Method and apparatus for performing motion compensated signal processing

Abstract

A method for performing motion-compensated signal processing is described. The method includes, at a receiver, receiving a first signal from a remote source in a first direction, providing a first local signal, determining motion of the receiver using the first data without 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 determined motion in the first direction to provide a preferential gain to the signal received along the first direction, and processing the received first signal based on the correlation. A system for performing motion-compensated signal processing is also described.

Description

[Technical Field]

[0001] FIELD OF THE INVENTION Embodiments of the present invention relate generally to wireless receivers, and more particularly to methods and apparatus for performing motion compensated signal processing within a wireless receiver. [Background technology]

[0002] Positioning signal receivers, such as receivers for Global Navigation Satellite System (GNSS) signals, have become ubiquitous in mobile devices. GNSS receivers (e.g., receivers for satellite signals such as GPS, GLONASS, GALILEO, DEIBOU, or a combination thereof) receive signals from satellites, process the received signals, and determine the receiver's position from the information contained in the received signals. Typical accuracy for consumer receivers without the aid of an inertial measurement unit (IMU) can range from 5 to 50 meters. To provide inertial navigation in a typical mobile device, an IMU typically includes a magnetometer, a gyroscope, and an accelerometer—i.e., traditional IMU sensors. Signals from these three sensors (typically MEMS-based sensors) are used to augment the GNSS receiver's positioning calculations, so that the receiver's accuracy may be improved to approximately 20 cm. However, that additional accuracy comes at the significant cost of the IMU sensors and additional computational complexity.

[0003] In other forms of wireless receivers, it may be advantageous to perform signal reception to account for receiver motion so that the received signal may be motion compensated, i.e., have frequency and / or phase errors caused by receiver motion removed from the signal correlation process. Compensating for receiver motion may improve receiver signal reception and / or reduce receiver component costs.

[0004] Therefore, there is a need for a method and apparatus for performing motion compensation signal processing without using conventional IMU data from a full complement of conventional IMU sensors. Summary of the Invention

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

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

[0007] According to a first aspect of the present invention, there is provided 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; and providing a first local signal; determining motion of the receiver using the first data without using data derived from the 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 determined motion in the first direction to provide preferential gain to signals received along the first direction; processing the received first signal based on the correlation; Includes.

[0008] The inventors have recognized that by compensating for the phase and frequency effects of receiver motion without the use of accelerometers, as conventionally used in IMU-augmented navigation and inertial motion sensing, significant improvements in signal reception and positioning, along with reduced computational and sensor component requirements, may be achieved. Alternatively, determining motion without the use of accelerometer-derived data may be defined as doing so without the use of data from an accelerometer, i.e., without the use of data from an accelerometer positioned and / or configured to directly and / or indirectly monitor receiver motion.

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

[0010] It will be appreciated that providing the first local signal and providing the correlation signal may include 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 signals are correlated. Motion compensation may also be applied to the correlated signal following correlation. By providing motion compensation in a first direction, typically extending between the receiver and the remote source, it is possible to achieve preferential gain for signals received along this direction. Thus, line-of-sight signals between the receiver and the remote source receive preferential gain over reflected signals received in a different direction. In addition to being useful for signal processing in general, motion-compensated correlation is particularly advantageous when applied in a positioning system or as part of a positioning method. In a GNSS receiver, for example, non-line-of-sight signals (e.g., reflected signals) are significantly suppressed, so the above-mentioned preferential gain can lead to a significant improvement in the accuracy of calculations based on received signals. The highest correlation may be achieved for line-of-sight signals, even if their absolute power is smaller than that of non-line-of-sight signals.

[0012] The received signal may contain any known or unknown pattern of transmitted information, either digital or analog, that can 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 chipping code that can be used for ranging. Examples of such received signals include GPS signals, which contain Gold codes encoded within the radio transmission. Another example is the extended training sequence used in GSM cellular transmissions.

[0013] Traditionally, phase changes in received signals caused by changes in the line-of-sight path between the receiver and a remote source have been viewed as a nuisance that exacerbates signal processing overhead and reduces positioning accuracy. A counterintuitive approach to determining receiver motion without IMU data can actually exploit these phase changes to improve identification of line-of-sight signals from remote sources while minimizing computational and resource requirements.

[0014] The motion compensation unit can provide motion compensation to the local signal so that the local signal more closely matches the received signal. In another configuration, motion compensation may be applied to the received signal to reduce the effect of receiver motion on the received signal. Similar results may 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 may be performed in parallel with correlation. Motion compensation may also be applied directly to the correlated signal.

[0015] In practice, the received signal may be processed as a complex signal containing an in-phase component and a quadrature component. The local signal may be complex as well. The correlation unit may be configured to provide a correlation signal that may be complex and that can be used as a measure of the correlation between these complex signals.

