Method and apparatus for performing motion compensation signal processing

Abstract

A method for performing motion compensation signal processing is described. The method includes receiving, at a receiver, a first signal from a remote source in a first direction; providing a first local signal; determining a movement of the receiver using the first data and not using data derived from the accelerometer; providing a correlation signal by correlating the local signal with the received signal; motion compensation is provided for at least one of the local signal, the received signal, and the correlation signal based on the determined movement in the first direction to provide a preferential gain for the signal received along the first direction, and the received first signal is processed based on the correlation. A system for performing motion compensation signal processing is also described.

Description

Technical Field

[0001] Embodiments of the present invention relate generally to radio receivers, and more particularly to a method and apparatus for performing motion compensated signal processing within a radio receiver. Background Art

[0002] Positioning signal receivers, such as receivers for global satellite navigation systems (GNSS) signals, have become ubiquitous in mobile devices. GNSS receivers (e.g., receivers for GPS, GLONASS, GALILEO, DEIBOU, etc. satellite signals or a combination thereof) receive signals from satellites, process the received signals, and determine the position of the receiver based on the information contained in the received signals. The typical accuracy of consumer receivers without the assistance of an inertial measurement unit (IMU) ranges from 5m to 50m. In order to provide inertial navigation in a typical mobile device, an IMU typically includes a magnetometer, a gyroscope, and an accelerometer, i.e., a traditional IMU sensor. The signals from these three sensors (typically, MEMS-based sensors) are used to enhance the positioning calculations of the GNSS receiver, so that the receiver accuracy can be improved to about 20cm. However, this additional accuracy brings huge costs and additional computational complexity to the IMU sensor.

[0003] In other forms of radio receivers, it may be advantageous for signal reception to be aware of the motion of the receiver so that the received signal can be motion compensated, i.e., frequency and / or phase errors caused by the receiver motion are removed from the signal correlation process. Compensating for receiver motion improves receiver signal reception and / or reduces the cost of receiver components.

[0004] Therefore, there is a need for a method and apparatus for performing motion compensated signal processing without using fully equipped conventional IMU data from a conventional IMU sensor. Summary of the invention

[0005] Embodiments of the present invention are generally directed to methods and apparatus for performing motion compensated signal processing as shown in the figures and / or described in connection with at least one of the accompanying figures.

[0006] These and other features and advantages of the present disclosure may be understood from a review of the following detailed description of the disclosure taken in conjunction with the accompanying drawings, wherein like reference numerals refer to like parts throughout.

[0007] According to a first aspect of the present invention, a method for performing motion compensated signal processing is provided, the method comprising: receiving, at a receiver, a first signal from a remote source in a first direction; providing a first local signal; determining movement of the receiver using first data and not using data derived from an accelerometer; providing a correlated signal by correlating the local signal with the received signal; providing motion compensation for at least one of the local signal, the received signal and the correlated signal based on the movement determined in the first direction so as to provide priority gain for the signal received along the first direction, and processing the received first signal based on the correlation.

[0008] The inventors have appreciated that a reduction in computational and sensor component requirements can be achieved while achieving significant improvements in signal reception and positioning by compensating for phase and frequency effects of receiver motion without using an accelerometer, as has been conventionally employed in IMU-enhanced navigation and inertial motion sensing. Determining movement without using data derived from an accelerometer may alternatively be defined as doing so without using data from an accelerometer, that is, without using any data from an accelerometer that is arranged and / or configured to directly and / or indirectly monitor the motion of the receiver.

[0009] In the context of the present disclosure, the determined movement of the receiver may be considered as movement data, or data representing or including a model or estimate of the movement of the receiver. For example, this may be obtained by representing a platform, structure, device or housing including the receiver. The data may, for example, represent the movement of a vehicle including the receiver. The determining step may be performed in some embodiments to determine a motion model of an antenna coupled to the radio receiver without using conventional IMU data.

[0010] It will be appreciated that the provision of the first local signal and the provision of the associated signal may comprise generating one or each of said signals.

[0011] Motion compensation can be applied to the received signal, the local signal, or a combination thereof before the signal is correlated. After correlation, motion compensation can also be applied to the correlated signal. By providing motion compensation in a first direction (which typically extends between the receiver and the remote source), preferential gain for signals received along that direction can be achieved. Therefore, the line-of-sight signal between the receiver and the remote source will receive gain preferentially over reflected signals received in different directions. In addition to being generally beneficial to signal processing, motion compensated correlation is particularly advantageous when applied to a positioning system or as part of a positioning method. In a GNSS receiver, for example, the aforementioned preferential gain can result in a significant improvement in the accuracy of calculations based on the received signal because non-line-of-sight signals (e.g., reflected signals) are significantly suppressed. The highest correlation can be achieved for a signal even if the absolute power of the signal is less than that of the non-line-of-sight signal.

[0012] The received signal may include any known or unknown transmission information pattern, digital or analog, which may be found in the broadcast signal by a cross-correlation process using a local copy of the same pattern. The received signal may be encoded with a clipping code that may be used for ranging. Examples of such received signals include GPS signals, which include Gold Codes encoded within the radio transmission. Another example is the Extended Training Sequences used in GSM cellular transmissions.

[0013] Regular phase variations in the received signal caused by changes in the line-of-sight path between the receiver and the remote source are viewed as a nuisance that exacerbates signal processing overhead and degrades localization accuracy. The counter-intuitive approach of determining the receiver motion without IMU data can actually exploit these phase variations to improve identification of line-of-sight signals from remote sources while minimizing computer and resource requirements.

[0014] The motion compensation unit can provide motion compensation to the local signal to make it more closely match the received signal. In another arrangement, motion compensation can be applied to the received signal to reduce the effect of the motion of the receiver on the received signal. Similar results can be achieved by providing partial motion compensation to both the local signal and the received signal. These techniques allow relative motion compensation to be applied between the local signal and the received signal. In some embodiments, motion compensation can be performed in parallel with correlation. Motion compensation can also be applied directly to the correlation signal.

[0015] In practice, the received signal may be processed as a complex signal, comprising in-phase and quadrature components. The local signal may be similarly complex. The correlation unit may be arranged to provide a correlation signal, which may also be a complex signal and which may be used as a measure of the correlation between these complex signals.

