Patent Description:
This present disclosure relates generally to systems for locating and mapping buried utility lines. More specifically but not exclusively, the present disclosure relates generally to vehicle-based systems using principal components for locating and mapping buried utility lines.

There are many situations where it is desirable to locate buried utilities such as electrical power lines, water and sewer lines, gas lines, telecommunication lines, or the like. For instance, excavation of buried utility lines for repair, improvement, or for purposes of new construction may require the location of such utilities to be precisely known so as to avoid costly destruction to infrastructure and potential harm to human wellbeing. Accordingly, the locating and mapping of utility lines is essential to prevent such problems.

Many solutions to locating and mapping buried utility lines have been proposed in the field. Such solutions known in the art generally include the use of one or more human portable devices referred to as "utility locator devices," "locator devices," or "locators" for sensing electromagnetic signals emitted from the utility line or lines. Often such locating operations may use so called "active locating" methods that include coupling of electromagnetic signal onto one or more target utility lines via a transmitter device. An operator, equipped with a utility locator device, may traverse an area of interest while interpreting feedback from the utility locator device to locate and then trace a target utility or utilities at the ground level. Whereas active locating, in some use scenarios, may be sufficient to locate a target utility line or lines, such methods may be impractical if not impossible in use to map and locate all utility lines in an area of interest. Likewise, such systems are subject to human error in interpreting utility locator device feedback as well as being constrained by the ability of the operator to adequately walk distances throughout the area of interest.

Other human portable utility locator devices known of the art may instead or additionally be configured for "passive locating" or, in other words, utilizing signals already present in the utility line or lines to locate and optionally map utility lines present in an area of interest. For instance, passive locating may utilize signals of opportunity emitted by current inherently flowing through the utility (e.g., power lines, telecommunication lines, or the like) and/or other signals caused by electromagnetic energy that may otherwise by present in the locate area (e.g., AM broadcast radio) that may energize conductive utility lines. Whereas passive locating may allow for the detection of utility lines not actively energized by a transmitter, such methods and associated utility locator devices often fail to be able to use sensed signals to distinguish a target utility line or lines from others present in the area of interest. Few utility locator devices known in the art may be configured for using principal component analysis (PCA) or like techniques for blind signal separation or detection allowing different utility lines to be distinguished from one another. Such utility locator devices may still suffer from problems related to human error as well as still being constrained by the ability of the operator to adequately walk distances throughout the area of interest. Such problems may be profound where the area of interest is large and/or dangerous for humans to access on foot such as busy roadways and intersections. Likewise, those utility locator devices known in the art configured for blind signal detection via PCA or like principal component based techniques are all optimized for being carried by and at human speeds of travel.

Few solutions known in the art suggest vehicle-based electromagnetic locating devices that may include one or more utility locator devices coupled to or built into a vehicle for purposes of sensing electromagnetic signals and determining the location of and mapping utility lines. Whereas such solutions mitigate the hazards associated with entering busy roadways or intersections on foot as well as facilitate ease in traveling distances across large areas of interest, there is a great deal of room to optimize vehicle-based locating solutions. In particular, vehicle-based solutions known in the art either completely fail to distinguish a target utility line or lines from others present in the area of interest or fail to optimize such blind signal separation/detection methods and associated devices. <CIT> describes systems and methods for uniquely identifying buried utilities in a multi-utility region. The system and methods may include sensing magnetic fields upon moving a magnetic field sensing locating device over a multi-utility region comprising a plurality of buried utilities. The sensed magnetic fields may be used to identify a plurality of location data points each indicative of location information pertaining to one or more buried utilities. Based on these location data points, a plurality of clusters may be generated where each cluster may include a set of location data points sharing common characteristics. The generated clusters may exhibit one or more patterns which may be identified and subsequently utilized for classifying the clusters to uniquely identify the buried utilities.

Accordingly, there is a need in the art to address the above-described as well as other problems.

This disclosure relates generally to systems for locating and mapping buried utility lines. More specifically but not exclusively, the present disclosure relates generally to vehicle-based systems using principal components for locating and mapping buried utility lines.

For example, in one aspect the disclosure relates to a vehicle-based utility locating device for use with a vehicle, such as an automobile, truck, or other vehicle, according to claim <NUM>.

In another aspect the present disclosure relates to a principal component based method for determining the position of and mapping of utility lines with a vehicle-based utility locating device disposed on a vehicle according to claim <NUM>.

Various additional aspects, features, and functionality are further described below in conjunction with the appended Drawings.

The present application may be more fully appreciated in connection with the following detailed description taken in conjunction with the accompanying drawings, wherein:.

The terms "utility lines," "utilities," or "buried utilities" as used herein refers not only to utilities below the surface of the ground, but also to utilities that are otherwise obscured, covered, or hidden from direct view or access (e.g. overhead power lines, underwater utilities, and the like). In a typical application a buried utility is a pipe, cable, conduit, wire, or other object buried under the ground surface, at a depth of from a few centimeters to meters or more, that a user, such as a utility company employee, construction company employee, homeowner or other wants to locate, map (e.g., by surface position as defined by latitude/longitude or other surface coordinates, and/or also by depth), measure, and/or provide a surface mark corresponding to it using paint, electronic marking techniques, images, video or other identification or mapping techniques.

The term "utility data" as used herein, may include, but is not limited to, data pertaining to presence or absence, position, depth, current flow, magnitude, phase, and/or direction, and/or orientation/pose of underground utility lines. The utility data may include a plurality of location data points each indicative of location information pertaining to a buried utility (interchangeably referred to as a "buried utility line") and associated characteristics of the buried utility. The utility data may also include data received from various sensors and systems, such as inertial navigation system (INS) sensors, motion sensors, light detection and radar (LiDAR), systems and sensors and methods relating to simultaneous localization and mapping (SLAM), and other sensors provided within or coupled to the vehicle-based utility locating devices and/or human-portable utility locator devices described herein. The utility data may be in the form of magnetic field signals emitted by utility lines.

