Methods and apparatuses for providing signal intelligence and security

Abstract

A method for providing signal intelligence and security by obtaining authentication information about a remote source is described. The method includes, at a receiver, receiving a signal from a remote source in a first direction, providing a local signal, determining movement of the receiver, providing a correlation 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 correlation signal based on the determined movement in the first direction to provide a priority gain to the signal received along the first direction, identifying a remote source vector corresponding to a portion of the propagation path of the received signal based on the correlation, the identifying including a portion that matches the remote source, and generating authentication information about the remote source according to the remote source vector of the received signal. A system and a computer program product for providing signal intelligence and security are also described.

Description

Technical Field

[0001] Embodiments of the present invention relate to wireless communication, and more particularly, to methods and systems for providing authenticity information about a signal source. [Background Art]

[0001] Wireless transmission is used in various communication and positioning systems. WiFi, Bluetooth®, and cellular communication transceivers are ubiquitous. Global Navigation Satellite System (GNSS) receivers are used in almost all mobile devices and require reliable satellite wireless transmission to accurately determine the position of the GNSS receiver. Systems using these technologies are becoming important for the future of functional infrastructure, communication, and transportation. For example, these systems help provide functionality to autonomous vehicles. Accurate position and communication with autonomous vehicles are essential for vehicle operation.

[0002]

[0002] Unfortunately, there are people who attempt to interfere with the reliable functions of systems that rely on wireless transmission by using spoof transmitters. Such spoofing poses a substantial cyber security threat. Illegitimate transmitters, such as spoof transmitters (aka spoofer), can transmit signals that mimic legitimate signals so that a receiver can receive and process the spoof signal as if it were legitimate. For example, in a GNSS receiver, a spoofer can generate a signal that causes the receiver to be provided with inaccurate position information. Such spoofing of a GNSS receiver can be annoying to a person using the signal for guidance or can lead to a catastrophe for an autonomous vehicle using the signal for vehicle guidance.

[0003]

[0003] Therefore, there is a need for methods and devices for obtaining information regarding the authenticity of wireless transmission and providing signal intelligence and security.

Summary of the Invention

[0004] According to a first aspect of the present invention, a method for obtaining authenticity information about a remote source, comprising: at a receiver, receiving a signal from a remote source in a first direction; providing a local signal; determining movement of the receiver; providing a correlation 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 correlation signal based on the determined movement in the first direction to provide a priority gain to the signal received along the first direction; identifying a remote source vector corresponding to a part of the propagation path of the received signal based on the correlation, the identifying including a part that matches the remote source; generating authenticity information about the remote source according to the remote source vector of the received signal; A method is provided that includes.

[0005]

[0005] It has been found that the problem of obtaining authenticity information about a remote source can be addressed by a motion compensation correlation process applied to signals received by a moving receiver. The inventors have realized that by effectively using the results of motion compensation correlation that can provide angle-of-arrival information of signals received from remote sources, an accurate determination regarding the authenticity of these sources can be obtained.

[0006]

[0006] Authenticity information may alternatively be referred to as validity information, security information, or signal intelligence in the sense that it may include information related to spoofers, cyber security threats, or other unauthorized signal sources. Authenticity information typically includes information indicating whether a signal source is a legitimate source or emitter or is unauthorized. Thus, the method may alternatively be considered a method for verifying or evaluating the authenticity of a remote source.

[0007]

[0007] As described hereinafter in the present disclosure, when legitimate information is obtained and refined by further optional verification, appropriate measures may be taken with respect to sources shown by that information to be illicit or potentially illicit. In some cases, such measures may be taken by the authorities and may include investigating, blocking, or invalidating illicit transmitters. The measures may, in some cases, be the aforementioned receiver or, alternatively, a further receiver that may access the legitimate information via, for example, a dataset to which one or more receivers or devices coupled thereto may contribute. Thus, the measures may include suppressing or discarding signals received from an illicit source or a source having a legitimacy score parameter value below a predetermined threshold. In this way, a receiver, or a device comprising or physically and / or communicably coupled to a receiver, may be configured such that any signal from a source shown by legitimate information to be illicit is excluded from any processing that the device is otherwise configured to perform on legitimate signals. For example, any further signal received from a GNSS signal source identified as likely being a spoof in the legitimate information may be excluded from a positioning calculation based on the received GNSS signals.

[0008]

[0008] Optionally, the data may be used by the receiver or a further receiver to perform additional evaluation or verification of sources deemed to be illicit, and may do so by performing the motion compensation correlation-based steps described above or by using any of the secondary verification techniques described hereinafter in the present disclosure. Thus, the method may additionally include, prior to any one or more of the steps described above, obtaining preliminary legitimate information about a remote source and, if the preliminary information indicates that the source is illicit, performing steps to obtain legitimate information.

[0009]

[0009] In some embodiments, the preliminary authenticity information may be obtained from an authenticity dataset such as a remotely hosted database, and the data therein may be obtained by any one or more of the methods for obtaining authenticity information as described above and any alternative methods. In some embodiments, the preliminary authenticity information may be generated according to the type, characteristics, or identifier of the received signal, or according to the known location of the receiver. For example, a preliminary indication of fraud may be generated using a discrepancy between the type of the received signal and data indicating one or more types of signals that are expected to be present or receivable in the estimated or other location of the receiver, or in the area where the receiver is located. Similarly, a signal or its transmitter may be preliminarily indicated as fraudulent if the receiver has not previously received a signal of that type and / or from that intended transmitter. In this way, unnecessary verification of established signals and transmitters can be avoided while continuously evaluating the validity of newly received transmissions.

[0010]

[0010] Generating authenticity information according to a remote source vector may be understood as determining, evaluating, estimating, or inferring the authenticity of the remote source and / or the received signal based on the remote source vector. This generation may, in other words, be regarded as performing an authenticity verification or check to verify or check the authenticity of the source or signal.

[0011] As described in this disclosure, the identification of a vector or direction may generally be considered as that which calculates or generates the vector. The above correlations may be understood as the correlations between the respective local signals and the received signals. The provided priority gain may, in some embodiments, be understood as the gain compared to the signals received in the respective second directions. In some cases, the first direction is the line-of-sight direction between the receiver and the remote source, and the second direction is not. However, in some embodiments, motion compensation is implemented to provide a priority gain to the signals received along a first direction that is not the line-of-sight direction, and in particular, in this case, additional information is available to enable the identification of the remote source vector from such non-line-of-sight signals.