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

[0017] Lower accuracy may be achieved by providing motion compensation of the correlation signal. In the above example, when applied to the GPS L1 C / A code, correlation may be performed independently on each of approximately 1,000 pseudorandom code chips to generate approximately 1,000 complex correlator signal outputs. A motion compensation vector may then be applied to these approximately 1,000 correlation signal components. Finally, the motion-compensated correlation signals may be summed to generate a measure of correlation. Thus, motion compensation of the correlation signal may produce an approximation of the results that can be achieved by motion compensation of the local and received signals. However, in some applications, the loss of accuracy may be negligible, which may be acceptable because it allows for a reduced computational load.

[0018] In some embodiments, the motion compensation process includes generating multiple phasor sequences, each of which 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 both amplitude and phase. The method may then include correlating at least one local signal with at least one received signal to generate at least one correlation result, and compensating at least one phase or multiple phases of the local signal, the at least one received signal, or the at least one correlation result based on multiple hypotheses regarding the determined motion model to generate multiple phase-compensated correlation results. Typically, the multiple phases correspond to a sequence of phase corrections, one of which is preferably applied to each of multiple samples of the signal. The method may then include determining a preferred hypothesis from the multiple hypotheses, which may be understood as the hypothesis that optimizes at least one of the phase-compensated correlation results. The method may, for example, include correlating multiple samples of the received signal received by the receiver during a certain period of time. The same signal may be compensated using multiple different estimated phasor sequences, and a correlation result may be generated for each of the multiple different estimated phasor sequences. Each phasor sequence may include multiple phasors representing different phases, typically at different defined times during the period. The multiple estimated phasor sequences may differ in that each estimated phasor sequence may be based on a different hypothesis regarding the evolution of frequency and phase through a defined time during the period. Correlation results may be used to determine a preferred hypothesis regarding the evolution of frequency and phase during the period.

[0019] As previously described in this disclosure, a gain provided to a signal received along a first direction may be prioritized in that it is greater than a gain provided to a signal received in a second direction that is not a line-of-sight direction on the remote source relative to the receiver. Typically, the first direction is such a line-of-sight direction. That is, the signal's propagation path may include only a single direction or vector between the receiver and 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 signal's propagation path may preferably be calculated based on geometric data representing reflective structures. For example, three-dimensional geometric models representing urban structures in some geographic regions are available. Knowledge of the presence, location, range, and orientation of reflective surfaces and structures, or any one or more of these, may be used to utilize non-line-of-sight signaling methods.

[0020] The correlation-based processing may include improving wireless receiver signal reception using the phase-compensated correlation results. The processing may be performed to improve wireless receiver reception, for example, to increase the quality, strength, and / or reliability of the received / processed signal. For example, the 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 to process the received signal based on the motion-compensated correlation signal, or alternatively, based on the motion-compensated correlation results.

[0021] In some embodiments, the receiver, typically its antenna, is mounted to the vehicle. Additionally or alternatively, the receiver may be mounted to, and / or attached to, coupled to, provided with, or part of the vehicle. Typically, the receiver or receiver components are mounted such that the position and / or orientation of the receiver is, or substantially is, fixed or unchanging relative to the vehicle, or its body, main portion, or chassis. Advantageously, in various embodiments, data is typically available from the vehicle from which motion can be determined, thereby eliminating the need for any inertial data in some embodiments. The vehicle may be, for example, an automobile, bus, train, industrial or agricultural vehicle, watercraft, or aircraft.

[0022] According to a second aspect of the present invention, there is provided 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 a receiver mounted on the vehicle using first data, the first data being derived from output of sensor devices carried by the vehicle, the sensor devices comprising any one or more of a 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 the received signal; providing motion compensation for at least one of the local signal, the received signal, and the correlated signal based on the determined motion in the first direction to provide preferential gain to signals received along the first direction; and processing the received first signal based on the correlation.

[0023] In this manner, the method enables motion compensation to be performed by determining motion from vehicle sensors and / or components using data from sensors and / or vehicle components that are typically commonly available in many vehicle systems, thereby improving the component and resource efficiency of the motion compensation correlation process.

[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 device excludes an accelerometer, and preferably the vehicle does not include an accelerometer.

[0025] In view of the above, it will be appreciated that the method according to the first aspect may in some embodiments include first data derived from output of sensor devices included in the vehicle, the sensor devices including any one or more of a wheel speed sensor, a vehicle steering angle sensor, a vehicle throttle position sensor, and a vehicle parking sensor.

[0026] The features described below 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 devices may be included in the vehicle and / or receiver itself. The aforementioned wheel speed sensors may, in some embodiments, be provided as rotational motion and / or position sensors. Wheel rotation information may be readily converted into data representative of the vehicle's distance traveled, speed, velocity, and acceleration. Typically, the vehicle's wheels, typically each wheel of the vehicle, are equipped with a speed sensor adapted to monitor the wheel's rotational speed, e.g., angular velocity. By analyzing the speed data from one or each wheel of the vehicle, typically a four-wheeled vehicle, a system such as an electronic control unit (ECU) can calculate the vehicle's speed, acceleration, and wheel slip.

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

[0029] A vehicle throttle position sensor may advantageously provide information regarding the position of an accelerometer control or pedal, which may typically be used to determine desired or controlled levels of driver input and / or engine or motor output.