The term "area of interest" refers to a geographic region or area that has been or may be scanned for the presence or absence of utility lines buried in the ground. In the present disclosure, such an area of interest may be scanned via a vehicle-based utility locating device embodiment.

The term "magnetic field signals" or "magnetic fields" as used herein may refer to radiation of electromagnetic energy at the area of interest. The magnetic field signals may further refer to radiation of electromagnetic energy from remote transmission sources measurable within the locate area, typically at two or more points. For example, an AM broadcast radio tower used by a commercial AM radio station may transmit a radio signal from a distance that is measurable within the locate operation area.

The term "signal content" may refer to measureable aspects or qualities of the sampled magnetic signals. Such signal content may include, but should not be limited to, measures of signal power, frequency, position including orientation/pose and depth of the measured signal/utility lines. In some method embodiments of the present disclosure, signal content may be used to group signals across the frequency band series together as belonging to the same utility line or other signal source. In further method embodiments, the signal content belonging to the same utility line or other signal source may be used to classify the type of utility.

The term "computing device" as used herein refers to any device or system that can be operated or controlled by electrical, optical, or other outputs from a user interface device. Examples of user electronic devices include, but are not limited to, vehicle-mounted display devices, navigation systems such as global positioning system receivers, personal computers, notebook or laptop computers, personal digital assistants (PDAs), cellular phones, computer tablet devices, electronic test or measurement equipment including processing units, and/or other similar systems or devices.

As used herein, the term "mapping data" refers to imagery, diagrams, graphical illustrations, line drawings or other representations depicting the attributes of a location, which may include maps or images containing various dimensions (i.e. two dimensional maps or images and/or three dimensional maps or images). These may be vector or raster objects and/or combinations of both. Such depictions and/or representations may be used for navigation and/or relaying information associated with positions or locations, and may also contain information associated with the positions or locations such as coordinates, information defining features, images or video depictions, and/or other related data or information. For instance, the spatial positioning of ground surface attributes may be depicted through a series of photographs or line drawings or other graphics representing a location. Various other data may be embedded or otherwise included into maps including, but not limited to, reference coordinate information such as latitude, longitude, and/or altitude data, topographical information, virtual models/objects, information regarding buried utilities or other associated objects or elements, structures on or below the surface, and the like. The maps may depict a probability contour indicative of likelihood of presence of the buried utilities at a probable location, and other associated information such as probable orientation and depth of the buried utilities. Alternatively or additionally, the map may depict optimized locations of the buried utilities along with associated information such as orientation/pose and depth of the buried utilities.

As used herein, the term, "exemplary" means "serving as an example, instance, or illustration. " Any aspect, detail, function, implementation, and/or embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other aspects and/or embodiments.

The present disclosure relates generally to systems for locating and mapping buried utility lines. More specifically but not exclusively, the present disclosure relates generally to vehicle-based systems using principal components for locating and mapping buried utility lines.

In one aspect, the present disclosure relates to a vehicle-based utility locating device for identifying and mapping buried utilities. The vehicle-based utility locating device includes a position element including one or more GNSS antennas and associated receivers to determine position data of the vehicle-based utility locating device in the world frame as well as a utility locating element for sensing electromagnetic signals and using the sensed electromagnetic signals to determine the presence and location or absence of buried utility lines. The utility locating element further includes an antenna array to sense magnetic fields emitted from one or more buried utilities as the utility locating element is moved through an area of interest and provide antenna array output signals corresponding to the sensed magnetic fields. The vehicle-based utility locating device further includes a receiver element having a receiver input to sample the antenna array output signals and provide receiver output signals corresponding to the sensed magnetic fields. The receiver element may sample the output signals at <NUM> or faster. A processing element having one or more processors coupled to the receiver element is configured to receive the receiver output signals and determine principal components in a plurality of frequency bands where the frequency bands may be organized into one or more series of spaced apart frequency bands and output data signals representing one or more field vectors corresponding to the eigenvector and eigenvalues of the principal components which may be further correlated with position data. The frequency bands may have a bandwidth of <NUM> or less. The frequency bands may, in some embodiments, be evenly spaced apart. In other embodiments, variable spacing in one or more series of frequency bands may be used and/or other frequency band spacing schemes. Each frequency band may be calibrated about the mid-point of the band. The vehicle-based utility locating device further includes a memory element comprising one or more non-transitory memories for storing output data values, signal data, position and mapping data, and instructions relating to methods for determining principal components and/or other methods for determining and mapping utility locations methods and a communication element comprising one or more radio transceivers to communicate data including output data values, signal data, position data, and other data relating to determining and mapping utility locations methods to a computing device. The vehicle-based utility locating devices described herein may be used in combination with narrow band filter. Likewise, the vehicle-based utility locating devices described herein may be used with wide band radio broadcast signals.

In another aspect, the vehicle-based utility locating device of the present disclosure utilizes the field vector at each of the frequency bands to distinguish between different utility lines or other signal sources originating from the same object. Likewise, the utility type of the various determined utility lines is further classified, for example, via the signal content (e.g., measures of frequency, power, position and depth in the ground, and/or orientation/pose of the signals associated with each utility line), optionally relative to the other frequencies or the same frequency at different times.

In another aspect, the utility locating element of vehicle-based utility locating devices of the present disclosure may be or include one or more human portable utility locator devices. In some embodiments, the utility locating element of the vehicle-based utility locating device, which may be or include one or more human portable utility locator devices, as well as other device elements may be removably coupled to a vehicle. In other embodiments, the utility locating and various other elements of the vehicle-based utility locating device may instead be built into, or integrated onto, the vehicle.