[0012]

[0012] The remote source vector corresponding to a part of the propagation path may preferably be understood as the remote source vector that is on the same straight line as that part. However, due to the probabilistic nature of the confirmed signal direction, that correspondence typically means that the remote source vector represents or indicates, or is an estimate of, a part of the propagation path. In the case of the line-of-sight direction between the receiver and the remote source, the remote source vector typically lies along the direction-of-arrival (DoA) vector, which is the direction in which the receiver receives the signal. However, if a given first direction corresponds to a reflected signal whose propagation direction has been changed by reflection from some object after being transmitted by the remote source, appropriate techniques may be used to calculate the part of the propagation path between the remote source and the reflecting structure based on the DoA at which the reflected signal is received. This can be used, for example, when it is possible to enable the use of the reflected signal in the calculation of the remote source vector using modeling of the reflecting structure and ray tracing. The above propagation path of the received signal may specifically be understood as the propagation path between the remote source and the receiver.

[0013]

[0013] 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 correlation signal following the correlation. By providing motion compensation in a first direction extending between the receiver and the remote source, it is possible to achieve a priority gain for signals received along this direction. Thus, the line-of-sight signal between the receiver and the remote source receives gain preferentially over reflected signals received in different directions. In a GNSS receiver, this can lead to a significant improvement in the accuracy of calculations based on the received signal, as non-line-of-sight signals (e.g., reflected signals) are significantly suppressed. Even if the absolute output of the line-of-sight signal is smaller than the absolute output of the non-line-of-sight signal, the highest correlation can be achieved for the line-of-sight signal.

[0014]

[0014] The received signal may include any known or unknown pattern of transmitted information, either digital or analog, which can be found within 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 that include a Gold code encoded within a wireless transmission. Another example is the Extended Training Sequence used in GSM® cellular transmissions.

[0015]

[0015] Conventionally, phase changes in the received signal caused by changes in the line-of-sight path between the receiver and the remote source have been regarded as troublesome factors that degrade positioning accuracy. The counterintuitive approach of the present invention can actually utilize these phase changes to improve the identification of line-of-sight signals from the remote source.

[0016]

[0016] The motion compensation unit can provide motion compensation to the local signal so that the local signal exactly matches the received signal. In another configuration, motion compensation may be applied to the received signal to reduce the impact of the receiver's 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 enable 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 can also be applied directly to the correlation signal.

[0017]

[0017] In practice, the received signal may be processed as a complex signal including an in-phase component and a quadrature component. The local signal may similarly be complex. The correlation unit may be complex and may be configured to provide a correlation signal that can be used as a measure of the correlation between these complex signals.

[0018]

[0018] Based on the movement measured or assumed in the first direction, it may be possible to achieve high accuracy by providing motion compensation for at least one of the local signal and the received signal. In practice, 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 can include 1023 pseudo-random code chips. The local signal and the received signal may be analog waveforms that can be digitized to provide values at the radio sampling rate, which means that there can be millions of values over a period of 1 ms. The correlation between the local signal digital values and the received signal digital values may be calculated by first correcting any set of values using the motion compensation vector for the relevant period. Then these data points may be summed over that period. In practice, this can generate accurate results because it operates at the radio sampling frequency, but it can be computationally intensive.

[0019]

[0019] Lower accuracy may be achieved by providing motion compensation for the correlation signal. In the above example, when applied to the GPS L1 C / A code, correlations may be performed independently for each of approximately 1000 pseudo-random code chips to generate approximately 1000 complex correlator signal outputs. A motion compensation vector can then be applied to these approximately 1000 correlation signal components. Finally, the motion-compensated correlation signals can be summed to generate a measure of correlation. Thus, motion compensation of the correlation signal may generate an approximation of the result that can be achieved by motion compensation of the local and received signals. However, in some applications, the loss of accuracy may be negligible and may be acceptable in order to reduce the computational load.

[0020]

[0020] As will be described later in this disclosure, various metrics of legitimacy can be obtained using remote source vectors. Any one or more of these types of information, which may be related to the altitude, movement, and geographical location of the source, can be used, for example, individually or in combination, in some embodiments, in cooperation with reference data, to generate legitimacy information.

[0021]

[0021] In some embodiments, the legitimacy information is generated according to the signal type of the received signal. Knowledge of the signal type, e.g., GNSS, cellular, WiFi, or Bluetooth, can facilitate determination of whether the signal source is legitimate, in particular by comparing or evaluating the angle or position information collected from the remote source vector with the expected characteristics or angle or position information of the legitimate source of a given type of signal. The method can be useful for verifying signals expected to occur from a particular height or at a given azimuth angle. For example, the method may be applied to GNSS signals, which should be transmitted from higher sources in the sky and thus should have a more steeply sloped DoA and / or remote source vector. For example, a spoofing source on the ground may be identified by having a transmission path with a less steep slope than expected. Thus, the method may include generating legitimacy information indicating that the remote source is an illegitimate source, or indicating as such, when the angle formed by the remote source vector and the horizontal direction, or alternatively or additionally, the angle between the horizontal direction and the direction of arrival is less than a predefined threshold angle. That is, legitimacy information may be generated indicating that it is an illegitimate source if the angle that can be calculated based on the identified remote source vector is less than that expected for a legitimate source. This may be in the form of a flag or any suitable form of data, e.g., to indicate an invalid or potentially suspicious source.

[0022]

[0022] In some embodiments, the predetermined threshold angle may be 5 degrees, or in some cases 10, 20, 30, or 40 degrees, depending on the level of discrimination applied. The horizontal direction may be understood as being orthogonal to the vertical direction and in the same vertical plane as the remote source or the incoming direction vector that together form an angle. The horizontal direction may be considered as being parallel to the plane of the horizontal line and in the same vertical plane as the vector or the direction of the vector. Such horizontal and vertical reference vectors or directions may, in some embodiments, be defined, for example, with respect to the position of the receiver at the time of signal reception by the receiver, or by the location where the vector on the same straight line as the remote source vector impinges on the earth's surface. The vertical reference direction may be defined as a direction parallel to the direction of gravity received at the above point on the earth's surface or the above location of the receiver.