[0030] Vehicle brake sensors may be provided to collect data from various sensors, such as brake pedal position sensors and / or wheel speed sensors, which are typically used in calculating decisions regarding braking force, wheel lockup, and vehicle deceleration.

[0031] Any one or more of these sensor systems, or a system that processes data therefrom, such as the ECU mentioned above, may be used to calculate a motion model that represents the motion of the vehicle.

[0032] Typically, a vehicle uses a communication network or system to process data related to the vehicle's motion in this manner, from which an estimate or model of the motion can be easily calculated. For example, the vehicle's speed, position, altitude, heading, heading, braking, acceleration, and changes in speed may be obtained. This data may be obtained directly from data communicated within the network, or indirectly, for example, with some quantitative influence, calculation, or estimation, and for example, by combining multiple data sources to converge on an accurate representation or motion of the vehicle. Thus, in some embodiments, the first data is obtained from the vehicle's communication system. Alternatively, the first data may be obtained from a communication device, for example, a vehicle bus. It will be understood that a vehicle bus refers to a communication network that is typically internal to or provided as part of the vehicle. Typically, such a bus is configured to interconnect vehicle components. In the context of the present disclosure, a bus may be understood as a device that connects or communicatively couples multiple electrical or electronic devices to each other.

[0033] In particular, the movement or data from which the movement is determined can be obtained from a Controller Area Network (CAN) bus, which may be understood as a vehicle bus standard adapted to allow one or more microcontrollers and / or devices in a vehicle to communicate. This communication is typically between respective applications, preferably without a host computer. Thus, the first data may be obtained from at least one electronic control unit (ECU) in the vehicle that includes a receiver. The ECU may be part of the vehicle bus or may be configured to communicate with or via the vehicle bus. Typically, a vehicle includes multiple ECUs corresponding to vehicle components or subsystems. Typically, a vehicle includes an engine ECU configured to process data for the engine and / or control functions related to the engine or, for example, related to the motor of an electric vehicle. The vehicle may also include ECUs for any one or more of the following: an advanced driver assistance system (ADAS), a transmission, a braking system, an anti-lock brake system, cruise control, and steering, e.g., electric power steering.

[0034] In addition to, or instead of, using data, typically expressed numerically, associated with vehicle components, typically moving components, to derive a model of vehicle motion from the monitored or controlled motion of these components, the motion model may be derived using image data or visual data. For example, in some embodiments, the first data includes data obtained from or acquired 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., images obtained by a camera mounted on or coupled to the vehicle.

[0035] Visual odometry data may be advantageously used to determine the motion of the receiver. If visual odometry data capability is provided in the vehicle, the use of image data from that system can improve the accuracy of the model's motion because inaccuracies that may be introduced 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, do not similarly affect images that provide a visual representation of the vehicle's true position, motion, etc.

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

[0037] Modeling the motion using the GNSS position and / or velocity information may include using the GNSS data as initial data, for example to initialize a prediction or estimate of the receiver's motion. After that initialization, the method may include using another subset 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 location information of the receiver obtained using a Global Navigation Satellite System, GNSS, receiver.

[0039] Processing received signals, whether for communication or positioning purposes, according to correlation results while taking into account receiver motion that can be determined in this manner provides a more efficient approach than conventional techniques. Furthermore, when multiple signals are received, multiple respective correlation results for each received signal can be combined and used to compute, for example, by converging, an optimal hypothesis having a phasor sequence that best represents the true motion of the platform.

[0040] Preferably, said GNSS receiver is the same as or is included in the same device as said receiver.

[0041] In some embodiments, the first data includes sensor data from a vehicle camera, such as a visual or optical imager, LIDAR, RADAR, camera, etc. Such sensors may be provided in communication with a device such as a CAN bus, or may contribute to the first data without being so connected, and may provide data to enable or facilitate determining the current attitude of the vehicle.

[0042] In some embodiments, the correlation results themselves are used to provide feedback to improve the motion modeling on which the ongoing motion-compensated correlation is based. In some cases, the method further includes generating motion estimation information representing receiver motion based on the aforementioned correlation. The motion estimation information can be understood as relating to the determined motion, and can be thought of as a motion estimate, a motion model, or a motion model, as described above. It may also be referred to as motion model adjustment information, motion model correction information, or motion model update information. The motion represented by the motion estimation information may be, include, or be contained in the determined motion. For example, it may include the determined motion, or a portion thereof, e.g., a later portion, as well as the motion that follows therefrom. The correlation results may indicate the true receiver speed and may converge to a hypothesis representing, for example, the true vehicle speed. This information is thus useful for motion determination and can be used, for example, to constrain motion calculations or predictions for ongoing motion compensation processing.

[0043] Therefore, the method may include determining the motion of the receiver based on the generated motion estimation information. This determination is preferably performed in the same manner as the motion determination described above, i.e., using the first data and / or without using data derived from the accelerometer. Typically, the determined motion is receiver or vehicle motion, some or all of which occurs later in time than some or all of the previously determined motions. Preferably, determining the motion of the receiver based on the generated motion estimation information includes updating a motion model using a motion estimate associated with a preferred hypothesis. In other words, the method may include generating feedback information using the correlation results to adjust, update, or correct the motion determination. This may improve the accuracy of the motion determination and may improve motion-compensated correlation and signal processing.