In another aspect, the present disclosure relates to a principal component based method for determining the position of and mapping utility lines via a vehicle-based utility locating device. The method includes sensing magnetic signals at a plurality of antennas as the vehicle-based locating device traverses an area of interest. A receiver element samples the magnetic signals at <NUM> or faster. The method further includes determining principal components for a plurality of frequency bands, which may be organized into one or more series of spaced apart frequency bands, which optionally may be evenly spaced apart, and further determining field vectors which may be characterized by the eigenvector optionally having the largest absolute eigenvalue of the previously determined principal components for each frequency band. The method further includes separating field vectors from the various frequency bands into different utility lines and/or other signal sources originating from the same object. From the separated utility lines, the method further includes classifying utility lines into different utility line types based on eigenvector patterns. Position data is determined by the vehicle-based utility locating device and such position data is further correlated with utility line data. Such position data may include positions and related data produced via global navigation satellite system (GNSS) and may further include data produced via other position sensors and systems including, but not limited to, inertial navigation system (INS) sensors, light detection and ranging (LiDAR), wheel counting mechanisms or other ground tracking mechanism, and/or other like sensors/systems. Further, such position data may include that generated via sensors and methods associated with simultaneous localization and mapping (SLAM). Utility line and correlated position data is further stored on one or more non-transitory memories. The method further includes communicating data to a computing device for processing and/or displaying of data that includes mapped utility lines. Likewise, the data may be communicated to one or more cloud computing devices.

In another aspect, the present disclosure relates to a method for determining the principal component across a plurality of frequency bands as used in locating and mapping utility lines. The method may include sampling magnetic signals at a plurality of antennas, performing Principal Component Analysis to produce eigenvectors with associated eigenvalues wherein the dimensionality of the eigensystem is characterized by the quantity of antennas sampled for a plurality a frequency bands, and finding the principal components which may be characterized by the dominant eigenvector optionally having the eigenvalue with the greatest absolute value. The frequency bands may be organized into one or more series of spaced apart frequency bands. The frequency bands may, in some embodiments, be evenly spaced apart. In other embodiments, variable spacing in one or more series of frequency bands may be used.

In another aspect, the present disclosure relates to another method for determining the principal component across a plurality of frequency bands as used in locating and mapping utility lines. The method may include sampling magnetic signals at a plurality of antennas, performing Principal Component Analysis to produce eigenvectors with associated eigenvalues wherein the dimensionality of the eigensystem is characterized by the quantity of antennas sampled for a plurality a frequency bands, and finding the principal components which may be characterized by one or more eigenvectors in each frequency band prioritized by corresponding eigenvalues.

In another aspect, the present disclosure relates to a computationally efficient method for determining the principal component across a plurality of frequency bands as used in locating and mapping utility lines which may optionally be used for near real-time display. The method may include sampling magnetic signals at a plurality of antennas, optionally performing Power Iteration Method or Inverse Power Method or other similar technique to determine the eigenvector of each first principal component in a plurality of frequency bands, and optionally using the Rayleigh quotient to determine eigenvalue corresponding to each eigenvector. The frequency bands may be organized into one or more series of individual frequency bands.

In another aspect, the present disclosure relates to another computationally efficient method for determining the principal component across a plurality of frequency bands as used in locating and mapping utility lines. The method may include sampling magnetic signals at a plurality of antennas, optionally performing Power Iteration Method or Inverse Power Method or other similar technique to determine one or more eigenvectors for each frequency band prioritized by their corresponding eigenvalues, and optionally using the Rayleigh quotient to determine eigenvalue corresponding to each eigenvector.

In another aspect the disclosure relates to a vehicle-based utility locating device for use with a vehicle, such as an automobile, truck, or other vehicle. The locating device includes:
a positioning element including one or more GNSS antennas and associated receivers to receive positioning signals and determine position data of the vehicle-based utility locating device in a world frame, a utility locating element for determining the presence and location or absence of buried utility lines, including: an antenna array to receive AC magnetic fields emitted from one or more buried utilities as the utility locating element is moved through an area of interest and provide antenna array output signals corresponding to the sensed AC magnetic fields; a receiver element having a receiver input operatively coupled to the antenna array output to sample the antenna array output signals and provide, at a receiver output, receiver output signals corresponding to the sensed AC magnetic fields; and a processing element, including one or more processors, operatively coupled to the receiver element receiver output to: receive the receiver output signals and determine principal component values in a plurality of frequency bands; and output data signals representing one or more field vectors corresponding to the eigenvector and eigenvalues of the principal component values so as to be correlated with the position data. The locating device also includes a memory element comprising one or more non-transitory memories for storing output data values, signal data, position and mapping data, and instructions to implement a signal processing method for determining and mapping utility locations on a communicatively coupled processing element, a communication element comprising one or more radio transceivers to communicate data including at least output data values, signal data, and position data relating to determining and mapping utility locations to a communicatively coupled computing device, and a power element to provide electrical power to one or more of the positioning element, the utility locating element, the memory element, and the communication of the vehicle-based utility locating device.

Ones of frequencies in the plurality of frequency bands may, for example, be spaced-apart in one or more series of frequency bands. The antenna array output signals may be sampled at speeds of <NUM> or faster. Each frequency band may have a bandwidth of <NUM> or less. Each frequency band may be calibrated at the mid-point of the band. The contents of the frequency bands may be used to provide data defining two or more different utility lines. The contents of the frequency bands may be used to provide data classifying two or more different utility lines. The utility locating element may be or may include one or more human portable utility locator devices mechanically coupled to the vehicle. One or more of the elements of the vehicle-based utility locating device may be removably coupled to the vehicle or alternately may be built into the vehicle.

In another aspect the present disclosure relates to a principal component based method for determining the position of and mapping of utility lines with a vehicle-based utility locating device disposed on a vehicle. The method includes:
sensing AC magnetic field signals at a plurality of antennas of the vehicle-based locating device as the vehicle traverses an area of interest and providing antenna output signals corresponding to the sensed AC magnetic field signals, receiving and sampling the antenna output signals at a receiver element at a rate of <NUM> or faster, determining principal component values for a plurality of spaced apart frequency bands based on the sample antenna output signals, determining field vectors characterized by the eigenvector having the largest absolute eigenvalue of the previously determined principal components for each frequency band, separating field vectors from the various frequency bands into different utility lines and/or other signal sources originating from the same object, classifying utility lines into different utility line types based on the separate field vectors, determining position data, correlating utility line data and position data, storing correlated line data and position data, and communicating the correlated line and position data to a computing device for processing and/or displaying of data that includes mapped utility lines. The frequency bands may be arranged into one or more series of evenly spaced apart frequency bands.