[0023]

[0023] For some signal types, the determination of legitimacy or illegitimacy may be assisted, in addition to or as an alternative to the methods described above, by checking whether the angle at which the signal is transmitted from the source is as steep as expected. Thus, in some embodiments, the method may include the step of generating legitimacy information indicating that the remote source is a legitimate source when the angle formed by the remote source vector and the horizontal direction is greater than a predetermined threshold angle. Further, for example, for signals originating from a geosynchronous satellite, a positive determination regarding the legitimacy of the signal source may be made if the azimuth angle of transmission is sufficiently large.

[0024] As described above, in embodiments where a threshold angle is used to determine that the source is unauthorized, the threshold angles used for any of these determinations may be the same, but are preferably different. The first threshold angle may be such that below it the source can be considered unauthorized, preferably less than the second threshold angle, and above it the source can be considered authorized. The difference between the two threshold angles may be, for example, 5 degrees, 10 degrees, or 15 degrees. In this way, three ranges of azimuth angles may be defined above, below, and between these two threshold angles, and obtaining authenticity information may be performed by comparing the remote source vector with these ranges. In some embodiments, particularly when the signal nominally originates from a satellite, the shallowest remote source vector of the three ranges may be an indicator that the source is unauthorized, the highest remote source vector of the three angle ranges may allow the source to be considered authorized, while the third intermediate range may correspond to a source that is classified or indicated as potentially authorized, for example, flagged as such so that further investigation can be performed regarding that source.

[0025] As suggested above, in addition to or instead of using the angle information directly, the source can be verified using location information based on the identified remote source vectors. The location information of the remote source may be found based on receiving and identifying the remote source vectors of two or more signals from the source. In some embodiments, the method includes, for each of a plurality of signals received at a receiver from a remote source, the steps of each signal being received in a respective first direction and providing a respective local signal, determining each movement of the receiver, correlating each local signal with the received signal to provide a respective correlation signal, providing motion compensation for at least one of each local signal, received signal, and respective correlation signal based on each determined movement in the respective first direction to provide a priority gain for the signal received along the respective first direction, and identifying, based on the correlation, each remote source vector corresponding to a portion of the propagation path of the received signal, wherein a portion coincides with the remote source. The plurality of received signals is understood to include the received signals described above. Thus, such embodiments of the method include providing a local signal for at least a second received signal received from a remote source in a second direction, determining each movement, and providing each correlation signal. However, preferably, in such embodiments, additional signals are received at the receiver from the source and the corresponding steps are performed on those signals as well. In this way, more remote source vectors can be obtained, which can improve the accuracy of the information regarding the source. Each local signal, each movement, and each correlation signal corresponding to the first received signal may be understood to be the same as the local signal, movement, and correlation signal described above.

[0026]

[0026] In embodiments involving multiple signals, the multiple signals, or at least a subset thereof, may be considered to be transmitted by a remote source as part of a single transmission. That is, the distinction between different ones of the multiple signals may be arbitrary, even though different ones of those signals are typically treated as distinct or separate in the identification of their corresponding remote source vectors for purposes of the method, because they are typically part of a given transmission by the remote source.

[0027]

[0027] Individual signals may typically be defined, for example, by the time difference between when, or during which, a receiver receives a given transmission or part of a transmission, and / or by the position and / or change in position of the receiver when the receiver receives it. Thus, the distinction between signals is generally understood to be independent of the content of the signals. Any two or more of the multiple signals may contain different or the same information, or may be composed of them. Thus, typically, each of the multiple signals is part of a transmission from a remote source received by the receiver during one of each of the multiple periods.

[0028]

[0028] In addition to providing an improvement in the determination of legitimacy by increasing the number of identified remote source vectors, such embodiments can further improve this determination by providing location information of the source, as described above. In the context of the present disclosure, the location information may be understood as data indicating, whether absolute or relative, for example, the position relative to the receiver or, for example, the geographical location. In some embodiments, the location information includes the geographical location of the remote source, and it will be understood that the location information may be associated with the remote source transmitter antenna. Thus, the method may be considered to include the step of identifying the location of the remote source. In some embodiments, the method further includes the step of generating location information of the remote source by identifying one or more locations where two or more of the respective remote source vectors of the plurality of received signals are intercepted. Then, the legitimacy information may be generated according to the location information. In this way, the signal intelligence of the source can be obtained based on the calculated location of the source. Knowledge of the location of the source can be used to determine the reliability of the source, whether it includes an indication of a geographical location such as geographical coordinates, or an indication of the height of the source, for example altitude, or an indication of an aerial location or orbital position.

[0029]

[0029] With respect to the receiver, particularly the position and / or orientation of its receiving antenna, two, preferably three or more, more preferably all of the plurality of received signals may be received along different respective first directions. In some embodiments, these signal reception directions are different due to the movement of the receiver relative to the remote source or within the vicinity of the remote source during the time the method is being implemented. In such a case, the movement of the receiver may include one or two components orthogonal to the direction of arrival or reception of the signal.

[0030]

[0030] However, it will be understood that the aforementioned movement of the receiver through the vicinity of the source need only be sufficient to perform the described motion-compensated correlation. That is, the movement generally includes components directed along a direction parallel to the direction-of-arrival vector of the signal, within a spatial and / or temporal extent that enables the compensation calculation. However, for the generation of the described location information, the receiver need not necessarily move other than what enables the motion-compensated correlation to be performed. Thus, the range of movement of the receiver or any component thereof that traverses the direction-of-arrival and / or line between the receiver and the source need not be large enough such that the angle defined by that movement or component at the location where the remote source and / or signal is reflected towards the receiver is large enough to permit or facilitate the calculation of the location information based on the two remote source vectors. Rather, the receiver movement may in some cases be insufficient for the purpose itself, and instead, or additionally, the calculation of any intersection location is based on the difference in the direction-of-arrival vectors resulting from the difference in the signal propagation paths.

[0031]

[0031] Accordingly, in some embodiments, the difference in the signal reception directions of any two or more signals received during the method being performed can result from the propagation path of one or more of those signals that includes one or more changes in direction, i.e., from one or more of those signals that are reflected. In this way, two sufficiently different remote source vectors corresponding to two different transmission angles can be obtained, and the intersection location of those vectors can be calculated regardless of whether the receiver has moved to an extent that enables triangulation of the line-of-sight vector to the source. In other words, by including one or more reflected signals in the basis of the calculation, the location of the remote source can still be identified even if the receiver has not moved sufficiently to enable accurate triangulation based on two line-of-sight signal vectors.