[0044] As previously suggested in this disclosure, motion compensation may be provided by generating multiple phasor sequences, each corresponding to a hypothesis including a set of one or more signal phase offsets representing receiver motion, and correlating at least one local signal with at least one received signal to generate at least one correlation result. Thus, the method may include compensating the phase of at least one of the local signal, the at least one received signal, or the at least one correlation result based on multiple hypotheses regarding the receiver motion to generate multiple phase-compensated correlation results. In some embodiments, a hypothesis may be considered a hypothesis regarding or for a determined motion model of the receiver, in the sense that determining motion typically includes generating an estimate or model of the motion. A preferred hypothesis from the multiple hypotheses may then be identified or determined. The preferred hypothesis may be one of the multiple that optimizes at least one of the phase-compensated correlation results.

[0045] Thus, the generated motion estimation information may include a motion estimate based on or associated with a preferred hypothesis. The motion estimation information may thereby include data that more accurately indicates the receiver's motion. Thus, typically, the determination of motion for one or more subsequent time periods may include an existing or predetermined estimate or model of the receiver's motion, as described above, updated, modified, or generated in accordance with the motion estimate. In particular, the motion determination may include generating or updating a motion model that represents the receiver's motion using the motion estimate.

[0046] Preferably, the determination of the receiver's movement 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 will be appreciated that systems typically adapted to monitor movement by accelerometers may do so specifically by an inertial measurement unit, and that eliminating the need for such components is an advantage provided by the method. Preferably, the determination of the receiver's movement is performed without using data derived from a gyro sensor. In any of the foregoing embodiments, instead of or in addition to determinations made without data derived from a given type of sensor or unit, the sensor apparatus described above in this disclosure, and indeed the receiver or any platform or vehicle including it, may be understood to exclude that respective type of sensor or unit.

[0047] Typically, the method enables more efficient processing of received signals for motion-compensated correlation. However, the technique is particularly useful in applications in which a metric of interest, such as receiver position, is 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 may be the position, velocity, time, or direction of motion of the receiver (e.g., 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. Thus, the wireless communication system may be, or may be part of, a positioning system.

[0048] The aforementioned communication link may be a cellular telecommunications 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 a 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, stepping cadence, stride length, distance traveled, motion context, position context, output power, calorie count, sensor bias, sensor scale factor, and sensor alignment error. Thus, if the metric of interest is related to a receiver, it may include any metric that may be determined from a sensor configured to make measurements from which the position or motion of the receiver or its platform may be determined.

[0050] According to a third aspect of the present invention, there is provided 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 a determined motion of the receiver using the first data and without using data derived from the accelerometer; a correlation unit configured to provide a correlated signal by correlating the local signal and the received signal; a motion compensation unit configured to provide motion compensation of at least one of the local signal, the received signal, and the correlation signal based on the determined motion in the first direction to provide a preferential gain to the signal received along the first direction; Equipped with.

[0051] In some embodiments, the system is or is included in a positioning system. Typically, the system does not include an accelerometer, or in particular an IMU. Typically, the system is not communicatively coupled to a receiver or any such sensor configured or provided to monitor the movement of any platform comprising or coupled to the receiver.

[0052] In some embodiments, the system is mounted on or integrated within the vehicle, or at least in data communication with the vehicle. At least the receiver or its antenna may be mounted on the vehicle instead of or in addition 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 first data derived therefrom to determine the compensated motion.

[0053] In some embodiments, the vehicle and / or system includes a sensor device, the sensor device including any one or more of a 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 an output of the sensor device. For example, the system may include a first data module configured to receive the first data or to receive one or more signals output by a central device and to derive the first data therefrom.

[0054] Typically, the first data is obtained from the vehicle's communication system, for example the 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 present invention there is provided a computer program product comprising executable instructions which, when executed by a processor, for example a processor in a positioning system, typically a vehicle's positioning system or a positioning system included in a vehicle, cause the computer program product to: receiving, at a receiver, a first signal from a remote source in a first direction; providing a first local signal; and determining motion of the receiver using the first data without using data derived from the 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 determined motion in the first direction to provide preferential gain to signals received along the first direction; processing the received first signal based on the correlation; causing a processor to execute steps including:

[0057] As alluded to above, methods and systems for performing motion compensated signal processing may be provided without relying on accelerometer data, such as traditional IMU data.

[0058] Accordingly, a fifth aspect of the present invention provides a method for performing motion compensated signal processing, the method comprising: determining a motion model of an antenna coupled to a wireless receiver without using conventional IMU data; generating a plurality of phasor sequences, each phasor sequence forming hypotheses including signal phase offsets, typically a sequence of signal phase offsets, that represent antenna motion; correlating at least one local signal with at least one received signal to generate at least one correlation result; compensating the phase of at least one of the local signal, the at least one received signal, or the at least one correlation result based on the plurality of hypotheses regarding the determined motion model to generate a plurality of phase-compensated correlation results; determining a preferred hypothesis from the plurality of hypotheses that optimizes at least one of the phase-compensated correlation results; updating the motion model using a motion estimate associated with the preferred hypothesis; and using the phase-compensated correlation results to improve wireless receiver signal reception.