In another aspect, the disclosure relates to a method for determining principal components used in utility locating. The method includes:
receiving AC magnetic field signals at a plurality of antennas, sampling the received AC magnetic field signal, implementing a principal components analysis algorithm to produce eigenvectors and associated eigenvalues, wherein the dimensionality of the eigensystem is characterized by the quantity of antennas sampled for a plurality of frequency bands, and determining a set of principal components characterized by the dominant eigenvector having the eigenvalue with the largest absolute value in each frequency band.

In another aspect, the disclosure relates to a method for determining principal components used in utility locating, with a vehicle-based utility locating system. The method includes:
receiving AC magnetic field signals emitted from one or more utilities at a plurality of antennas, sampling the received AC magnetic field signals, implementing a principal components analysis algorithm to produce eigenvectors and associated eigenvalues, wherein the dimensionality of the eigensystem is characterized by the quantity of antennas sampled for a plurality of frequency bands, and determining principal components characterized by one or more eigenvectors in each frequency band prioritized by their corresponding eigenvalues.

In another aspect, the disclosure relates to a method for determining principal components used in utility locating, with a vehicle-based utility locating system. The method includes:
receiving AC magnetic field signals emitted from one or more utilities at a plurality of antennas, sampling the received AC magnetic field signals using the power iteration method or inverse power method to determine an eigenvector of each first principal component in a plurality of frequency bands, and determining the eigenvalue corresponding to each eigenvector using the Rayleigh quotient.

In another aspect, the disclosure relates to a method for determining principal components used in utility locating, with a vehicle-based utility locating system. The method includes:
receiving AC magnetic field signals emitted from one or more utilities at a plurality of antennas, sampling the received AC magnetic field signals, processing the sampled AC magnetic field signals using the power iteration method or inverse power method to determine one or more eigenvectors in each of a plurality of frequency bands where the eigenvectors are prioritized by their corresponding eigenvalues, and determining the eigenvalue corresponding to each eigenvector using the Rayleigh quotient.

In another aspect, the disclosure relates to a principal component based method for separating magnetic signals into different utility lines or other signal sources. The method includes:
determining principal components across a plurality of frequency bands from sampled magnetic signals received at a plurality of antennas from utility lines, determining field vectors which may be characterized by the eigenvector optionally having the largest absolute value in each frequency band, evaluating similarities and differences in signal content associated with each field vector at each of the plurality of frequency bands, separating field vectors from the various frequency bands into the same utility line and/or other signal source where similarities exist in signal content to within a predetermined threshold, and comparing spatially separated measurement to identify similar eigenvector patterns across frequency bands to match signals to a target utility.

The frequency bands may, for example, be organized into one or more series of evenly spaced apart frequency bands. The signal content may include a measure of signal power of the utility line/signal source. The signal content may include a measure of signal frequency of the utility line/signal source. The signal content may include a measure of position of the utility line/signal source. The signal content may include a measure of orientation/pose of the utility line/signal source.

In another aspect, the disclosure relates to a principal component based method for classifying utility lines via a vehicle-based utility locating device. The method includes:
determining principal components across one or more series of frequency bands from sampled AC magnetic signals emitted from one or more utilities and received at a plurality of antennas, determining field vectors characterized by the eigenvector having the largest absolute value in each frequency band, identifying separate utility lines by evaluating similarities and differences in signal content based on the field vectors, comparing signal content associated with each individual utility line to a predefined lookup table containing data associating signal content to utility types, and assigning a utility type to each separate utility line based upon fitting lookup table criteria to within a predefined threshold.

In another aspect, the present disclosure relates to a principal component based method for separating magnetic signals into different utility lines or other signal sources originating from the same object. The method includes determining principal components across a plurality of frequency bands, which may be organized into one or more series of spaced apart frequency bands, from sampled magnetic signals received at a plurality of antennas from utility lines and further determining field vectors which may be characterized by the eigenvector optionally having the largest absolute value in each frequency band. In some embodiments, the frequency bands may be evenly spaced apart. In other embodiments, other frequency band schemes may be used including but not limited to the use of variable spacing in one or more series of frequency bands. The method may further include evaluating similarities and differences in signal content associated with each field vector at each of the plurality of frequency bands. Such signal content may include, but should not be limited to, measures of position/location, depth, orientation/pose, signal power, and/or frequency of the utility line/signal source. Further, the method includes separating field vectors from the various frequency bands into the same utility line and/or other signal source where similarities exist in signal content to within a predetermined threshold. The method further may include comparing spatially separated measurements to identify similar eigenvector patterns across frequency bands to match signals to a target utility.

In another aspect, the present disclosure relates to a principal component based method for classifying utility lines via vehicle-based utility locating device. The method includes determining principal components across a plurality of frequency bands, which may be organized into a plurality of frequency bands, from sampled magnetic signals received at a plurality of antennas from utility lines and further determining field vectors which may be characterized by the eigenvector optionally having the largest absolute value in each frequency band. The method may include identifying separate utility lines by evaluating similarities and differences in signal content. Such signal content may include, but should not be limited to, measures of position/location, depth, orientation/pose, signal power, and/or frequency of the utility line/signal source. The method may further include comparing signal content associated with each individual utility line to a lookup table containing data relating signal content to utility types and assigning utility type to each separate utility line based upon fitting lookup table criteria to within a threshold.

Various additional aspects of the present disclosure are described subsequently herein.

The following exemplary embodiments are provided for the purpose of illustrating examples of various aspects, details, and functions of the present disclosure; however, the described embodiments are not intended to be in any way limiting.