[0016] High accuracy can be achieved by providing motion compensation for at least one of the local signal and the received signal based on the measured or assumed movement in the first direction. In practice, when applied to GNSS signals, for example, the local signal and the received signal can be encoded using a periodically repeated code. For example, for the GPS L1 C / A code, the local signal and the received signal can include 1023 pseudo-random digital chips. The local signal and the received signal can be analog waveforms that can be digitized to provide values ​​at the radio sampling rate, which means that there may be millions of values ​​in a 1ms time period. The correlation between the local signal digital value and the received signal digital value can be calculated, first correcting any set of values ​​using the motion compensation vector within the relevant time period. These data points can then be summed over the time period. In practice, this can produce accurate results because it works at the radio sampling frequency, although it may be computationally intensive.

[0017] Lower accuracy can be achieved by providing motion compensation of the correlated signals. In the above example, when applied to the GPS L1 C / A code, correlation can be performed independently on each of the ~1000 pseudo-random digital chips to produce ~1000 complex correlator signal outputs. The motion compensation vector can then be applied to these ~1000 correlated signal components. Finally, the motion compensated correlated signals can be summed to produce a measure of correlation. Therefore, motion compensation of the correlated signals can produce an approximation of the results that can be achieved by motion compensation of the local signal and the received signal. However, for some applications, the loss of accuracy can be negligible and can be acceptable because it can reduce the computational load.

[0018] In some embodiments, the motion compensation process includes generating a plurality of phasor sequences, wherein each phasor sequence forms a hypothesis including a sequence of signal phase offsets representing the motion of the receiver or its antenna. A phasor is a vector quantity representing amplitude and phase. The method may then include: correlating at least one local signal with at least one received signal to produce at least one correlation result; and compensating a phase or multiple phases of at least one of the local signal, at least one received signal, or at least one correlated signal based on a plurality of hypotheses about the determined motion model to generate a plurality of phase-compensated correlation results. Typically, the plurality of phases corresponds to a sequence of phase corrections, wherein one of the sequence is preferably applied to each of a plurality of samples of the signal. The method may then include determining a preferred hypothesis among the plurality of hypotheses, which may be understood as a hypothesis that optimizes at least one correlation result of at least one of the phase-compensated correlation results. The method may, for example, include causing a plurality of samples of a received signal received by a receiver during a time period to be correlated. The same signal may be compensated using different multi-estimation phasor sequences to produce correlation results for each different multi-estimation phasor sequence. Each phasor sequence may include a plurality of phasors representing different phases, typically at different defined times during the time period. Multiple imputed phasor sequences may be different because each imputed phasor sequence may be based on a different hypothesis about the evolution of frequency and phase through a defined time during the time period. The correlation results may be used to determine a preferred hypothesis about the evolution of frequency and phase during the time period.

[0019] As noted earlier in this disclosure, a gain provided for a signal received along a first direction may be preferred because it is greater than a gain provided for a signal received in a second direction (which is not a line-of-sight direction from a remote source to a receiver). Typically, the first direction is a line-of-sight direction in this manner. That is, the propagation path for the signal may include only a single direction or vector between the receiver and the transmitter of the signal. However, the first direction may in some cases correspond to a non-line-of-sight direction, i.e., a vector corresponding to a portion of an indirect, or reflected propagation path. In such cases, the propagation path for the signal may preferably be calculated based on geometric data representing the reflective structure. For example, a three-dimensional geometric model may be available that represents the urban structure of a certain geographic area. Knowledge of the existence, location, extent, and orientation of reflective surfaces and structures, or any one or more of these, may be used in methods that utilize signals that are not line-of-sight signals.

[0020] Correlation-based processing may involve improving radio receiver signal reception using phase compensated correlation results. The processing may be performed to improve radio receiver reception, such as enhancing any of the quality, strength, and reliability of the received / processed signal. For example, motion compensated correlation may be used for any one or more of signal identification, interference reduction, and synchronization. In some embodiments, the processing step may be considered as processing the received signal based on motion compensated correlation signals. Alternatively, it may be considered as a correlation result based on motion compensation.

[0021] In some embodiments, the receiver (typically its antenna) is mounted to the vehicle. Additionally or alternatively, the receiver may be mounted in and / or mounted on the vehicle, coupled to the vehicle, contained by the vehicle or be part of the vehicle. Typically, the receiver or receiver component is mounted in such a way that the position and / or orientation of the receiver is fixed or unchanged relative to the vehicle, or its body, main body or chassis, or substantially so. Advantageously, in various embodiments, data is typically available from the vehicle, using which motion can be determined, thereby avoiding the need for any inertial data in some embodiments. The vehicle may be, for example, a car, a bus, a train, an industrial or agricultural vehicle, a ship or an aircraft.

[0022] According to a second aspect of the invention, a method for performing motion compensated signal processing is provided, the method comprising: receiving, at a receiver, a first signal from a remote source in a first direction; providing a first local signal; determining movement of the receiver using first data, wherein the receiver is mounted on a vehicle, and wherein the first data is derived from an output of a sensor arrangement included by the vehicle, the sensor arrangement comprising any one or more of: a vehicle wheel speed sensor, a vehicle steering angle sensor, a vehicle throttle position sensor, and a vehicle brake sensor; providing a correlated signal by correlating the local signal with a received signal; providing motion compensation for at least one of the local signal, the received signal, and the correlated signal based on the movement determined in the first direction so as to provide priority gain for the signal received along the first direction; and processing the received first signal based on the correlation.

[0023] In this way, the method allows motion compensation to be performed by determining movement from sensors and / or components of the vehicle, typically using data commonly available in many vehicle systems. By doing so, the weight and resource efficiency of the motion compensation correlation process is improved.

[0024] Preferably, the determination of movement is performed without using data derived from an accelerometer, as described in relation to the first aspect.Preferably, the sensor arrangement excludes an accelerometer, and preferably the vehicle does not comprise an accelerometer.

[0025] In view of the above, it should be understood that in some embodiments, the method according to the first aspect may involve deriving first data from the output of a sensor arrangement included by the vehicle, the sensor arrangement including any one or more of: a vehicle wheel speed sensor, a vehicle steering angle sensor, a vehicle throttle position sensor, and a vehicle parking sensor.

[0026] Features described hereinafter may be applied to the methods according to the first and second aspects, and correspondingly to the further aspects disclosed herein.