[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 including at least one processor and at least one non-transitory computer-readable medium storing instructions that, 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 wireless receiver without using conventional IMU data; generating a plurality of phasor sequences, each phasor sequence forming a hypothesis including a signal phase offset or a sequence of signal phase offsets, representing antenna motion; correlating at least one local signal with at least one received signal to generate at least one correlation result; compensating the phase of at least one of the local signal, the at least one received signal, or the at least one correlation result based on the plurality of hypotheses for the determined motion model to generate a plurality of phase-compensated correlation results; determining a preferred hypothesis from the plurality of hypotheses that optimizes at least one of the phase-compensated correlation results; updating the motion model using a motion estimate associated with the preferred hypothesis; and improving wireless receiver signal reception using the phase-compensated correlation results. [Brief explanation of the drawings]

[0060] So that the above-described features of the present invention may be understood in detail, a particular description of the invention can be made by reference to embodiments, some of which are illustrated in the accompanying drawings. It should be noted, however, that the accompanying drawings illustrate only typical embodiments of the invention and therefore should not be considered as limiting its scope, since the invention may admit of other equally effective embodiments. [Figure 1] FIG. 1 is a functional block diagram of a wireless signal receiver mounted in a vehicle in accordance with at least one embodiment of the present invention. [Figure 2]2 is a block diagram of a computing device programmed to function as a signal processor of the receiver of FIG. 1 in accordance with at least one embodiment of the present invention. [Figure 3] 1 is a flow diagram of a method of operation of a computing device when executing signal processing software in accordance with at least one embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0061] Embodiments of the present invention include apparatus and methods for performing motion-compensated signal processing for wireless 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 by utilizing only gyroscope IMU data. Such positioning systems simplify the calculations required to improve positioning accuracy compared to traditional IMUs (e.g., magnetometers, accelerometers, and gyroscopes). Furthermore, by eliminating the IMU or using a simplified IMU, embodiments of the present invention significantly reduce the bill of materials (BOM) of the wireless receiver.

[0062] Satellite-based positioning systems and communications receivers utilize coded digital signals that include deterministic digital codes, e.g., Gold codes, to facilitate signal acquisition. 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 combined with an accurate motion model of the receiver, embodiments of the present invention are useful for enabling the receiver to improve its position calculation accuracy and / or signal reception without using conventional IMU data from a full complement of IMU sensors. A technique for improving wireless signal reception using receiver motion compensation signal processing is known as SUPERCORRELATION™ and is described in commonly assigned U.S. Pat. No. 9,780,829, issued October 3, 2017, U.S. Pat. No. 10,321,430, issued June 11, 2019, U.S. Pat. No. 10,816,672, issued October 27, 2020, U.S. Patent Application Publication No. 2020 / 0264317, published August 20, 2020, and U.S. Patent Application Publication No. 2020 / 0319347, published October 8, 2020, which are incorporated by reference herein in their entireties. Motion models are typically derived using IMU data; however, in embodiments 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 the motion information determined by the SUPERCORRELATION™ technique is provided to the motion module as feedback to correct and / or update the motion model.

[0063] In one embodiment, the wireless receiver is incorporated into a moving platform, such as, but not limited to, an automobile, motorcycle, airplane, helicopter, drone, bicycle, or person (e.g., a person carrying a smartphone, tablet, computer, Internet of Things (IoT) device, etc.). In certain embodiments, the platform may be a vehicle. In one embodiment, the vehicle's CAN bus data may be used to determine initialization parameters for a motion module that generates a motion model used in the SUPERCORRELATION™ technology. The initialization parameters include a reference direction, downward, as well as vehicle speed and heading. The vehicle's CAN bus carries data from all electronic control units (ECUs) and sensors located on the vehicle. As a result, data such as speed, acceleration, steering input, braking input, and throttle input is readily available for use in generating the vehicle's motion model. If a gyroscope is available, the CAN bus data may be used to generate gyroscope drift compensation. Additionally, other sensor data from vehicle LIDAR, RADAR, cameras, etc., which may or may not be available from the CAN bus, may also be used to determine the vehicle's current attitude.

[0064] During operation, at least one received signal is correlated with at least one locally generated signal to generate 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, thus resulting in a less complex and less expensive wireless receiver.

[0065] FIG. 1 shows a block diagram of a wireless receiver 100 installed in a vehicle 102 in accordance with at least one embodiment of the present invention. In this embodiment, the wireless 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 standard communication protocols (ISO 11898-1, -2, -3). The receiver 100 uses the CAN bus data to derive motion information (also referred to as a motion model) regarding vehicle motion. As the vehicle moves, the receiver 100 receives signals from remote positioning transmitters (e.g., GNSS satellites 108 arranged in an Earth-orbiting constellation of satellites).