Turning to <FIG> and <FIG>, a vehicle-based utility locating device <NUM> is illustrated that may be secured to a vehicle <NUM>. The vehicle-based utility locating device <NUM> includes a position element <NUM> including one or more GNSS antennas and associated receivers, such as the GNSS antennas/receivers <NUM>, to determine position data of the vehicle-based utility locating device in the world frame. Likewise, the position element may include one or more other sensors or systems to determine position. For instance, as illustrated in <FIG>, the position element <NUM> may further include one or more inertial navigation system (INS) sensors <NUM> that includes gyroscopic sensors, accelerometers, magnetometers, or the like and/or other position sensors <NUM> for determining movement or position in the world frame (e.g., light detection and radar (LiDAR) systems, other rangefinders, optical or mechanical ground tracking devices, or the like as well as systems, sensors, and methods associated with simultaneous localization and mapping (SLAM) or similar techniques). Different position sensors and systems may be included in other vehicle-based utility locating device embodiments in keeping with the present disclosure.

The vehicle-based utility locating device <NUM> further includes a utility locating element <NUM> for sensing electromagnetic signals that may be emitted by one or more utility lines that may be buried in the ground and use the sensed electromagnetic signals to determine the presence and location or absence of buried utility lines. In the vehicle-based utility locating device <NUM>, the utility locating element <NUM> may be or include one or more human-portable utility locator devices <NUM> such as those described in the patent applications including, but not limited to, <CIT>, entitled A BURIED OBJECT LOCATING AND TRACING METHOD AND SYSTEM EMPLOYING PRINCIPAL COMPONENTS ANALYSIS FOR BLIND SIGNAL DETECTION; <CIT>, entitled GRADIENT ANTENNA COILS AND ARRAYS FOR USE IN LOCATING SYSTEMS; <CIT>, entitled BURIED OBJECT LOCATOR APPARATUS AND SYSTEMS; and <CIT>, entitled UTILITY LOCATORS WITH RETRACTABLE SUPPORT STRUCTURES AND APPLICATIONS THEREOF.

As shown in greater detail in <FIG>, each human-portable utility locator device <NUM> may include an antenna node <NUM> to sense magnetic fields <NUM> (<FIG> and <FIG>) emitted from one or more buried utility lines such as utility line <NUM> (<FIG> and <FIG>) as the vehicle-based utility locating device <NUM> (<FIG> and <FIG>) is moved through an area of interest. Further illustrated in <FIG>, the antenna node <NUM> (<FIG> and <FIG>) may house a dodecahedral array of antennas <NUM>. In other vehicle-based utility locating device or utility locator device embodiments, a different number of antennas may be used that may be arranged in different ways.

Further illustrated in <FIG>, the utility locator device <NUM> further includes a position element <NUM> comprising one or more systems and sensors to determine position and movement. For instance, the utility locator device <NUM> may include a position element <NUM> that may include an array of GNSS antennas and associated receivers to receive satellite navigation signals and determine positions of the utility locator devices <NUM> in the world frame. Likewise, the position element <NUM> of the utility locator device <NUM> may include a variety of other position sensors/systems including, but not limited to, one or more accelerometers, gyroscopes, magnetometers, altimeters, other inertial sensors, LiDAR or other rangefinders, optical or mechanical ground tracking apparatus, or the like as well as systems, sensors, and methods associated with SLAM and/or other methods and systems. Such position data may be further correlated with utility line data and displayed on a display <NUM> on each utility locator device <NUM> and/or a computing device <NUM> (<FIG> and <FIG>) to communicate mapped utility line data to a user. Likewise, such data may be communicated to one or more cloud computing devices <NUM> for storage, processing, mapping of utility and related data, providing data for display, and/or the like.

In use in the vehicle-based utility locating device <NUM>, as illustrated in <FIG>, the position elements <NUM> of each utility locator device <NUM> may be used for positioning in conjunction with the position element <NUM> of the vehicle-based utility locating device <NUM>. Likewise, the positioning may be done solely in the positioning element <NUM> of the vehicle-based utility locating device <NUM> or solely in the position elements <NUM> of each utility locator device <NUM>.

Further illustrated in <FIG>, each utility locator device <NUM> includes a memory element <NUM> comprising one or more non-transitory memories for storing output data values, signal data, position and mapping data, and instructions relating to PCA or other methods for determining principal components and mapping utility locations methods and/or function of the utility locator device <NUM>. The utility locator device <NUM> further includes a communication element <NUM> comprising one or more radio transceivers for communicating data with the vehicle-based utility locating device <NUM> and/or other devices such as the computing device <NUM> or remote cloud based devices such as the cloud computing device(s) <NUM>. For instance, the communication element <NUM> may be or include a <NUM> or like cellular radio transceiver to communicate such data. Each human-portable utility locator devices <NUM> may further include a battery <NUM> for providing electrical power to the various powered elements of the human-portable utility locator devices <NUM>. In some embodiments, such electrical power may be provided to each human-portable utility locator devices <NUM> from the vehicle-based utility locating device <NUM> or vehicle <NUM>.

Further illustrated in <FIG>, the antennas <NUM> of antenna node <NUM> may provide antenna array output signals <NUM> corresponding to the sensed magnetic fields <NUM> from utility line <NUM>. The magnetic field <NUM> signals may, in some embodiments, include that caused by wide band radio broadcast signals coupling to the utility line <NUM>. A receiver element <NUM> comprising one or more receivers may receive the antenna array output signals <NUM>. The receiver element <NUM> may include one or more filters and signal conditioners to receive the antenna array output signals <NUM> and generate receiver output signals <NUM>. For instance, such filters may be or include narrow band filter (not illustrated). The receiver output signals <NUM> may be sampled at a processing element <NUM> at <NUM> or faster. The processing element <NUM>, comprising one or more processors, is configured to receive the receiver output signals <NUM> and determine principal components frequency bands which may be organized into one or more frequency bands such as the frequency band scheme <NUM> of <FIG> or the frequency band scheme <NUM> of <FIG> or other frequency band scheme. Such processing may instead be or be shared by a processing element <NUM> otherwise disposed in the vehicle-based utility locating device <NUM> and/or a processing element disposed in a connected computing device <NUM> in real-time, near real-time, or in post processing. Likewise, such data may be communicated to one or more cloud computing devices <NUM> for storage, processing, mapping of utility and related data, providing data for display, and/or the like via a communication element <NUM> in the vehicle-based utility locating device <NUM>. For instance, the communication element <NUM> may be or include a <NUM> or like cellular radio transceiver to communicate such data. The processing element <NUM>, processing element <NUM>, or other connected processing element may generate output data signals representing one or more field vectors corresponding to the eigenvector and eigenvalues of the principal components which may be further correlated with position data from the position element <NUM> and/or position element <NUM> of the utility locator devices <NUM>. For instance, the processing element <NUM>, processing element <NUM>, or other connected processing element may carry out the method <NUM> of <FIG>, method <NUM> of <FIG>, method <NUM> of <FIG>, method <NUM> of <FIG>, method <NUM> of <FIG>, method <NUM> of <FIG>, and/or method <NUM> of <FIG> to determine and map utility lines using principal components that may be used with the vehicle-based utility locating devices of the present disclosure.