[0032]

[0032] The generation of location information may be carried out, for example, such that the location information includes the average value of a plurality of locations where two or more of the identified remote source vectors intersect, particularly a point corresponding to the average location. The generation of location information may also be understood as being based on the one or more intersection locations. Each intersection location may correspond to a point defined by the intersection between two remote source vectors, typically also by any degree of uncertainty of the identified vectors, or to a one-dimensional, two-dimensional, or three-dimensional region. Typically, at least two, preferably three or more, identified remote source vectors intersect at each of the one or more intersection locations.

[0033]

[0033] This method facilitates the accurate calculation of the location of a remote source with respect to a receiver. For example, the absolute location of the remote source with respect to an established coordinate system, such as geographical location data, may be found by specifying the location of the receiver in that coordinate system. Thus, in some embodiments, the method further includes obtaining location information of the receiver. The location information of the remote source may be generated based on the location information of the receiver, for example, based on specifying the location of one or more intersection points or intersection regions between remote source vectors with respect to the receiver. The receiver location is typically obtained for at least one of a plurality of received signals, i.e., it may include information indicating the location of the receiver at the time of reception or during the reception of at least one of the plurality of received signals. The receiver location may be obtained using GNSS (Global Navigation Satellite System) and / or IMU (Inertial Measurement Unit) data, and additionally, may be obtained based on the determined movement of the receiver, such as each determined movement corresponding to any one or more of the received signals.

[0034] As described above in the present disclosure, in some embodiments, using additional information about the received signal, it is possible for the method to take into account signals that may be non-line-of-sight signals. Thus, the step of identifying the remote source vector of the signal may include the step of obtaining respective line-of-sight information about the received signal. In particular, this additional line-of-sight information may indicate whether the received signal is a line-of-sight signal. Preferably, this indication may be used to determine whether to use, discard, or perform additional processing or calculations on the direction-of-arrival vector for the purpose of identifying the intersection location. The additional information may indicate whether the propagation path from the source to the receiver is direct, i.e., along the line of sight between them. In the case of some signals, conversely, the line-of-sight information may indicate that the received signal is a non-line-of-sight signal such as a reflected signal.

[0035]

[0035] By using this information, non-line-of-sight signals can be so identified, enabling the utilization of more signals that may be received during a given period or during the movement of the receiver along a given path segment. Thus, these signals can be used more quickly and accurately in identifying the intersection between the remote source vectors and, thus, in locating the remote sources, despite their indirect propagation paths. Accordingly, the step of identifying the remote source vector for the received signal may further include the step of identifying respective directions of arrival based on the above correlations, and the step of identifying the remote source vector according to the respective directions of arrival and respective line-of-sight information. The direction of arrival may be considered as corresponding to or representing the direction or vector in which the signal is received by the receiver and / or the direction of travel of the signal when it is received by the receiver. Generally, it will be understood that the method typically includes estimating the direction of arrival (DoA) of the signal using supercorrelation techniques that will be described in more detail later in the present disclosure.

[0036]

[0036] In the case of a line-of-sight signal, the DoA and the remote source vector typically correspond to the same direction, i.e., they are parallel and may be considered to have vectors typically on the same straight line. For non-line-of-sight signals, the method may be enhanced using line-of-sight information such that a super-correlation technique is applied to obtain the DoA. These DoAs may then be used in conjunction with knowledge of the nearby reflection structure, such as any one or more of the position, orientation, shape of one or more reflecting surfaces or objects, to calculate the remote source vector. Thus, even when calculated based on a DoA that does not directly correspond to the direction in which the signal was received from the source, additional data, and thus improved position accuracy, can be obtained by using additional remote source vectors. These additional remote source vectors may also be useful, for example, when a line-of-sight signal from a given transmitter is blocked or attenuated to the point where it cannot be used to obtain location information.

[0037]

[0037] Identifying the remote source vector according to the direction of arrival and line-of-sight information typically involves a modification to the motion-compensated correlation technique, whereby a priority gain is achieved for signals received along these non-line-of-sight directions, particularly based on the fact that those signals can still be used nonetheless. Alternatively, one or more signals indicated as being reflected signals may, in some embodiments, be excluded from the plurality of signals on which calculations for obtaining location information are performed based thereon.

[0038]

[0038] In embodiments involving the use of non-line-of-sight signals despite those indirect propagation paths, the method may further include obtaining reflection model data including a geometric model of a set of structures capable of reflecting the signals. Such models that can enable the calculation of remote source vectors based on the DoA of the reflected signals can be particularly useful in urban environments. For example, it may be beneficial to utilize methods of a predefined 3D building model representing structures that can interfere with and / or reflect transmissions, such as those containing received signals. Techniques such as ray tracing are used to model the propagation paths through such environments so that useful remote source vector information can be inferred even when the only signal received at a given location along the receiver's movement path is reflected by one or more structures. It will be appreciated that the geometric model may include a set of one or more structures, which may be natural or artificial, such as buildings, landscapes, and topographical features. These structures capable of reflecting the signals may be understood to be capable of reflecting signals of the same or a similar type as one or more of the plurality of signals, i.e., being reflective with respect to them. For example, a model representing structures within a predefined radius or an area including the estimated or obtained location of the receiver at a given time in the vicinity of the receiver may be obtained and used to model the propagation path. Typically, the model data includes three-dimensional geometric data representing the reflective structures and including sufficient information regarding the position and / or orientation of the reflective structures to enable the calculation of propagation paths including one or more reflections by the reflective structures.

[0039]

[0039] The step of identifying the remote source vector according to each arrival direction and each line-of-sight information may include, when each line-of-sight information indicates that the received signal is not a line-of-sight signal, calculating each remote source vector based on the reflection model data and each arrival direction. Typically, the aforementioned use of the estimated non-line-of-sight direction of arrival requires geometric information that enables the calculation or estimation of the transmission direction or the remote source vector. In embodiments with reflection model data, compensation can be applied to account for the fact that there was a reflection, which could otherwise cause a positioning error, or the reflected signal may be used in some other way to enhance the positioning accuracy.