[0066] In an exemplary embodiment, receiver 100 comprises 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 inseparable unit, with antenna 110 moving with vehicle 102. SUPERCORRELATION™ technology operates based on determining the motion component of a signal receiving antenna in the direction of the source of the received signal. Any reference to motion herein refers to the motion of antenna 110. In most scenarios, the motion of vehicle 102 is the same as the motion of antenna 110, and therefore, the following description assumes that the motions of vehicle 102 and antenna 110 are the same.

[0067] The receiver front end 112 downconverts, filters, and samples (digitizes) the received signal in a manner well 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, e.g., a Gold code, that the GNSS receiver uses to synchronize transmissions to the GNSS receiver 100.

[0068] The GNSS signal processor 114 correlates the received code from each satellite with a locally generated code to generate a correlation result. The correlation result is processed as known in the art to generate position information 126, where the correlation result is used to determine a pseudorange for each satellite, and the pseudorange is processed to calculate the receiver position. The motion compensation processor 116 performs SUPERCORRELATION™ processing to provide a signal (phasor sequence) to phase-adjust the correlation result so that the coherent integration period is extended, e.g., to one second or more. A phasor sequence is a time sequence of phase offsets in which each phasor in the sequence adjusts the phase of a signal sample. The adjustment may be performed by adjusting the phase of each sample of the received signal, a locally generated signal, or the correlation result itself. The least computationally intensive adjustment process is adjusting the phase of the correlation result.

[0069] The motion module 118 generates vehicle motion information that is used by the motion compensation processor 116 to generate phasor sequences used to motion-compensate the correlation results. The phasor sequences include a sequence of phase offsets over time, e.g., across the received signal, to compensate for phase changes that occur over time due to vehicle motion. In one embodiment, the motion module 118 uses the 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 vehicle speed and heading. In an alternative embodiment, the motion module 118 may include an optional gyroscope 122 to provide vehicle direction information for the motion model. The motion compensation processor 116 provides motion estimation correction information along the path 120 to the motion module 118. In this manner, the motion compensation processor 116 provides corrective feedback to the motion module 118.

[0070] FIG. 2 illustrates a block diagram of a computing device operating as the motion compensation processor 116 of FIG. 1 in accordance with at least one embodiment of the present invention. The motion compensation processor 116 comprises 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, or the like. The support circuits 202 may comprise well-known circuits and devices that facilitate the functions of the processor. The support circuits 202 may include one or more, or a combination of, a power supply, a clock circuit, an analog-to-digital converter, a communication circuit, a cache, a display, and / or the like. The support circuits 202 form an interface between the processor 200 and both the motion module 118 and the GNSS signal processor 114.

[0071] 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 various additional data used to perform SUPERCORRELATION™ processing. The signal processing software 206, when executed by the one or more processors 200, generates signals to facilitate motion-compensated correlation. The motion-compensated correlation process is described in more detail below. The operation of the signal processing software 206 functions as the motion compensation processor 116 of FIG. 1.

[0072] 3 is a flow diagram of a method 300 of operation of signal processing software 206 when executed by processor 200, in accordance with at least one embodiment of the present invention. Method 300 may be implemented in software (e.g., using motion compensation processor 116 of FIG. 1), hardware, or a combination of both.

[0073] Method 300 begins at 302 and proceeds to 304, where signals are received at a receiver from at least one remote source (e.g., a transmitter such as satellite 108 of FIG. 1) in a manner such as described with respect to FIG. 1. Each received signal includes a synchronization or acquisition code, e.g., a Gold code, extracted from a radio frequency (RF) signal received at an antenna. Processes for downconverting RF signals and sampling digital codes are well known in the art.

[0074] At 306, method 300 defines a search space for processing the received signal. 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. Upon initialization, the search space may be wide, i.e., have many hypotheses. As hypotheses are tested and the correlation result converges to an optimal value, the search space can be narrowed for subsequent correlation result processing. For example, if motion information is uncertain, the method may define a search space with many phasor sequence hypotheses associated with several unknown parameters, such as speed and / or direction of travel. Once a preferred hypothesis is determined, the next received signal is tested with a hypothesis that is close to or identical to the previous preferred hypothesis.

[0075] In one embodiment, information from the CAN bus may be used to constrain the search space. For example, steering input data on the CAN bus may indicate that the steering wheel has been turned to the right. As a result, the vehicle's direction changes, and method 300 may adjust the search space to the right. In another example, brake pedal data may indicate that the brake pedal has been depressed to slow the vehicle. As a result, method 300 may modify the speed search space to cover slower speed values in anticipation of the vehicle slowing down. Similarly, visual odometry data may be used to constrain the search space by predicting changes in vehicle pose.

[0076] In other embodiments, there may be no additional data available at initialization to aid GNSS information for the platform's initial position and velocity. Thus, method 300 may use the initial GNSS position / velocity and then use any available motion-indicating data to constrain the hypothesis search space. In some embodiments, method 300 may not have other measured motion information available. In these situations, motion constraints may be applied based on laws of physics, such as typical vehicle acceleration and deceleration values, maximum vehicle turning radius, knowledge of most vehicles over short periods of time moving in substantially straight lines, etc.