The vehicle-based utility locating devices in keeping with the present disclosure further include a memory element, such as the memory element <NUM> of vehicle-based utility locating device <NUM> of <FIG>, comprising one or more non-transitory memories for storing output data values, signal data, position and mapping data, and instructions relating to PCA or other methods for determining principal components and mapping utility locations methods. In some embodiments, such a memory element may instead be disposed in a human portable utility locator device such as the memory element <NUM> of the human portable utility locator device <NUM>. The vehicle-based utility locating device <NUM> of <FIG> includes a communication element <NUM> comprising one or more radio transceivers to communicate data including output data values, signal data, position data, and other data relating to determining and mapping utility locating methods to a computing device such as computing device <NUM> as well as the utility locator devices <NUM> or remote cloud based devices such as the cloud computing device(s) <NUM>. Further, a power element <NUM> may provide electrical power to the various powered elements of the vehicle-based utility locating device <NUM>. In some embodiments, such electrical power may be provided to the vehicle-based utility locating device <NUM> from the vehicle <NUM>.

Turning to <FIG> and <FIG>, a vehicle-based utility locating device <NUM> in keeping with the present disclosure is illustrated that may be built into a vehicle <NUM>. The vehicle-based utility locating device <NUM> includes a position element <NUM> including one or more GNSS antennas and associated receivers, such as the GNSS antennas/receivers <NUM>, to determine position data of the vehicle-based utility locating device in the world frame. Likewise, the position element may include one or more other sensors or systems to determine position. For instance, as illustrated in <FIG>, the position element <NUM> may further include one or more inertial navigation system (INS) sensors <NUM> that includes gyroscopic sensors, accelerometers, magnetometers, or the like and/or other position sensors <NUM> for determining movement or position in the world frame (e.g., light detection and radar (LiDAR) systems, other rangefinders, optical or mechanical ground tracking devices, or the like and/or system, sensors, and methods associated with SLAM or the like). Different position sensors and systems may be included in other vehicle-based utility locating device embodiments in keeping with the present disclosure.

The vehicle-based utility locating device <NUM> further includes a utility locating element <NUM> for sensing electromagnetic signals that may be emitted by one or more utility lines <NUM> that may be buried in the ground and use the sensed electromagnetic signals <NUM> to determine the presence and location or absence of buried utility lines <NUM>. In the vehicle-based utility locating device <NUM>, the utility locating element <NUM> may be or include one or more antenna nodes <NUM> configured to sense electromagnetic signals <NUM> as the vehicle-based utility locating device <NUM> is moved through an area of interest. Each antenna node <NUM> may house a dodecahedral array of antennas <NUM> (<FIG>), which may be or share aspects with the dodecahedral array of antennas <NUM> illustrated in <FIG>, or other arrangement/quantity of antennas.

Further illustrated in <FIG>, the antennas <NUM> of antenna node <NUM> may provide antenna array output signals <NUM> corresponding to the sensed magnetic fields <NUM> from utility line <NUM>. A receiver element <NUM> comprising one or more receivers may receive the antenna array output signals <NUM>. The receiver element <NUM> may include one or more filters and signal conditioners to receive the antenna array output signals <NUM> and generate receiver output signals <NUM>. The receiver output signals <NUM> may be sampled at a processing element <NUM> at <NUM> or faster. The processing element <NUM>, comprising one or more processors, is configured to receive the receiver output signals <NUM> and determine principal components for a plurality of frequency bands which may be organized into one or more frequency bands such as the frequency band scheme <NUM> of <FIG> or the frequency band scheme <NUM> of <FIG> or other frequency band schemes. Such processing may instead be or be shared by a processing element disposed in a connected computing device <NUM> in real-time, near real-time, or in post processing. The processing element <NUM>, or other connected processing element may generate output data signals representing one or more field vectors corresponding to the eigenvector and eigenvalues of the principal components which may be further correlated with position data from the position element <NUM>. For instance, processing element <NUM> and/or other connected processing element may carry out the method <NUM> of <FIG>, method <NUM> of <FIG>, method <NUM> od <FIG>, method <NUM> of <FIG>, method <NUM> of <FIG>, method <NUM> of <FIG>, and/or method <NUM> of <FIG> to determine and map utility lines using principal component analysis (PCA) that may be used with the vehicle-based utility locating devices of the present disclosure.

The vehicle-based utility locating device <NUM> may include a memory element <NUM> comprising one or more non-transitory memories for storing output data values, signal data, position and mapping data, and instructions relating to PCA or other methods for determining principal components and mapping utility locations methods. The vehicle-based utility locating device <NUM> may further a communication element <NUM> comprising one or more radio transceivers to communicate data including output data values, signal data, position data, and other data relating to determining and mapping utility locations methods to a computing device such as computing device <NUM>. Likewise, such data may be communicated to one or more cloud computing devices <NUM> for storage, processing, mapping of utility and related data, and/or the like. Further, a power element <NUM> may provide electrical power to the various powered elements of the vehicle-based utility locating device <NUM>. In some embodiments, such electrical power may be provided to the vehicle-based utility locating device <NUM> from the vehicle <NUM>.