[0040]

[0040] In various embodiments, the reflection model data and the line-of-sight information may be separate, or related, or the same. For example, a set of line-of-sight information may indicate that the arrival direction is the arrival direction of a non-line-of-sight signal by indicating that the arrival direction vector intersects or coincides with a reflection structure modeled within the reflection model data.

[0041]

[0041] The method may further include obtaining arrival time data, or time difference of arrival data, for one or more of the plurality of received signals, and the line-of-sight information may be obtained according to the arrival time data. For example, abnormal arrival time data may be used to determine that the received signal is a line-of-sight signal, and vice versa. This may then be used to exclude non-line-of-sight signals from one or more calculations when obtaining the location information of the remote source. This may also be used, for example, with the reflection model data, to perform additional processing.

[0042]

[0042] In some embodiments, the step of generating authenticity information according to the location information is obtaining reference location data, which may also be referred to as reference source location data, indicating one or more legitimate signal sources, and generating authenticity information based on a comparison between the generated location information and reference location data; For example, the reference location data may include one or more areas where a legitimate source is known to be located, or instructions therefor. Thus, determining that a remote source is illegitimate may also be based on the generated location information indicating that the source is outside of that one or more areas.

[0043]

[0043] Regardless of whether reference location data is available to enable comparison of the determined source location with known transmitter locations or areas containing them, the generated location information may also be used to determine legitimacy based on whether the signal source should be in a particular area anyway. In some embodiments, thus, the method further includes obtaining reference geographic data corresponding to or including information about one or more geographic areas and including information indicating the expected presence of one or more legitimate sources therein, and generating authenticity information according to the generated location information and the reference geographic data.

[0044]

[0044] The reference geographic data may define either the boundaries of the geographic area and the extent or area of the geographic area, or any information sufficient to determine whether a given location is actually within the area. The geographic area may be understood as a particular area on and / or above the surface of the earth. The one or more geographic regions may include or coincide with locations indicated by the location information, particularly geographic locations. The expected presence may be understood as a level of presence, or degree of presence of a legitimate source, and may be expressed in terms of the absolute or relative amount, number, or density of legitimate sources, or their spatial distribution. For example, the expected presence may indicate an expected level, and thus may be considered the expected presence or absence of a legitimate source from a given area.

[0045]

[0045] In such an embodiment, the location information may be used to identify the geographic area corresponding to the reference geographic data where the source is located. Thus, an evaluation regarding the validity of the source may be performed based on the expected presence of legitimate sources in that area. For example, it is obvious that if the expected presence within the area where the signal is determined to have been transmitted is zero, the method may include determining that the source is illegitimate. The method may also involve calculating or otherwise determining the amount of sources within the area, for example, by obtaining the location information of a plurality of sources indicating that they are located there and comparing that amount to the expected presence. For example, if an excessive amount of sources are found within the area compared to a reference data amount, one or each of the sources identified as being within that area may be determined to be illegitimate or potentially illegitimate. Further, the method may involve performing additional checks on those sources, as will be described in more detail later in the present disclosure.

[0046]

[0046] The reference geographical data may include expected source type information. This information may correspond to one or more geographical regions, and the authenticity information may be generated according to a comparison between the above source type and one or more identified types of the plurality of received signals. The expected source type may refer to an expectation based on any knowledge of what types of sources should exist within the region and / or what sources are known to be transmitted from or are likely to be transmitted from the region, as may be indicated by the expected source type information. The source type may include or be indicated by or inferred from any one or more of the signal wavelength, signal content, time and / or date of signal transmission or reception. The expected source type information may indicate any one or more of one or more types of sources expected to exist within the region and one or more types of sources not expected to exist within the region. For example, the method may include inferring source irregularity when different indications of the source content or its source type are unexpected within a given type of terrain, water area, or geopolitically defined area. The method may also include identifying or determining the signal type in order to obtain one or more of the above identified types of the plurality of received signals.

[0047]

[0047] In embodiments involving the use of a plurality of received signals, the method may further include generating source movement information indicating the movement state of the remote source based on a plurality of remote source vectors, i.e., the remote source vectors of each of the plurality of received signals including the first remote source vector as described above. Then, the authenticity information may be generated according to the source movement information.

[0048] By obtaining a plurality of remote source vectors of signals transmitted at different times, clues to the legitimacy of the source can be revealed. In particular, obtaining an accurate indication of whether the source is moving or stationary, along with knowledge of whether a legitimate source of that type moves, is beneficial for obtaining legitimacy information. Thus, the movement state mentioned above may be understood as information regarding whether the source is moving and how it is moving. The step of generating source movement information may include the step of calculating movement or its components. For example, it may involve calculating the coordinates, position, speed, velocity, acceleration, or components thereof of the source. In some components, the information may simply indicate, for example, whether the first and second remote source vectors among a plurality of remote source vectors are different, or whether they are the same, or whether they differ by more than a threshold angle. Remote source vectors that remain the same over a given period may indicate no movement, and conversely, the difference between them may indicate movement of the source.

[0049]

[0049] This method may further include the step of obtaining reference source movement data indicating the expected movement state of a legitimate remote source. The reference source movement data may indicate, for example, whether the source should be moving. This may be based, for example, on the type of signal reported and transmitted by a cellular network base station, and the reference data may indicate that the source should not be moving. The indication in the data may include an explicit flag or may be implicit, for example, in the type of source and / or the signal. The data may include the expected movement states of multiple signals and source types. The method may include the step of generating legitimacy information according to the generated source movement information and the reference source movement data. This typically includes a comparison between the source movement information and the reference source movement data. If the generated movement information is different from or does not match the reference data, the legitimacy information may be generated to indicate that the source is illegitimate. For example, in the case of a cellular base station, if the generated source movement information indicates movement of the source, the source may be marked as illegitimate, contrary to the opposing implicit or explicit indication by the reference data.

[0050]

[0050] In some embodiments, it will be understood that evaluating the legitimacy of a source based on its movement determination may not require calculating the location of the source or its change. Rather, the movement of the source may, in some cases, be inferred from changes in the identified remote source vectors. However, preferably, if a sufficient number of remote source vectors are calculated for the source and a sufficient number are obtained, that data may be used to calculate two or more intersection locations of those remote source vectors, each corresponding to a signal transmitted at a different time, and as a result, find two or more locations of the source at those different times.

