation, the function is a machine learning algorithm trained for a given antenna design. The skilled person will appreciate that the presently disclosed communication device may be used to advantage in a localization system or in any other system in which AoA estimations are performed.
As mentioned above, there are different types of polarization directions of electromagnetic waves. A linear polarization direction means that the electric field vector moves along a line with a constant angle in space. A circular polarization direction means that the electric field vector rotates in a circle over time. This can be achieved by adding two linearly polarized waves with equal magnitude, where one is out of phase with the other. Furthermore, an elliptic polarization refers to a combination of two linearly polarized waves with different magnitudes and phases. It is noted that most antennas are designed to receive waves having a specific one of these polarization types and suppress others. A linearly polarized antenna is built to receive a linearly polarized wave with a given angle relative to the antenna, for example to receive vertically polarized waves and suppress horizontally polarized waves.
Furthermore, it is noted that these angles are relative to the coordinate system of the antenna.
P
ant1
=P
sig*|cos(α)| (Eq. 3)
P
ant4
=P
sig*|sin(α)| (Eq. 4)
Equations (3) and (4) show the simplified signal strength behavior for ideal, linearly polarized, and omnidirectional antennas with the same gain. In case of a nearly ideal antenna design the polarization, angle may be estimated as shown in equation (5). If the gain of the antennas (i.e., the first antenna 702 and the fourth antenna 708) is not the same, a power scaling ratio may be applied. However, in order to simplify the design identical antenna elements with a smooth radiation pattern may be used.
After the polarization has been calculated by comparing the strength of the signals received at the vertically and horizontally polarized antennas, the AoA may be estimated by using the PDoAs of the 0° polarized antennas and the knowledge of the polarization. In other words, based on the polarization angle estimate one may select the corresponding PDoA to AoA calibration mapping that yields the best AoA estimation performance. Which algorithm is used for the AoA estimation (e.g., a machine learning algorithm, a look-up table approach, or a simple higher order equation) is system- and use case-dependent and may vary depending on the available computational power, the amount of time available for AoA computation, and other factors and system requirements. It is noted that a vertically polarized antenna is an antenna which is 90° linearly polarized, and a horizontally polarized antenna is an antenna which is 0° linearly polarized.
In order to cope with less optimized antenna designs, the polarization angle of the incoming signal may be estimated in another manner. In real world scenarios optimizing the antenna design may be difficult, due to space and cost constraints. In such scenarios the gain ratio between the antennas' polarization used for the polarization estimation may be also angle-dependent; additionally, the antenna polarization might not be ideally 0° and 90°. In that case, the polarization angle may be a function of the measured PDoAs, as shown in equation (6).
α=ƒ(pdoa1,pdoa2,kgain) (Eq. 6)
By making a calibration measurement over multiple polarizations and signal polarizations, the function shown in equation (6) may be approximated and subsequently used for polarization estimation, also under non-ideal conditions. The skilled person will appreciate that the way in which the function shown in equation 6 is created may again be dependent on the antenna design and system requirements. A common approach for finding a solution for equation 6 is to use a machine learning (ML) algorithm that is trained for the given antenna design. Another solution may be to search for the minimum difference between the calibration data and the measured data, which is able to indicate the polarization angle with the calibration solution (e.g., a least squares estimator).
The systems and methods described herein may at least partially be embodied by a computer program or a plurality of computer programs, which may exist in a variety of forms both active and inactive in a single computer system or across multiple computer systems. For example, they may exist as software program(s) comprised of program instructions in source code, object code, executable code or other formats for performing some of the steps. Any of the above may be embodied on a computer-readable medium, which may include storage devices and signals, in compressed or uncompressed form.
As used herein, the term “computer” refers to any electronic device comprising a processor, such as a general-purpose central processing unit (CPU), a specific-purpose processor or a microcontroller. A computer is capable of receiving data (an input), of performing a sequence of predetermined operations thereupon, and of producing thereby a result in the form of information or signals (an output). Depending on the context, the term “computer” will mean either a processor in particular or more generally a processor in association with an assemblage of interrelated elements contained within a single case or housing.
The term “processor” or “processing unit” refers to a data processing circuit that may be a microprocessor, a co-processor, a microcontroller, a microcomputer, a central processing unit, a field programmable gate array (FPGA), a programmable logic circuit, and/or any circuit that manipulates signals (analog or digital) based on operational instructions that are stored in a memory. The term “memory” refers to a storage circuit or multiple storage circuits such as read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, Flash memory, cache memory, and/or any circuit that stores digital information.
As used herein, a “computer-readable medium” or “storage medium” may be any means that can contain, store, communicate, propagate, or transport a computer program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium may be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium.
It is noted that the embodiments above have been described with reference to different subject-matters. In particular, some embodiments may have been described with reference to method-type claims whereas other embodiments may have been described with reference to apparatus-type claims. However, a person skilled in the art will gather from the above that, unless otherwise indicated, in addition to any combination of features belonging to one type of subject-matter also any combination of features relating to different subject-matters, in particular a combination of features of the method-type claims and features of the apparatus-type claims, is considered to be disclosed with this document.
Furthermore, it is noted that the drawings are schematic. In different drawings, similar or identical elements are provided with the same reference signs. Furthermore, it is noted that in an effort to provide a concise description of the illustrative embodiments, implementation details which fall into the customary practice of the skilled person may not have been described. It should be appreciated that in the development of any such implementation, as in any engineering or design project, numerous implementation-specific decisions must be made in order to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill.
Finally, it is noted that the skilled person will be able to design many alternative embodiments without departing from the scope of the appended claims. In the claims, any reference sign placed between parentheses shall not be construed as limiting the claim. The word “comprise(s)” or “comprising” does not exclude the presence of elements or steps other than those listed in a claim. The word “a” or “an” preceding an element does not exclude the presence of a plurality of such elements. Measures recited in the claims may be implemented by means of hardware comprising several distinct elements and/or by means of a suitably programmed processor. In a device claim enumerating several means, several of these means may be embodied by one and the same item of hardware. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.
| Number | Date | Country | Kind |
|---|---|---|---|
| 22174785.0 | May 2022 | EP | regional |