Turning to <FIG>, an exemplary frequency band scheme <NUM> is illustrated having a number of frequency band series 410a, 410b, 410c, and 410d. Each frequency band series 410a, 410b, 410c, and 410d may have a plurality of individual frequency bands <NUM>. Each frequency band <NUM> may be approximately evenly spaced apart in the respective frequency band series 410a, 410b, or 410c. For instance, each frequency band <NUM> may have a bandwidth of <NUM> or less and may be calibrated about a midpoint <NUM> of each frequency band <NUM>. In frequency band scheme <NUM>, for instance, the individual frequency bands <NUM> of frequency band series 410a may each be <NUM> / <NUM> wide ranging from <NUM> - <NUM>. The individual frequency bands <NUM> of frequency band series 410b may each be <NUM> wide ranging from <NUM> - <NUM>. Further, the individual frequency bands <NUM> of frequency band series 410c may each be <NUM> wide ranging from <NUM> - <NUM>. The frequency band series 410d may include frequencies greater than <NUM>.

Turning to <FIG>, another exemplary frequency band scheme <NUM> is illustrated having a single frequency band series <NUM>. The frequency band series <NUM> may have a plurality of individual frequency bands <NUM>. Each frequency band <NUM> may be approximately evenly spaced apart in the frequency band series <NUM>. For instance, each frequency band <NUM> may have a bandwidth of <NUM> or less and may be calibrated about a midpoint <NUM> of each frequency band <NUM>. In frequency band scheme <NUM>, the individual frequency bands <NUM> may each be <NUM> wide ranging from <NUM> - <NUM> and may further include frequency bands <NUM> having frequencies greater than <NUM>.

It should be noted that other frequency band schemes may be used with the vehicle-based utility locating devices in keeping with the present disclosure besides those described in frequency band scheme <NUM> of <FIG> and frequency band scheme <NUM> of <FIG>. For instance, some frequency schemes may include variable spacing in one or more series of frequency bands.

Turning to <FIG>, a principal component based method <NUM> for determining the position of and mapping utility lines that is used with a vehicle-based utility locating device of the present disclosure is described. In a first step <NUM>, magnetic signals may be sensed at a plurality of antennas as the vehicle-based locating device traverses an area of interest. In a step <NUM>, the magnetic signals may be sampled by a receiver element at <NUM> or faster. In a step <NUM>, principal components are determined for a plurality of frequency bands. Such frequency bands may, in some embodiments, be evenly spaced apart in one or more sets of frequency bands. In other embodiments, other types of frequency band schemes may be used. For instance, variable spacing in one or more series of frequency bands may be used in some embodiments. The principal components of step <NUM> may, for instance, be found through the method <NUM> of <FIG>, method <NUM> of <FIG>, method <NUM> of <FIG>, or method <NUM> of <FIG>. In a step <NUM>, field vectors which may be characterized by the eigenvector optionally having the largest absolute eigenvalue of the previous step may be determined from the principal components for each frequency band. In a step <NUM>, field vectors from the various frequency bands are separated into different utility lines and/or other signal sources originating from the same object. The step <NUM> may, for instance, utilize the principal component based method <NUM> for separating magnetic signals into different utility lines or other signal sources originating from the same object described in <FIG>. In a step <NUM>, utility lines are classified into different utility line types. In a step <NUM>, position data may be determined. The step <NUM> may, for instance, use the principal component based method <NUM> for classifying utility lines described with <FIG>. In a step <NUM>, utility line data may be correlated with position data. In a step <NUM>, utility line data and position data may be stored in one or more non-transitory memories. In a step <NUM>, data may be communicated to a computing device for processing and/or displaying of data that includes mapped utility lines.

Turning to <FIG>, a method <NUM> for determining principal components for use in locating and mapping utility lines is described. In a first step <NUM>, the method <NUM> may include sampling the magnetic signal at a plurality of antennas. For instance, in the dodecahedral array of antennas <NUM> of the antenna node <NUM> illustrated in <FIG>, magnetic signal may be sampled at all twelve antennas <NUM>. In another step <NUM>, the method <NUM> may further include performing Principal Components Analysis producing eigenvectors and associated eigenvalues wherein the dimensionality of the eigensystem is characterized by the quantity of antennas sampled for a plurality of frequency bands. Such frequency bands may, in some embodiments, be evenly spaced apart in one or more sets of frequency bands. In other embodiments, other types of frequency band schemes may be used. For instance, variable spacing in one or more series of frequency bands may be used in some embodiments. In a step <NUM>, the principal components which may be characterized by the dominant eigenvector optionally having the eigenvalue with the largest absolute value may be found for each frequency band. The method <NUM> may repeat throughout the area of interest.

Turning to <FIG>, a method <NUM> for determining principal components for use in locating and mapping utility lines is described. In a first step <NUM>, the method <NUM> includes sampling the magnetic signal at a plurality of antennas. For instance, in the dodecahedral array of antennas <NUM> of the antenna node <NUM> illustrated in <FIG>, magnetic signal may be sampled at all twelve antennas <NUM>. In another step <NUM>, the method <NUM> further includes performing Principal Components Analysis producing eigenvectors and associated eigenvalues wherein the dimensionality of the eigensystem is characterized by the quantity of antennas sampled for a plurality of frequency bands. Such frequency bands may, in some embodiments, be evenly spaced apart in one or more sets of frequency bands. In other embodiments, other types of frequency band schemes may be used. For instance, variable spacing in one or more series of frequency bands may be used in some embodiments. In a step <NUM>, the principal components which may be characterized by one or more eigenvectors in each frequency band where the eigenvectors are prioritized by their corresponding eigenvalues. The method <NUM> may repeat throughout the area of interest.

Turning to <FIG>, a computationally-efficient method <NUM> for determining principal components for use in utility locating is described. In a step <NUM> the method <NUM> includes sampling the magnetic signal at a plurality of antennas. For instance, in the dodecahedral array of antennas <NUM> of the antenna node <NUM> illustrated in <FIG>, magnetic signal may be sampled at all twelve antennas <NUM>. In another step <NUM>, the Power Iteration Method or Inverse Power Method may be used to determine the eigenvector of each first principal component in a plurality of frequency bands. Such frequency bands may, in some embodiments, be evenly spaced apart in one or more sets of frequency bands. In other embodiments, other types of frequency band schemes may be used. For instance, variable spacing in one or more series of frequency bands may be used. In a step <NUM>, the Rayleigh quotient may be used to determine the eigenvalue corresponding to each eigenvector of step <NUM>. The method <NUM> may repeat throughout the area of interest.