[0027] The aforementioned sensor arrangement may be included by the vehicle and / or by the receiver itself. In some embodiments, the aforementioned vehicle wheel speed sensor may be configured as a rotational motion and / or position sensor. Wheel rotation information may be easily converted into data representing the distance traveled, speed, velocity and acceleration of the vehicle. Typically, a vehicle wheel (typically each wheel of the vehicle) is equipped with a speed sensor suitable for monitoring the rotational speed, e.g. angular velocity, of the wheel. By analyzing speed data from one or each wheel of a vehicle (typically a four-wheeled vehicle), a system such as an electronic control unit (ECU) may calculate the speed, acceleration and wheel slip of the vehicle.

[0028] A steering angle sensor may be understood as a sensor adapted to monitor the angle at which a steering wheel or other control is turned or otherwise adjusted and / or the angle to which one or more vehicle wheels are rotated by steering. Typically, this allows the ECU to calculate the turning radius and / or steering dynamics of the vehicle.

[0029] A vehicle throttle position sensor may advantageously provide information about the position of an accelerometer control or pedal. This may typically be used to determine a desired or controlled level of driver input and / or engine or motor output power.

[0030] Vehicle brake sensors may be arranged to collect data from various sensors, such as brake pedal position sensors and / or wheel speed sensors. This is typically used to calculate braking force, wheel locking and determine the deceleration of the vehicle.

[0031] Any one or more of these sensor systems, or a system that processes data from these sensors (such as the aforementioned ECU), may be used to calculate a motion model representing the movement of the vehicle.

[0032] Typically, vehicles employ a communication network or system that processes data related to vehicle motion in such a way that an estimate or model of motion can be easily calculated from these data. For example, the speed, position, height, orientation, direction of travel, braking, acceleration and change of these vehicles and their rates can be obtained. These data can be obtained directly from data communicated within the network, or indirectly, such as by using some quantitative influences, calculations, estimates, and, for example, by combining multiple data sources to converge to an accurate representation or vehicle movement. In some embodiments, therefore, the first data is obtained from the vehicle's communication system. Alternatively, it can also be obtained from a communication device (e.g., a vehicle bus). It should be understood that a vehicle bus refers to a communication network, typically inside a vehicle or provided as part of a vehicle. Typically, such buses are configured to interconnect components of a vehicle. In the context of the present disclosure, a bus can be understood as a device that connects multiple electrical or electronic devices together or couples them communicatively.

[0033] In particular, data from which movement or motion is determined can be obtained from a controller area network (CAN) bus. This can be understood as a vehicle bus standard suitable for allowing one or more microcontrollers and / or devices of a vehicle to communicate. Such communication is typically performed between corresponding applications, and preferably without a host computer. The first data can thus be obtained from at least one electronic control unit ECU of a vehicle including a receiver. The ECU can be part of a vehicle bus, or configured to communicate with or via a vehicle bus. Typically, a vehicle includes a plurality of ECUs corresponding to components or subsystems of the vehicle. Typically, a vehicle includes an engine ECU, which is configured to process data for and / or for controlling functions related to an engine, or, for example, otherwise related to a motor of an electric vehicle. The vehicle may include any one or more ECUs for an advanced driver assistance system (ADAS), a transmission, a braking system, anti-lock braking, cruise control, steering (e.g., electric power steering).

[0034] In addition to (or in lieu of) using data (which is typically digitally represented) relating to components of the vehicle (typically moving components) in order to derive a model of vehicle movement from the movement of those components being monitored or controlled, image data or visual data may also be used to derive the movement model. For example, in some embodiments, the first data is obtained from a visual odometry system of the vehicle, or includes data obtained from a visual odometry system of the vehicle. As is well understood in the art, a visual odometry system typically refers to a device or system configured to determine the position and / or orientation of a vehicle by analyzing camera images (e.g., obtained by a camera mounted or coupled to the vehicle).

[0035] Visual odometry data may advantageously be used to determine receiver motion. If visual odometry data capability is provided in the vehicle, using image data from that system may improve the accuracy of model motion, as inaccuracies that may be introduced, for example, by odometry techniques based on data that may not be a complete representation of all motion, such as monitored wheel rotation or steering control, or wheel slip, will not equally affect the imagery that provides a visual representation of the vehicle's true position, motion, etc.

[0036] For example, when the receiver is not coupled or mounted to a platform that is a vehicle, and therefore no vehicle system data is available to infer the motion, it may be beneficial to calculate the receiver motion based solely on the positioning and / or velocity information acquired by the GNSS. In some embodiments, no motion information is used other than the position or positions obtained by means of a GNSS receiver included by the above-mentioned receiver or a platform including the receiver. However, preferably, the GNSS receiver is used in combination with vehicle data, such as from any arrangement of CAN bus or vehicle component sensors and / or controllers, and optionally further sensors (such as gyro sensors) configured to provide data indicative of the spatial orientation of a vehicle or other platform and / or changes therein.

[0037] Modeling motion using GNSS position and / or velocity information may include using the GNSS data as initial data, for example to initialize a prediction or estimate of receiver movement. After this initialization, the method may include using other subsets of the first data, i.e. any other motion indicative data, to constrain the motion prediction.

[0038] Thus, in some embodiments, the first data comprises positioning information for the receiver obtained using a Global Navigation Satellite System, GNSS, receiver.

[0039] Processing received signals based on correlation results that take into account the receiver motion determined in this way provides a more efficient approach than conventional techniques, whether for communication or positioning purposes. Furthermore, in the event that multiple signals are received, for each received signal, multiple corresponding correlation results can be used in combination to calculate (e.g., by convergence) the best hypothesis having a phasor sequence that best represents the true motion of the platform.

[0040] Preferably, the aforementioned GNSS receiver is the same as the aforementioned receiver, or is comprised by the same device.

[0041] In some embodiments, the first data includes sensor data from a vehicle camera such as a visual or optical imaging device, a lidar, a radar, a camera, and the like. Such sensors may be arranged to communicate with a device such as a CAN bus, or may contribute to the first data without being connected, and may provide data for enabling or facilitating determination of the current posture of the vehicle.