[0077] At 308, method 300 generates multiple phasor sequence hypotheses associated with the motion information. Each phasor sequence hypothesis includes a sequence of signal phase offset estimates that vary with a receiver motion parameter. Signal processing correlates a local code encoded in the local signal with a code encoded in the received RF signal. In this example, the phasor sequence hypotheses are used to adjust the carrier phase of the local signal with sub-wavelength accuracy. In some examples, such adjustment or compensation may be performed by adjusting the local oscillator signal, the received signal, or the correlation result to generate a phase-compensated correlation result. The signal and / or correlation result include complex signal samples having an in-phase component (I) and a quadrature component (Q). The method applies each phase offset in the phasor sequence to the corresponding complex sample in the signal and / or correlation result. For each received signal, at 310, method 300 correlates the received signal with a set (or multiple) phasor sequence hypotheses that include the time-series phase offset estimates necessary to accurately correlate the received signal.

[0078] A motion estimate is typically a hypothesis of motion in a direction of interest, such as the direction of a satellite that transmitted a received signal along a signal propagation path. At initialization, the direction of the target may be unknown or inaccurately estimated. As a result, a brute-force search technique may be used to identify the direction of one or more targets by searching across all directions and correlating the received signal across all directions. Comparing the correlation results across all directions allows the method 300 to narrow the search space when processing subsequently received signals. Because there is a very strong correlation between the true values of these hypotheses during code iterations, the initial search may be intensive, but subsequent processing only requires tracking the parameters at the receiver as they evolve. As a result, subsequent compensation is performed across a narrow search space.

[0079] In one embodiment, if a signal from a given satellite has been previously received, the set of hypotheses for the newly received signal includes a group 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 hypothesis values may be centered around the last value used or the last value used with an additional offset, with a prediction of a further offset based on expected receiver motion. At 310, method 300 correlates each received signal with the set of hypotheses for that signal. The hypotheses are used as parameters to form phase-compensated phasors to phase-compensate the correlation process. Thus, phase compensation may be applied to the received signal, a local frequency source (e.g., an oscillator), or the correlation result values. In addition to searching for receiver motion (usually expressed as receiver velocity) to ensure the correct motion compensation is applied, method 300 may also apply hypotheses related to other variables (parameters), such as oscillator frequency, to correct for frequency and / or phase drift (if not previously corrected) or signal direction of arrival (DoA). The number of hypotheses does not have to be the same for each variable. For example, the search space may include 10 hypotheses for searching DoA and 2 hypotheses for searching receiver motion parameters such as speed, for a total of 20 hypotheses (10 x 2). The result of the correlation process is multiple phase-compensated correlation results, one phase-compensated correlation result value for each hypothesis for each received signal.

[0080] At 312, method 300 processes the correlation results to find the "best" or optimal result for each received signal. In one embodiment, method 300 generates a joint correlation output as a function (e.g., the sum) of multiple correlation results resulting from all hypotheses and received transmitter signals. The joint correlation output may be a single value or multiple values representing the parameter hypothesis (preferred hypothesis) that provides the optimal or best correlation output. Generally, a cost function is applied to each set of correlation values for each received signal to find the optimal correlation output corresponding to the preferred hypothesis or hypotheses.

[0081] For example, assuming all other receiver parameters except vehicle speed are known, method 300 tests hypotheses using different phasor sequences that compensate for the phase change due to each speed hypothesis. The correct phasor sequence hypothesis, representing an accurate speed estimate, produces the highest correlation result magnitude for a given received signal. By processing received signals from different satellites, the correlation results converge to a hypothesis that represents the true vehicle speed. Performing the correlation process using phase compensation based on true motion information enables the GNSS processor to generate an accurate position without using traditional IMU information.

[0082] At 314, method 300 feeds back the motion information represented by the preferred hypothesis that provides the best output correlation to the motion module. The 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 the occurrence of a deceleration, method 300 may predict that the deceleration will continue and extrapolate the motion model such that the hypothesis is constrained to account for the predicted continued deceleration. The feedback is used to facilitate optimal use of processing resources, i.e., to limit the number of hypotheses tested.

[0083] The method 300 ends at 316.

[0084] In other embodiments, other testing criteria may be used rather than using the correlation value with the largest magnitude. For example, method 300 may monitor the progress of the correlation as hypotheses are tested and apply a cost function that indicates the best hypothesis when the cost function reaches a minimum (e.g., a small Hamming distance between peaks in the correlation plot). Thus, the joint correlation output may be a joint correlation value or group of values.

[0085] Examples are provided herein to illustrate various features and are not intended to be limiting as such. 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. Indeed, it should be understood that any combination of the features and / or elements described in the examples above is contemplated, including any variations or modifications that may achieve the same, although not listed. Unless otherwise specified, any one or more of the features may be combined in any order.

[0086] As noted above, the drawings are presented herein for illustrative purposes and are not meant to impose any architectural limitations unless otherwise specified. Various modifications to any of the structures shown in the figures are contemplated as being within the scope of the inventions presented herein. The invention is not intended to be limited to any extent by the language of the claims.

[0087] When "coupled" or "connected" is used, unless otherwise specified, no limitation that the coupling or connection be limited to a physical coupling or connection is implied, but instead should be read to include communication couplings, including wireless transmissions and protocols.