[0051]

[0051] However, in some embodiments, a remote source vector may be used to infer movement of the source independent of any calculated location. That is, at least the angular change of movement or the angular / lateral component may be inferred from the remote source vector itself over a given period, which does not necessarily involve calculating the radial component of movement, i.e., the component of movement in the direction of the remote source vector or the direction of arrival. However, as described above, the evaluation of validity may be improved by calculating two or more locations based on the acquired remote source vector.

[0052]

[0052] The method thus generating first location information of the remote source by identifying one or more locations where two or more first sets of a plurality of remote source vectors intersect; generating second location information of the remote source by identifying one or more locations where two or more second sets, different from the first set, of the plurality of remote source vectors intersect; generating source movement information based on the first location information and the second location information; may further include. The second set of remote source vectors may be different from the first set in that they correspond to signals received or transmitted at different times. That is, preferably, each of the remote source vectors of the second set corresponds to a signal transmitted after one or all of the signals of the first set. Preferably, the reception and / or transmission times corresponding to the two sets are separated by a duration long enough to evaluate the movement of the source. For example, this duration may be on the order of seconds, tens of seconds, minutes, or hours.

[0053]

[0053] The generation of source movement information may involve comparing the first location information and the second location information, or calculating the difference between them. Further, the method may additionally use a set of third, fourth, and any number of further remote source vectors corresponding to respective different signal transmission times to calculate respective further locations. It may be possible to define an estimated movement path of the remote source using a plurality of identified locations. Comparison of the movement path with the expected pattern or type of movement of a legitimate source may assist in obtaining legitimacy information. Thus, in some embodiments, the generated source movement information includes a generated source movement path based on, i.e., calculated based on, the first and second location information. In fact, this may be based on any additional location information. In some preferred embodiments, a detailed path may be generated, and the estimated movement of the source may be tracked with a sufficient set of remote source vectors and the correspondingly calculated locations.

[0054]

[0054] The reference source movement data may include an expected legitimate source movement path, and the legitimacy information may be generated according to a comparison between the generated source movement path and the expected source movement path. That is, if the comparison operation returns a difference or discrepancy between the paths, e.g., a displacement or deviation from the path expected for a legitimate source that is greater than a predetermined threshold, the legitimacy information may be generated to indicate that the source is illegitimate. Similarly, if the calculated difference between the paths is less than a predetermined tolerance, or if no difference or substantially no difference is identified, the legitimacy information may indicate that the source is legitimate.

[0055]

[0055] Preferably, the method includes the step of storing the authenticity information of the remote source in a remote source authenticity dataset. In this way, receivers operating simultaneously or at different times in a certain area, or preferably multiple receivers, can check the authenticity of the transmission sources therein and / or be able to take appropriate measures to build a store of data that can be used to flag, notify, or warn any interested party about the presence of unauthorized sources in the area. Such a dataset is preferably stored in a database, which is typically preferably remote from the receiver and is preferably implemented on one or more servers or other computer devices that are directly or indirectly accessible by the receiver via one or more wired or wireless communication links or any other mode of transferring data.

[0056]

[0056] The source authenticity dataset can indicate any one of the authenticity status, authenticity flag, authenticity score, and any other form of authenticity indicator for each source where the information is recorded. Preferably, the dataset additionally includes source location information for one or more sources. More preferably, the stored location information indicates or represents the geographical location of the source, for example, in the form of geographical coordinates.

[0057]

[0057] The source location information stored in the dataset can be obtained by various means including, as previously described in this disclosure, as part of the method, for example, receiving and identifying the remote source vectors of two or more signals from the source and, for example, identifying the intersection location. In some embodiments, the source location information is obtained by other techniques or using additional data. For example, satellite or aerial images representing the geographical area where the source is located can be used to visually estimate the location of the transmitter, and in some embodiments, it can also be used for secondary authenticity checks of the source.

[0058]

[0058] In some embodiments, the location information includes, for example, a relative location indicating the position of the source relative to the receiver at the time of signal reception. Such relative location information may additionally or alternatively include angle information or direction information, and in particular may include an indication of the direction in which the source is located relative to the receiver. The information may include an indication of a remote source vector, along with location information derived from the location information of the receiver. In this way, in implementations where the location of the source is not necessarily obtained during the method, a range of locations along the remote source vector and thus including the true or at least approximate location of the source can be obtained. Such information may be used in conjunction with similar information obtained by a method that is executed multiple times using the receiver, preferably one or more additional receivers.

[0059] By providing or updating a data set having information regarding the location of an unauthorized transmitter, any receiver that may be within or pass through the broadcast range of those transmitters, or that may be receiving transmissions from their locations, can be given a preliminary indication or warning regarding the potential presence, direction, and / or location of the identified transmitters. This can be the same even for receivers that are approaching or in the vicinity when the location is unknown or the exact location is not known. The data set used by the receiver can, for example, establish a range of directions with respect to its own known or estimated location that is indicated by, or from which transmissions from such sources are expected based on, legitimate information previously obtained by the unauthorized or potentially unauthorized transmitter. Using that knowledge, the receiver can utilize the data set itself to take appropriate measures regarding signals received from the direction or area indicated by the legitimate information that an unauthorized transmission could occur. Such measures may include, as previously described in this disclosure, selective processing or exclusion of particular signals, and may include these receivers performing their own primary and / or secondary validation of the signals by any of the techniques described herein. Thus, the legitimate information itself that can be added to the data set may constitute preliminary legitimate information for subsequent use by any receiver.

[0060]

[0060] In some cases, the legitimacy or illegitimacy of a source may not be definitively determined by this method, and it should be understood that the generated legitimacy information may indicate that the source is potentially illegitimate rather than definitely illegitimate. Thus, in some embodiments, it may be useful to perform further legitimacy evaluation according to a confidence level or parameter associated with the information, or on the condition that a remote source vector-based evaluation indicates that the source is not necessarily legitimate. Thus, some embodiments further include the step of performing a legitimacy verification for the remote source using or based on the received signal when the legitimacy information indicates that the remote source is an illegitimate source. Thus, the method may further include the step of updating the legitimacy information according to the result of the legitimacy verification and / or the confidence parameter.