[0042] In some embodiments, the result of the correlation itself is used to provide feedback for improving the motion modeling based on which the ongoing motion compensation correlation is based. In some cases, the method also includes generating movement estimation information representing the movement of the receiver based on the aforementioned correlation. The movement estimation information can be understood as being related to the determined movement, as noted above, it can be considered as an estimate of the movement, or as a movement model or a motion model. This information can also be referred to as movement model adjustment information, or movement model correction information, or movement model update information. The movement represented by the movement estimation information can be the aforementioned movement that has been determined, including the aforementioned movement that has been determined, or included in the aforementioned movement that has been determined. For example, it can include the determined movement, or a part thereof (such as the latter part), and the movement that continues therefrom. The correlation result can indicate the true receiver rate, and can, for example, converge to an assumption representing the true vehicle rate. This information is therefore useful for the determination of movement, and can, for example, be used to constrain the calculation or prediction of movement for continued motion compensation processing.

[0043] The method may therefore include determining the movement of the receiver based on the generated movement estimate information. The determination is preferably performed in the same manner as the previously described determination of movement, i.e. using the first data, and / or without using data derived from the accelerometer. Typically, the determined movement is a receiver or vehicle movement, part or all of which occurs later in time than part or all of the previously determined movement. Preferably, determining the movement of the receiver based on the generated movement estimate information includes updating the motion model using a motion estimate associated with a preferred hypothesis. In other words, the method may include using the correlation results to generate feedback information for adjusting, updating or correcting the determination of the movement. This may accordingly improve the accuracy of the movement determination, thereby improving motion compensation correlation and signal processing.

[0044] As suggested earlier in this disclosure, motion compensation can be provided by generating a plurality of phasor sequences, each phasor sequence corresponding to a hypothesis including a set of one or more signal phase offsets representing movement of the receiver, and correlating at least one local signal with at least one received signal to produce at least one correlation result. The method can accordingly include compensating the phase of at least one of the local signal, at least one received signal, or at least one correlation result based on a plurality of hypotheses about the movement of the receiver to generate a plurality of phase compensated correlation results. In some embodiments, the hypothesis can be considered to be a hypothesis about the determined movement of the receiver, or a hypothesis of a motion model determined therefor, since determining the motion typically includes generating an estimate or model of the motion. A preferred hypothesis among the plurality of hypotheses can then be identified or determined. The preferred hypothesis can be one of the plurality of hypotheses that optimizes at least one of the phase compensated correlation results for at least one of the correlation results.

[0045] The generated movement estimate information may thus include a motion estimate based on or associated with a preferred hypothesis. The movement estimate information may thus include data indicating the movement of the receiver with improved accuracy. Thus, typically for one or more subsequent time periods, the determination of movement may involve updating, modifying or generating an existing or predetermined estimate or model of the movement of the receiver as described above based on the motion estimate. In particular, the determination of movement may include generating or updating a motion model representing the movement of the receiver using the motion estimate.

[0046] Preferably, the determination of the movement of the receiver is performed without using data derived from a magnetometer. Preferably, the determination of the movement is performed without using data derived from an inertial measurement unit, IMU. It should be understood that systems typically adapted to monitor movement by means of accelerometers monitor movement in particular by means of an inertial measurement unit, and that the method provides the advantage of eliminating the need for such components. Preferably, the determination of the movement of the receiver is performed without using data derived from a gyroscopic sensor. In any of the foregoing embodiments, as an alternative or in addition to performing a determination without data derived from a given type of sensor or unit, the sensor arrangement described earlier in this disclosure and indeed the receiver or any platform or vehicle comprising the sensor arrangement may be understood to exclude the corresponding type of sensor or unit.

[0047] Typically, due to the motion compensated correlation, the method allows the received signal to be processed more efficiently. However, the technology is particularly beneficial for applications in which a metric of interest (such as a receiver position) is to be obtained. In some embodiments, the method may include processing the received first signal based on the correlation to determine a metric of interest associated with the receiver and / or associated with a communication link including the receiver. The metric of interest associated with the receiver can be the position, rate, time or direction of motion of the receiver, such as a physical metric associated with the receiver. The metric of interest associated with the receiver is typically used to determine a tracking or navigation solution for the receiver. The wireless communication system can accordingly be a positioning system or a part of a positioning system.

[0048] The aforementioned communication link may be a cellular telecommunication link, such as a 3G, 4G or 5G communication link. Alternatively or additionally, it may be a Wi-Fi or Bluetooth data communication link. Examples of metrics of interest related to the communication link that may be determined by processing the signal include channel estimation parameters, such as channel state information, frequency selection, quality of service, signal availability, and the quality of the communication channel between the receiver and the remote source of the signal.

[0049] In some embodiments, the metric of interest includes at least one of position, range, speed, velocity, trajectory, altitude, compass heading, step cadence, step length, distance traveled, motion context, position context, output power, calorie count, sensor bias, sensor scale factor, and sensor alignment error. Thus, where the metric of interest is associated with a receiver, it may include any metric that can be determined from a sensor configured to make a measurement from which the position or movement of the receiver or its platform can be determined.

[0050] According to a third aspect of the present invention, a system is provided, comprising: a receiver configured to receive a signal from a remote source in a first direction; a local signal generator configured to provide a local signal; a motion module configured to provide a determined movement of the receiver using first data and not using data derived from an accelerometer; a correlation unit configured to provide a correlation signal by correlating the local signal with a received signal; and a motion compensation unit configured to provide motion compensation for at least one of the local signal, the received signal and the correlation signal based on the determined movement in the first direction so as to provide priority gain for the signal received along the first direction.

[0051] In some embodiments, the system is, or is comprised of, a positioning system. Typically, the system does not include an accelerometer or, in particular, an IMU. Typically, the system is not communicatively coupled to any such sensor configured or arranged to monitor the motion of the receiver or any platform containing it or coupled to it.

[0052] In some embodiments, the system is mounted to or integrated into a vehicle, or at least in data communication with the vehicle. At least the receiver or its antenna may alternatively or additionally be mounted to the system itself. As described above, the vehicle may include systems, components or sensors adapted to provide one or more forms of odometry data, and the motion module may be configured to utilize the first data derived therefrom in order to determine the motion to be compensated.

[0053] In some embodiments, the vehicle and / or system includes a sensor arrangement including any one or more of the following: a vehicle wheel speed sensor, a vehicle steering angle sensor, a vehicle throttle position sensor, and a vehicle brake sensor. The first data may be derived from the output of the sensor arrangement. For example, the system may be configured to receive the first data, or may be configured to receive one or more signals output by the central arrangement, and may include a first data module configured to derive the first data therefrom.