[0088] Any block, step, module, or the like described herein may represent one or more instructions that may be stored as software on a non-transitory computer-readable medium and / or implemented by hardware. Any such block, module, step, or the like may be implemented by various software and / or hardware combinations, possibly in an automated manner, including the use of dedicated hardware designed to achieve such purposes. As noted above, any number of blocks, steps, or modules may be performed substantially simultaneously, in any order, or not at all, including within the capabilities of the system executing the blocks, steps, or modules.

[0089] When conditional language, including but not limited to "can," "could," "may," or "might," is used, it is to be understood that the associated feature or element is not required. Thus, when conditional language is used, the element and / or feature should be understood as being optionally present in at least some instances, and is not necessarily contingent on anything unless otherwise specified.

[0090] Where a list is alternatively or conjunctively enumerated (e.g., one or more of A, B, and / or C), it is understood to include one or more of each element, including any one or more combinations of any number of the listed elements, unless otherwise stated (e.g., A, AB, AC, ABC, ABB, etc.). When "and / or" is used, it is understood that elements may be joined alternatively or conjunctively.

[0091] While the forgoing 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, which scope is determined by the following claims.

Claims

1. 1. A method for performing motion compensated signal processing, comprising: receiving, at a receiver, a first signal from a remote source in a first direction; providing a first local signal; determining motion of the receiver using the first data without using data derived from an accelerometer; correlating the local signal with the received signal to provide a correlated signal; providing motion compensation for at least one of the local signal, the received signal, and the correlated signal based on the determined motion in the first direction to provide preferential gain to signals received along the first direction; processing the received first signal based on the correlation; A method comprising:

2. The method of claim 1 , wherein the receiver is mounted in a vehicle.

3. the first data is derived from an output of a sensor device provided in the vehicle; The method of claim 2 , wherein the sensor device comprises any one or more of a wheel speed sensor, a vehicle steering angle sensor, a vehicle throttle position sensor, and a vehicle brake sensor.

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

5. The method of claim 2 , wherein the first data is obtained from a visual odometry system of the vehicle.

6. The method of claim 1 , wherein the first data comprises location information of a Global Navigation Satellite System (GNSS) receiver obtained using the receiver.

7. generating motion estimation information representative of motion of the receiver based on the correlation; determining the motion of the receiver based on the generated motion estimation information; 7. The method of claim 1, further comprising:

8. 4. The method of claim 3, wherein the step of providing motion compensation comprises: generating a plurality of phasor sequences, each phasor sequence corresponding to a hypothesis including a set of signal phase offsets representative of the receiver's motion; and correlating at least one local signal with at least one received signal to generate at least one correlation result; compensating the phase of at least one of the local signal, the at least one received signal, or the at least one correlation result based on the plurality of hypotheses regarding the motion of the receiver to generate a plurality of phase-compensated correlation results; determining a preferred hypothesis among the plurality of hypotheses that optimizes at least one of the phase-compensated correlation results; the generated motion estimation information includes a motion estimate associated with the preferred hypothesis; determining the motion based on the generated motion estimation information includes updating a motion model representing the motion using the motion estimates; The method of claim 7.

9. 9. The method of claim 1, wherein the step of determining the movement of the receiver is performed without using data derived from a magnetometer.

10. 10. The method of claim 1, wherein the step of determining the movement of the receiver is performed without using data derived from an inertial measurement unit (IMU).

11. The method of claim 1 , wherein the step of determining the movement of the receiver is performed without using data derived from a gyro sensor.

12. 12. The method of claim 1, comprising processing the received 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.

13. 13. The method of claim 12, wherein the metrics of interest include at least one of position, range, speed, velocity, trajectory, altitude, compass heading, stepping cadence, stride length, distance traveled, motion context, position context, output power, calorie count, sensor bias, sensor scale factor, and sensor alignment error.

14. 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 motion of the receiver using the first data and without using data derived from an accelerometer; a correlation unit configured to provide a correlated signal by correlating the local signal with the received signal; a motion compensation unit configured to provide motion compensation of at least one of the local signal, the received signal, and the correlation signal based on the determined motion in the first direction to provide a preferential gain to a signal received along the first direction; A system comprising:

15. The system of claim 14 wherein the receiver is mounted in a vehicle.

16. the vehicle includes a sensor device, the sensor device including any one or more of a wheel speed sensor, a vehicle steering angle sensor, a vehicle throttle position sensor, and a vehicle brake sensor; The system of claim 15 , wherein the first data is derived from an output of the sensor device.

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

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

19. 1. A computer program product comprising executable instructions that, when executed by a processor, receiving, at a receiver, a first signal from a remote source in a first direction; providing a first local signal; determining motion of the receiver using the first data without using data derived from an accelerometer; correlating the local signal with the received signal to provide a correlated signal; providing motion compensation for at least one of the local signal, the received signal, and the correlated signal based on the determined motion in the first direction to provide preferential gain to signals received along the first direction; processing the received first signal based on the correlation; a computer program product causing the processor to perform steps including:

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