[0061]

[0061] The above legitimacy verification may be considered a secondary legitimacy check or a second legitimacy verification, taking into account the initial generation of legitimacy information that may be considered the first check or the first verification step. It may be useful to perform one or more such additional checks. However, the efficiency of the process of verifying sources and identifying illegitimate sources is typically improved by first identifying potentially illegitimate sources based on remote source vectors that are accurately determined using motion compensation correlation techniques and conditionally performing these additional checks.

[0062]

[0062] Preferably, the additional verification is performed based on one or more signal characteristics other than the direction information. That is, the characteristics may exclude the direction of arrival, the remote source vector, or other information generally related to or derived from the propagation path of the signal or any part thereof. The above update of the authenticity information may be an optional step in some embodiments, or may be performed conditionally itself. For example, the authenticity information may remain unchanged if it matches or is supported by a secondary check. For example, if the check returns a result confirming the source's illegitimacy, the update may be performed so that the indicated authenticity in the data is not changed, but preferably, the data may be updated to indicate that the secondary check has been performed.

[0063]

[0063] In some embodiments, the update may include modifying or adding authenticity information, such as modifying the indication of the legitimacy or illegitimacy of the source / signal included in the data. This update may, in some cases, confirm the initial indication that the source is valid or invalid. For example, in some other cases, if a further check concludes that a potentially illegitimate source is actually valid, the information may be updated to reflect its modified indication of illegitimacy. Similarly, following any number of auxiliary checks, the update may include flagging the signal or source for further investigation, for example, if those further checks are inconclusive regarding the authenticity.

[0064]

[0064] The information may also be updated to include further details about the source, such as the monitored characteristics of the source, technical information, test results, recorded signal content, and characteristics.

[0065]

[0065] Generally, the result of the illegitimacy verification may include any data generated as a result of the verification step. Typically, this indicates the authenticity of the source as evaluated by that verification process.

[0066]

[0066] Examples of scenarios where the secondary verification step is useful involve the reception of reflected signals, particularly signals whose propagation path involves reflection by a moving object. For example, signals such as cellular base station transmissions can be reflected over a period of time by a moving vehicle such as a bus or a heavy goods vehicle and received by a receiver. In that situation, the receiver typically calculates the remote source vector without knowledge of the signal reflected by the vehicle, since any geometric data that can model the indirect propagation path generally omits temporary reflection structures and surfaces such as the vehicle. In that case, calculating a plurality of remote source vectors assuming that the signal is a line-of-sight signal and determining the movement state or movement path of the source based thereon indicates that the source is moving. Then, initial legitimate information may be generated so as to indicate the source as being illegitimate by comparison with the expected movement state of a transmitter such as a cellular base station. Thus, the secondary verification of the source's legitimacy can be effective for maintaining the accuracy of the maintained legitimate information.

[0067]

[0067] The secondary verification may, for example, involve obtaining additional signals from the source, which may include signals that can find a remote source vector that truly matches the source's transmitter (regardless of whether it is a line-of-sight signal or an indirect signal that can accurately model the reflected propagation path). In this way, the legitimacy of the source may be verified, and additionally, the obtained information may be updated, for example, to indicate that the received movement signal therefrom may be reflected and should be discarded.

[0068]

[0068] One way to perform a secondary check that is particularly effective when the potentially illegitimate received signal is a positioning broadcast such as a GNSS signal may involve evaluating the effect of the signal on the positioning calculation result. Thus, in some embodiments, particularly where the signal is a positioning signal that can enumerate a first positioning signal, the legitimacy verification is performing a first positioning calculation based on a plurality of received positioning signals including the first positioning signal to obtain the first location information of the receiver, and To obtain second location information of the receiver, performing a second positioning calculation based on a plurality of received positioning signals excluding the first positioning signal; obtaining a comparison between the first location information and the second location information; may be included. In other words, additional verification may be at least partially based on comparing two calculated receiver positions, one based on one or more suspected fraudulent broadcasts and the other based on positioning broadcasts excluding one or more suspected fraudulent broadcasts. If the comparison between the two positioning results shows a difference between the calculated locations, e.g., a positional difference defined as a difference exceeding a preferably pre-defined distance or difference threshold, the verification may confirm the source and / or signal as being fraudulent.

[0069]

[0069] Typically, a fraudulent transmitter includes components of lower quality than legitimate ones. In particular, fraudulent sources generally use frequency standards with low stability and / or accuracy. This common shortcoming may be used as an indicator of fraud, the presence of these components may be inferred from the signal characteristics, and thus may be used as a secondary check of sources where initial legitimacy information has potentially been shown to be fraudulent. Thus, legitimacy verification may include using the received signal to obtain source quality parameters of the remote source. The parameters may indicate the evaluated quality level of the components of the remote source. Obtaining the parameters may include analyzing the stability, accuracy, and / or phase noise of the carrier frequency. If the source quality parameter or its value is below a pre-defined threshold or indicates that the component quality is below what would be expected for a legitimate source corresponding to a nominally legitimate source, the legitimacy information may, in some embodiments, be updated to confirm or reconfirm fraud.

[0070] As described above, the above components of the remote source may be frequency standard components. The source quality parameter is typically obtained in such embodiments by calculating the quality of the frequency standard component of the remote source based on the received signal. Quality is typically defined as the frequency stability of the frequency standard used by the transmitting source, or a measure or indication thereof. For example, a metric such as Allan variance may be used.

[0071]

[0071] A further technique for performing secondary verification may involve the polarization state of the radiation carrying the signal. In other words, in some embodiments, the validity verification may be based on the monitored polarization state of the received signal. Thus, the signal may be received using an antenna capable of monitoring the polarization state of the radiation carrying the signal. The method may include comparing the state to an expected polarization state, for example, as expected for a legitimate signal of the same type and / or from the same type of source and / or from the same location.