[0054] Typically, the first data are obtained from a communication system of the vehicle (eg a CAN bus).

[0055] Additionally or alternatively, the first data may be obtained from a visual odometry system of the vehicle.

[0056] According to a fourth aspect of the invention, there is provided a computer program product comprising executable instructions which, when executed by a processor (e.g., such as a processor in a positioning system, typically a positioning system of a vehicle or a positioning system included by a vehicle), cause the processor to perform steps comprising: receiving a first signal from a remote source in a first direction at a receiver; providing a first local signal; determining the movement of the receiver using first data and not using data derived from an accelerometer; providing a correlated signal by correlating the local signal with the received signal; providing motion compensation for at least one of the local signal, the received signal and the correlated signal based on the movement determined in the first direction so as to provide priority gain for the signal received along the first direction; and processing the received first signal based on the correlation.

[0057] As hinted above, a method and system may be provided for performing motion compensated signal processing without relying on accelerometer data, such as conventional IMU data, for example.

[0058] Therefore, a fifth aspect of the present invention provides a method for performing motion compensated signal processing, comprising: determining a motion model of an antenna coupled to a radio receiver without using conventional IMU data; generating a plurality of phasor sequences, wherein each phasor sequence forms a hypothesis including a signal phase offset, which signal phase offset is typically a sequence of phase offsets representing the motion of the antenna; correlating at least one local signal with at least one received signal to produce at least one correlation result; compensating the phase of at least one of the local signal, at least one received signal, or at least one correlated signal based on a plurality of hypotheses about the determined motion model to generate a plurality of phase-compensated correlation results; determining a preferred hypothesis of at least one correlation result that optimizes at least one of the phase-compensated correlation results among the plurality of hypotheses; updating the motion model using a motion estimate associated with the preferred hypothesis; and improving radio receiver signal reception using the phase-compensated correlation results.

[0059] According to a sixth aspect of the present invention, there is provided an apparatus for performing signal correlation, typically within a positioning system, the apparatus comprising at least one processor and at least one non-transitory computer-readable medium for storing instructions, which instructions, when executed by the at least one processor, cause the apparatus to perform operations including: determining a motion model of an antenna coupled to a radio receiver without using conventional IMU data; generating a plurality of phasor sequences, wherein each phasor sequence forms a hypothesis comprising a signal phase offset or a sequence of signal phase offsets representing the motion of the antenna; correlating at least one local signal with at least one received signal to produce at least one correlation result; compensating the phase of at least one of the local signal, at least one received signal, or at least one correlated signal based on a plurality of hypotheses about the determined motion model to generate a plurality of phase-compensated correlation results; determining a preferred hypothesis of at least one correlation result that optimizes at least one of the phase-compensated correlation results among the plurality of hypotheses; updating the motion model using a motion estimate associated with the preferred hypothesis; and improving radio receiver signal reception using the phase-compensated correlation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order that the above-mentioned features of the present invention can be understood in detail, a specific description of the present invention can be obtained by reference to embodiments, some of which are shown in the attached drawings. However, it should be noted that the attached drawings only illustrate typical embodiments of the present invention and therefore should not be considered as limiting the scope thereof, because the present invention may admit of other equally effective embodiments.

[0061] Figure 1 depicts a functional block diagram of a radio signal receiver installed in a vehicle according to at least one embodiment of the present invention;

[0062] Figure 2 is programmed to act as a Figure 1 A block diagram of a computing device of a signal processor of a receiver; and

[0063] Figure 3 is a flow chart of a method of operation of a computing device when executing signal processing software according to at least one embodiment of the present invention. DETAILED DESCRIPTION

[0064] Embodiments of the present invention include devices and methods for performing motion compensated signal processing for radio signal receivers. Such receivers include positioning systems (e.g., GNSS receivers) and / or communication receivers (e.g., WiFi, cellular, Bluetooth communication receivers). In one exemplary embodiment, improved positioning accuracy is provided without relying on an IMU. In another exemplary embodiment, improved positioning accuracy is provided using only IMU data from a gyroscope. Compared to conventional IMUs (e.g., magnetometers, accelerometers, and gyroscopes), such positioning systems simplify the calculations required to improve positioning accuracy. In addition, by not using an IMU or using a simplified IMU, embodiments of the present invention significantly reduce the bill of materials (BOM) for a radio receiver.

[0065] Satellite-based positioning systems and communications receivers utilize coded digital signals that include deterministic digital codes to facilitate signal acquisition, such as Gold codes. Such digital codes are determined by the receiver and repeatedly broadcast by the transmitter to enable the receiver to acquire and process the transmitted signal. Using such deterministic codes in conjunction with an accurate motion model of the receiver, embodiments of the present invention are useful for enabling a receiver to improve its position calculation accuracy and / or signal reception without using conventional IMU data from a full complement of IMU sensors. The technique of using receiver motion compensated signal processing to improve radio signal reception is known as SUPERCORRELATION TM, and described in the following documents: commonly assigned U.S. Patent 9,780,829, issued on October 3, 2017; U.S. Patent 10,321,430, issued on June 11, 2019; U.S. Patent 10,816,672, issued on October 27, 2020; U.S. Patent Publication 2020 / 0264317, published on August 20, 2020; and U.S. Patent Publication 2020 / 0319347, published on October 8, 2020, which are hereby incorporated by reference in their entirety. The motion model is typically derived using IMU data; however, in an embodiment of the present invention, the motion model is derived using only gyroscope data, controller area network (CAN) bus data, visual odometry data, or a combination of data from any of these motion data sources. In one embodiment, the receiver has no motion information other than the position from the GNSS receiver. And, by SUPERCORRELATION TM The motion information determined by the technique is provided as feedback to the motion module to correct and / or update the motion model.

[0066] In an embodiment, the radio receiver is embedded in a mobile platform, such as, for example but not limited to, a car, a motorcycle, an airplane, a helicopter, a drone, a bicycle, a person (e.g., a person carrying a smartphone, a tablet, a computer, an Internet of Things (IoT) device), and the like. In a specific embodiment, the platform may be a vehicle. In an embodiment, the CAN bus data of the vehicle may be used to determine the CAN bus data used to generate the SUPERCORRELATION TM The initialization parameters of the motion module of the motion model used in the technology. The initialization parameters include the downward direction as a reference direction and the vehicle speed and orientation. The vehicle's CAN bus carries data from all electronic control units (ECUs) and sensors located on the vehicle. Therefore, data such as speed, acceleration, steering input, brake input, throttle input, etc. can be easily used to generate a motion model for the vehicle. If a gyroscope is available, the CAN bus data can be used to generate drift compensation for the gyroscope. In addition, other sensor data such as from vehicle lidar, radar, camera and the like (which may or may not be available from the CAN bus) can also be used to determine the current attitude of the vehicle.