Turning to <FIG>, another computationally-efficient method <NUM> for determining principal components for use in utility locating is described. In a step <NUM> the method <NUM> includes sampling the magnetic signal at a plurality of antennas. For instance, in the dodecahedral array of antennas <NUM> of the antenna node <NUM> illustrated in <FIG>, magnetic signal may be sampled at all twelve antennas <NUM>. In another step <NUM>, the Power Iteration Method or Inverse Power Method may be used to determine one or more eigenvectors in each frequency band that may be prioritized by their corresponding eigenvalues. Such frequency bands may, in some embodiments, be evenly spaced apart in one or more sets of frequency bands. In other embodiments, other frequency band schemes may be used such as variable spacing in one or more series of frequency bands. In a step <NUM>, the Rayleigh quotient may be used to determine the eigenvalue corresponding to each eigenvector of step <NUM>. The method <NUM> may repeat throughout the area of interest.

Turning to <FIG>, a principal component based method <NUM> for separating magnetic signals into different utility lines or other signal sources originating from the same object is described. In a step <NUM>, principal components are determined across a plurality of frequency bands from sampled magnetic signals received at a plurality of antennas from utility lines. The frequency bands may, in some embodiments, be organized into one or more series of evenly spaced apart frequency bands. In other embodiments, other frequency band schemes may be used such as variable spacing in one or more series of frequency bands. In a step <NUM>, field vectors may be determined which may be characterized by the eigenvector optionally having the largest absolute value in each frequency band. In a step <NUM>, similarities and differences in signal content associated with each field vector at each of the plurality of frequency bands may be evaluated. The signal content may include the measureable qualities associated with each signal in each frequency band. For instance, such signal content may include, but should not be limited to, measures of signal power, frequency, position including orientation/pose and depth of the measured signal, and/or the like. In a step <NUM>, field vectors from the various frequency bands are classified into the same utility line and/or other signal source where similarities exist in signal content to within a predetermined threshold. The method <NUM> may include a step <NUM> comparing spatially separated measurements to identify similar eigenvector patterns across frequency bands to match signals to a target utility.

Turning to <FIG>, a principal component based method <NUM> for classifying utility lines via vehicle-based utility locating device is described. In a step <NUM>, principal components are determined across a plurality of frequency bands from sampled magnetic signals received at a plurality of antennas from utility lines. The frequency bands may be, in some embodiments, organized into one or more series of evenly spaced apart frequency bands. In other embodiments, other frequency band schemes may be used such as variable spacing in one or more series of frequency bands. In a step <NUM>, field vectors may be determined which may be characterized by the eigenvector optionally having the largest absolute value in each frequency band. In a step <NUM>, separate utility lines or other signal sources originating from the same object may be determined by evaluating similarities and differences in signal content. For instance, step <NUM> may use method <NUM> of <FIG>. In a step <NUM>, signal content associated with each individual utility line may be compared to a lookup table containing data relating signal content to utility types. The signal content may include the measureable qualities associated with each signal in each frequency band. For instance, such signal content may include, but should not be limited to, measures of signal power, frequency, position including orientation/pose and depth of the associated utility line, and/or the like. In a step <NUM>, utility type may be assigned to each separate utility line or signal sources originating from the same object based upon fitting lookup table criteria to within a threshold.

In one or more exemplary embodiments, the functions, methods, and processes described may be implemented in whole or in part in hardware, software, firmware, or any combination thereof. Computer-readable media include computer storage media.

The various illustrative functions, modules, and circuits described in connection with the embodiments disclosed herein with respect to locating and/or mapping, and/or other functions described herein may be implemented or performed in one or more processing units or modules with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein.

The disclosures are not intended to be limited to the aspects shown herein, but are to be accorded the full scope consistent with the specification and drawings, wherein reference to an element in the singular is not intended to mean "one and only one" unless specifically so stated, but rather "one or more. As an example, "at least one of: a, b, or c" is intended to cover: a; b; c; a and b; a and c; b and c; and a, b and c.

Claim 1:
A vehicle-based utility locating device (<NUM>, <NUM>) for use with a vehicle, comprising:
a positioning element (<NUM>, <NUM>, <NUM>) including one or more GNSS antennas and associated receivers to receive positioning signals and determine position data of the vehicle-based utility locating device in a world frame;
a utility locating element (<NUM>, <NUM>) for determining the presence and location or absence of buried utility lines, including:
an antenna array to receive AC magnetic fields emitted from one or more buried utilities as the utility locating element is moved through an area of interest and provide antenna array output signals corresponding to the sensed AC magnetic fields;
a receiver element (<NUM>) having a receiver input operatively coupled to the antenna array output to sample the antenna array output signals and provide, at a receiver output, receiver output signals corresponding to the sensed AC magnetic fields; and
a processing element (<NUM>), including one or more processors, operatively coupled to the receiver element receiver output to:
receive the receiver output signals and determine principal component values in a plurality of frequency bands;
output data signals representing one or more field vectors corresponding to the eigenvector and eigenvalues of the principal component values so as to be correlated with the position data;
separate field vectors from the various frequency bands into different utility lines and/or other signal sources originating from the same object; and
classify utility lines into different utility line types based on the separate field vectors;
a memory element (<NUM>) comprising one or more non-transitory memories for storing output data values, signal data, position and mapping data, and instructions to implement a signal processing method for determining and mapping utility locations on a communicatively coupled processing element;
a communication element (<NUM>) comprising one or more radio transceivers to communicate data including at least output data values, signal data, and position data relating to determining and mapping utility locations to a communicatively coupled computing device; and
a power element (<NUM>) to provide electrical power to one or more of the positioning element, the utility locating element, the memory element, and the communication of the vehicle-based utility locating device.