[0067] In operation, at least one received signal is correlated with at least one locally generated signal to produce at least one correlation result. As described in detail below, embodiments of the present invention use motion information to motion compensate the correlation result to enable the receiver to improve signal processing. Embodiments of the present invention enable motion compensated signal processing to be performed without using traditional IMU data; therefore, resulting in a less complex and lower cost radio receiver.

[0068] Figure 1 A block diagram of a radio receiver 100 installed in a vehicle 102 is depicted in accordance with at least one embodiment of the present invention. In an exemplary embodiment, the radio receiver is a GNSS receiver. The GNSS receiver 100 is coupled to a vehicle ECU 104 via a CAN bus 106. The CAN bus 106 facilitates communication of ECU and sensor data throughout the vehicle using a standard communication protocol (ISO 11898-1, -2, -3). The receiver 100 uses the CAN bus data to derive motion information (also referred to as a motion model) about the vehicle's motion. As the vehicle moves, the receiver 100 receives signals from remotely located transmitters (e.g., GNSS satellites 108 arranged in a satellite constellation in Earth orbit).

[0069] In an exemplary embodiment, receiver 100 includes antenna 110, front end 112, GNSS signal processor 114, motion compensation processor 116, and motion module 118. In vehicle 102, receiver 100 and antenna 110 are an integral unit, where antenna 110 moves with vehicle 102. SUPERCORRELATION TM The technique operates based on determining the motion component of the signal receiving antenna in the direction of the source of the received signal. Any reference to motion herein refers to the motion of the antenna 110. In most scenarios, the motion of the vehicle 102 is the same as the motion of the antenna 110, and therefore, the following description assumes that the motion of the vehicle 102 and the antenna 110 are the same.

[0070] The receiver front end 112 down-converts, filters and samples (digitizes) the received signal in a manner known to those skilled in the art. The output of the receiver front end 112 is a digital signal containing data. The data of interest for performing motion compensation is a deterministic code, such as a Gold code, which is used by a GNSS receiver to synchronize transmissions to the GNSS receiver 100.

[0071] The GNSS signal processor 114 correlates the received code from each satellite with the locally generated code to produce a correlation result. The correlation result is processed as is known in the art to generate position information 126, which is used to determine a pseudorange for each satellite, and the pseudoranges are processed to calculate the receiver position. The motion compensation processor 116 performs SUPERCORRELATION TM Processing is performed to provide a signal (a phasor sequence) to phase adjust the correlation result so that the coherent integration period is extended, for example to one or more seconds. A phasor sequence is a time sequence of phase offsets, where each phasor in the sequence adjusts the phase of a signal sample. The adjustment can be performed by adjusting the phase of each sample of a received signal, a locally generated signal, or the correlation result itself. The least computationally intensive adjustment process adjusts the phase of the correlation result.

[0072] The motion module 118 generates vehicle motion information used by the motion compensation processor 116 to generate a phasor sequence that is used for motion compensation correlation results. The phasor sequence includes a phase offset sequence over time, for example, across the received signal to compensate for phase changes that occur over time due to the movement of the vehicle. In one embodiment, the motion module 118 uses CAN bus data 124 to generate motion information for the motion compensation processor 116. In one embodiment, the motion information may include a prediction of the vehicle's speed and heading. In an alternative embodiment, the motion module 118 may include an optional gyroscope 122 to provide vehicle orientation information for the motion model. The motion compensation processor 116 provides motion estimation correction information to the motion module 118 along the path 120. In this way, the motion compensation processor 116 provides correction feedback to the motion module 118.

[0073] Figure 2 Describes a method of programming a Figure 1 1. Block diagram of a computing device for operating a motion compensation processor 116. The motion compensation processor 116 includes at least one processor 200, support circuits 202, and memory 204. The at least one processor 200 may be any form of processor or combination of processors, including but not limited to a central processing unit, a microprocessor, a microcontroller, a field programmable gate array, a graphics processing unit, a digital signal processor, and the like. The support circuits 202 may include well-known circuits and devices that facilitate the functions of the processor. The support circuits 202 may include one or more of a power supply, a clock circuit, an analog-to-digital converter, a communication circuit, a cache, a display, and / or the like, or a combination thereof. The support circuits 202 form an interface between the processor 200 and both the motion module 118 and the GNSS signal processor 114.

[0074] The memory 204 includes one or more forms of non-transitory computer readable media, including one or more of read-only memory or random access memory or any combination thereof. The memory 204 stores software and data, including, for example, signal processing software 206 and data 208. The data 208 includes vehicle motion 210, vehicle position 212, phasor sequence 214, and data for performing SUPERCORRELATION. TM The signal processing software 206 generates signals to facilitate motion compensation correlation when executed by one or more processors 200. The motion compensation correlation process is described in detail below. The signal processing software 206 acts as Figure 1 The motion compensation processor 116 operates.

[0075] Figure 3 2 is a flow chart of a method 300 of operation when the signal processing software 206 is executed by the processor 200 according to at least one embodiment of the present invention. The method 300 may be implemented in software, hardware, or a combination of both (e.g., using Figure 1 motion compensation processor 116).

[0076] Method 300 begins at 302 and proceeds to 304 where a receiver is provided with respect to Figure 1 The described method receives data from at least one remote source (e.g., such as Figure 1 The antenna 108 receives signals from a transmitter of a satellite 108. Each received signal includes a synchronization or acquisition code, such as a Gold code, extracted from a radio frequency (RF) signal received at the antenna. The process of down-converting the RF signal and sampling the digital code is well known in the art.

[0077] At 306, method 300 defines a search space in which the received signal is processed. The search space defines the number of phasor sequence hypotheses to be tested to adjust the correlation result phase until a preferred hypothesis is found. After initialization, the search space can be wide, i.e., there are many hypotheses. As the hypotheses are tested and the correlation results converge to an optimal value, the search space can be narrowed for subsequent correlation result processing. For example, if the motion information is uncertain, the method can define a search space with many phasor sequence hypotheses related to multiple unknown parameters (such as, for example, rate and / or heading). Once the preferred hypothesis is determined, the next received signal is tested with a hypothesis that is close to or the same as the previous preferred hypothesis.

[0078] In one embodiment, information from a CAN bus can be used to constrain the search space. For example, steering input data on the CAN bus can show that the steering wheel has been turned to the right. Therefore, the direction of the vehicle has changed and the method 300 can adjust the search space to the right. In another example, brake pedal data can show that the brake pedal has been stepped on to slow the vehicle. Therefore, the method 300 can change the rate search space to cover the slower speed values ​​at which the vehicle is expected to be slowed. Similarly, visual odometry data can be used to constrain the search space by predicting changes in the vehicle's posture.

[0079] In other embodiments, there may be no additional data available at initialization to assist the GNSS information for the initial position and velocity of the platform. Therefore, the method 300 uses the initial GNSS position / velocity, and thereafter, may use any motion indicative data that can be used to constrain the hypothesis search space. In some embodiments, the method 300 may have no other measured motion information available. In those cases, motion constraints may be applied based on the laws of physics, such as typical vehicle acceleration and deceleration values, vehicle maximum turning radius, knowledge that most vehicles travel in substantially straight lines for short periods of time, and the like.

[0080] At 308, method 300 generates multiple phasor sequence hypotheses associated with motion information. Each phasor sequence hypothesis includes a sequence of signal phase offset estimates that vary with the motion parameters of the receiver. Signal processing correlates the local code encoded in the local signal with the code encoded in the received RF signal. In this example, the phasor sequence hypothesis is used to adjust the carrier phase of the local signal with sub-wavelength accuracy. In some examples, such adjustments or compensations can be performed by adjusting the local oscillator signal, the received signal, or the correlation result to produce a phase-compensated correlation result. The signal and / or the correlation result include complex signal samples having in-phase (I) and quadrature phase (Q) components. The method applies each phase offset in the phasor sequence to the corresponding complex sample in the signal and / or the correlation result. For each received signal, at 310, method 300 correlates the received signal with a set (multiple) of phasor sequence hypotheses containing a time series of phase offset estimates necessary for accurately correlating the received signal.

[0081] Motion estimation is typically an assumption of motion in a direction of interest, such as in the direction of a satellite transmitting a received signal, e.g., along a signal propagation path. At initialization, the direction of interest may be unknown or inaccurately estimated. Therefore, a brute force search technique may be used to identify one or more directions of interest by searching in all directions and correlating signals received in all directions. Comparison of correlation results in all directions enables method 300 to narrow the search space when processing subsequent received signals. There is a very strong correlation between the true values ​​of these assumptions between code repetitions, so that the initial search may be intensive, but subsequent processing only requires tracking parameters in the receiver (as they evolve). Therefore, subsequent compensation is performed on a narrow search space.

[0082] In one embodiment, if a signal from a given satellite was previously received, a set of hypotheses for the newly received signal includes a set of phasor sequence hypotheses that use the expected Doppler and Doppler rate and / or the last Doppler and last Doppler rate used in receiving the previous signal from that particular satellite. The hypothesized values ​​may be centered around the last used value, or additionally offset by a prediction of further offset based on expected receiver motion. At 310, the method 300 correlates each received signal with a set of hypotheses for that signal. The hypothesis is used as a parameter to form a phase compensation phasor to phase compensate the correlation process. Thus, phase compensation may be applied to the received signal, the local frequency source (e.g., an oscillator), or the correlation result value. In addition to searching for receiver motion (which is typically expressed as a receiver rate) to ensure that the correct motion compensation is being applied, the method 300 may also apply hypotheses related to other variables (parameters) such as oscillator frequency to correct for frequency and / or phase offset (if not previously corrected) or signal direction of arrival (DoA). The number of hypotheses may be different for each variable. For example, the search space may contain ten hypotheses for searching for DoA, and have two hypotheses for searching for receiver motion parameters (such as velocity) - i.e., a total of twenty hypotheses (ten times two). The result of the correlation process is a plurality of phase-compensated correlation results - one phase-compensated correlation result value for each hypothesis for each received signal.

[0083] At 312, method 300 processes the correlation results to find the "best" or optimal result for each received signal. In one embodiment, method 300 produces a joint correlation output as a function (e.g., sum) of multiple correlation results produced by all hypotheses and received transmitter signals. The joint correlation output can be a single value or multiple values ​​representing the parameter hypothesis (preferred hypothesis) that provides the best or optimal correlation output. In general, a cost function is applied to each set of correlation values ​​for each received signal to find the best correlation output corresponding to the preferred hypothesis.

[0084] For example, assuming that all other receiver parameters are known except for the vehicle velocity, the method 300 tests the hypotheses using various phasor sequences that compensate for the phase changes due to each velocity hypothesis. The correct phasor sequence hypothesis representing an accurate velocity estimate will produce the highest correlation result magnitude for a given received signal. By processing received signals from different satellites, the correlation results will converge to the hypothesis representing the true vehicle velocity. Performing the correlation process using phase compensation based on true motion information enables the GNSS processor to produce an accurate position without using traditional IMU information.

[0085] At 314, the method 300 feeds back to the motion module the motion information represented by the preferred hypothesis that provides the best output correlation. This feedback is used by the motion module to adjust the motion model to reflect the motion represented by the preferred hypothesis. For example, if the preferred hypothesis indicates that deceleration is occurring, the method 300 may predict that the deceleration will continue and extrapolate the motion model so that the hypothesis is constrained in view of the predicted continued deceleration. This feedback is used to promote the best use of processing resources, i.e., constrain the number of hypotheses tested.

[0086] Method 300 ends at 316 .

[0087] In other embodiments, other test criteria may be used rather than using the maximum magnitude correlation value. For example, method 300 may monitor the progression of correlations as hypotheses are tested and apply a cost function that indicates a cost function indicating the best hypothesis is applied when the cost function reaches a minimum (e.g., a small Hamming distance between peaks in a correlation graph). Thus, the joint correlation output may be a joint correlation value or a set of values.

[0088] A number of examples have been given here to illustrate various features and are not intended to be so limited. Any one or more of the features may not be limited to the specific examples presented herein, regardless of any order, combination or connection described. In fact, it should be understood that any combination of the features and / or elements described above by way of example is contemplated, including any variations or modifications that are not listed but can achieve the same. Unless otherwise specified, any one or more of the features may be combined in any order.

[0089] As mentioned above, the drawings are presented herein for illustrative purposes and are not meant to impose any structural limitations unless otherwise specified. Various modifications to any structure shown in the drawings are contemplated to be within the scope of the invention presented herein. The invention is not intended to be limited to any scope of the claim language.

[0090] Where "coupled" or "connected" is used, unless otherwise stated, the coupling or connection is not implied to be limited to physical coupling or connection, but should be understood to include communicative coupling, including wireless transmissions and protocols.

[0091] Any block, step, module or other means described herein may represent one or more instructions, which may be stored as software on a non-transitory computer-readable medium and / or executed by hardware. Any such block, module, step or other means may be executed by various software and / or hardware combinations in a manner that may be automated, including using special hardware designed to achieve such purposes. As described above, any number of blocks, steps or modules may be executed in any order or not at all, including substantially simultaneously, i.e., within the tolerance of the system executing the blocks, steps or modules.

[0092] Where conditional language is used, including but not limited to "can," "may," "could," or "might," it should be understood that the associated features or elements are not required. Thus, where conditional language is used, elements and / or features should be understood to be optionally present in at least some examples, and not necessarily conditional on anything, unless otherwise specified.

[0093] Where a list is listed with alternatives or conjunctions (e.g., one or more of A, B, and / or C), unless otherwise specified, it is understood to include one or more of each element, including any one or more combinations of any number of the listed elements (e.g., A, AB, AC, ABC, ABB, etc.). When "and / or" is used, it should be understood that the elements can be connected in an alternative or conjunction manner.

[0094] While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the following claims.

Claims

1. A method for performing motion compensated signal processing, the method comprising: receiving, at a receiver, a first signal from a remote source in a first direction; providing a first local signal; determining movement of the receiver using the first data and not using data derived from the accelerometer; providing a correlated signal by correlating the local signal with a received signal; providing motion compensation for at least one of the local signal, the received signal, and the correlation signal based on the determined movement in the first direction to provide preferential gain for signals received along the first direction; as well as The received first signal is processed based on the correlation.

2. The method according to claim 1, wherein: The receiver is mounted to a vehicle.

3. The method according to claim 2, wherein: The first data is derived from an output of a sensor arrangement comprised by the vehicle, the sensor arrangement comprising any one or more of: a vehicle wheel speed sensor, a vehicle steering angle sensor, a vehicle throttle position sensor, and a vehicle brake sensor.

4. The method according to claim 2 or claim 3, wherein: The first data is obtained from a communication system of the vehicle.

5. The method according to any one of claims 2 to 4, wherein: The first data is obtained from a visual odometry system of the vehicle.

6. A method according to any one of the preceding claims, wherein: The first data includes position information for a receiver obtained using a Global Navigation Satellite System (GNSS) receiver.

7. The method according to any one of the preceding claims, further comprising: generating motion estimate information representative of motion of the receiver based on the correlation, and Movement of the receiver is determined based on the generated movement estimate information.

8. The method according to claim 7, wherein: Providing motion compensation includes: generating a plurality of phasor sequences, each phasor sequence corresponding to a hypothesis including a set of signal phase offsets representing movement of the receiver, correlating at least one local signal with at least one received signal to produce at least one correlation result; compensating a phase of at least one of the local signal, the at least one received signal, or the at least one correlation result based on a plurality of assumptions about movement of the receiver to generate a plurality of phase-compensated correlation results; and determining a preferred hypothesis among the plurality of hypotheses that optimizes at least one correlation result of at least one of the phase compensated correlation results, and wherein the generated motion estimate information comprises a motion estimate associated with the preferred hypothesis, and The determination of the movement based on the generated motion estimate information includes updating a motion model representing the movement using the motion estimate.

9. A method according to any one of the preceding claims, wherein: The determination of the movement of the receiver is performed without using data derived from a magnetometer.

10. A method according to any one of the preceding claims, wherein: The determination of the movement of the receiver is performed without using data derived from an inertial measurement unit (IMU).

11. A method according to any one of the preceding claims, wherein: The determination of the movement of the receiver is performed without using data derived from a gyroscopic sensor.

12. A method according to any preceding claim, comprising processing the received signal based on the correlation in order to determine a metric of interest related to the receiver and / or to a communication link comprising the receiver.

13. The method according to claim 12, wherein: The metric of interest includes at least one of: position, range, speed, velocity, trajectory, altitude, compass heading, step cadence, step length, distance traveled, motion context, position context, output power, calorie count, sensor bias, sensor scale factor, and sensor alignment error.

14. A system comprising: a receiver configured to receive a signal from a remote source in a first direction; a local signal generator configured to provide a local signal; a motion module configured to provide the determined movement of the receiver using the first data and without using data derived from the accelerometer; a correlation unit configured to provide a correlation signal by correlating the local signal with a received signal; as well as A motion compensation unit is configured to provide motion compensation for at least one of the local signal, the received signal and the correlation signal based on the determined movement in the first direction so as to provide a preferential gain for the signal received along the first direction.

15. The system of claim 14, wherein: The receiver is mounted to the vehicle.

16. The system of claim 15, wherein: The vehicle comprises a sensor arrangement comprising any one or more of: a vehicle wheel speed sensor, a vehicle steering angle sensor, a vehicle throttle position sensor, and a vehicle brake sensor, and Therein, the first data is derived from an output of the sensor arrangement.

17. A system according to claim 15 or claim 16, wherein: The first data is obtained from a communication system of the vehicle.

18. A system according to any one of claims 15 to 17, wherein: The first data is obtained from a visual odometry system of the vehicle.

19. A computer program product comprising executable instructions which, when executed by a processor, cause the processor to perform steps comprising: receiving, at a receiver, a first signal from a remote source in a first direction; providing a first local signal; determining movement of the receiver using the first data and not using data derived from the accelerometer; providing a correlated signal by correlating the local signal with a received signal; providing motion compensation for at least one of the local signal, the received signal, and the correlation signal based on the determined movement in the first direction to provide preferential gain for signals received along the first direction; as well as The received first signal is processed based on the correlation.

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