[0072]

[0072] In some embodiments, the hybrid modality signal evaluation may be performed either between the secondary verification step and / or the step of obtaining preliminary authenticity information as described above in the present disclosure. By examining different types of signals in addition to the signals whose authenticity has been verified, the efficiency of the method and the quality of the resulting signal intelligence can be effectively improved. Thus, such an evaluation may provide preliminary and / or secondary indications of the authenticity of the signal source. The evaluation typically involves performing a comparison between one or more signal characteristics and a corresponding set of one or more signal characteristics for one or more additional received signals that are different from, preferably of a different signal type or modality than, the first received signal. The characteristics may include any one or more of the direction of arrival at the transmitter, signal type or modality, intensity, duration, and content. The expected characteristics are typically associated with one or more given geographical areas in which the receiver can operate and may be obtained by reference data acquired in relation thereto. For example, if the received GNSS signal is to be verified and has authenticity information obtained therefor, by the present method, additional hybrid modality signal evaluation may involve monitoring a further set of signals, typically their direction of reception and type, and comparing the monitored signals with signals that are expected to be present in the area, at least with respect to them. For example, a discrepancy between the monitored signal and the expected signal may indicate the presence of an invalid source, and conversely, the confirmed similarity between the measurement and the prediction may be used to confirm or indicate to the receiver the area or location in which the receiver is operating, which may, as a result, be used to identify an incorrect position calculated using a positioning broadcast such as a GNSS signal and thereby indicate the invalidity of those broadcasts.

[0073]

[0073] According to a second aspect of the present invention, a system comprising a local signal generator configured to provide a local signal, A receiver configured to receive a signal from a remote source in a first direction, and a motion module configured to provide a determined movement of the receiver; A correlation unit configured to provide a correlation signal by correlating a local signal with the received signal; A motion compensation unit configured to provide motion compensation for at least one of the local signal, the received signal, and the correlation signal based on the determined movement in the first direction; A source vector unit configured to identify a remote source vector corresponding to a part of the propagation path of the received signal that matches the remote source based on the correlation; A legitimacy information unit configured to generate legitimacy information according to the remote source vector of the received signal; A system is provided that includes the above.

[0074]

[0074] Typically, any one or more of the local signal generator, motion module, correlation unit, motion compensation unit, source vector unit, and authenticity information unit are provided as part of a single device. In some embodiments, the device further comprises a receiver. Typically, the device comprising the receiver is a user equipment (UE) within a communication network. Any one or more of the modules and units may be provided separately from the receiver or the device comprising it so that the system is distributed. For example, certain calculations such as those performed by the motion compensation unit and / or the correlation unit may be performed by a processor within the network or via data communication in a manner separate from the device comprising the receiver. In this way, the UE may offload the calculations to a remote or distributed process for efficiency and user equipment battery usage purposes where appropriate. In some embodiments, the system, preferably the device comprising the receiver, includes a GNSS positioning device. The output of the positioning device and / or, specifically, the output of the inertial measurement unit that may also be included in the system or user equipment, or the device comprising the receiver, is used for either or both of providing the determined movement of the receiver and providing one or more location information of the receiver, and thus may enable confirmation of the absolute location and / or movement path of the remote source based on the relative location information for the receiver.

[0075]

[0075] According to a third aspect of the present invention, when executed by a processor, the processor is caused to receive a signal from a remote source in a first direction at a receiver; provide a local signal; determine the movement of the receiver; providing a correlation signal by correlating a local signal with a received signal; and providing motion compensation for at least one of the local signal, the received signal, and the correlation signal based on a determined movement in each first direction to provide a priority gain to the signal received along each first direction identifying, based on the correlation, a remote source vector corresponding to a part of the propagation path of the received signal, wherein part coincides with a remote source generating authenticity information about the remote source according to the remote source vector of the received signal A computer program product is provided that includes executable instructions for causing the steps including the above to be performed

[0076]

[0076] Any of the characteristics, features, and steps described in connection with the preceding and subsequent embodiments in the present disclosure may be related to the method of the first aspect, the system of the second aspect, the computer program product of the third aspect, or the aspects described later

[0077]

[0077] According to a fourth aspect of the present invention, a method for identifying the location of a cellular emitter using a receiver, the method comprising: performing motion compensation correlation on at least one received signal to generate at least one motion compensation correlation result; identifying the direction of arrival of at least one received signal using at least one motion compensation correlation result; and determining the location of the cellular emitter from the direction of arrival of at least one received signal

[0078]

[0078] In any of the aspects of the invention provided by the present disclosure, the method may include any one or more of: determining the arrival time of at least one received signal; using the arrival time to remove the direction of arrival of the received signal associated with the non-line-of-sight signal; determining whether the emitter is legitimate or illegitimate; and taking measures to mitigate interference generated by an illegitimate emitter if the emitter is illegitimate.

[0079]

[0079] According to a further aspect of the invention, there is provided an apparatus for performing signal correlation within a signal processing system, comprising at least one processor and at least one non-transitory computer-readable medium storing instructions which, when executed by the at least one processor, cause the apparatus to perform operations including: performing motion-compensated correlation on at least one received signal to generate at least one motion-compensated correlation result; using the at least one motion-compensated correlation result to identify the direction of arrival of the at least one received signal; and determining the location of the cellular emitter from the direction of arrival of the at least one received signal.

[0080]

[0080] Embodiments of the invention generally relate to methods and apparatus for providing signal intelligence and security as shown in and / or described in connection with at least one of the figures.

[0081]

[0081] These and other features and advantages of the present disclosure can be understood by considering the following detailed description of the present disclosure together with the accompanying drawings in which like reference numerals generally refer to like parts throughout.

Brief Description of the Drawings

[0082]

[0082] To enable a detailed understanding of the features described above of the present invention, a specific description of the present invention can be made by referring to the embodiments shown in several of the accompanying drawings. However, it should be noted that the accompanying drawings show only typical embodiments of the present invention, and therefore, since the present invention can recognize other equally effective embodiments, it should not be considered as limiting its scope.

[0083]

Figure 1

[0083] FIG. 1 is a diagram showing a block diagram of a scenario having a receiver for providing signal intelligence according to at least one embodiment of the present invention.

[0084]

Figure 2

[0084] FIG. 2 is a block diagram of the receiver of FIG. 1 according to at least one embodiment of the present invention.

[0085]

Figure 3

[0085] FIG. 3 is a diagram showing a scenario of the operation of the receivers of FIGS. 1 and 2 according to at least one embodiment of the present invention.

[0086]

Figure 4

[0086] FIG. 4 is a flowchart of an operation method of signal processing software according to at least one embodiment of the present invention.

[0087]

Figure 5

[0087] FIG. 5 is a flowchart of an operation method of emitter location software according to at least one embodiment of the present invention.

Mode for Carrying Out the Invention

[0088]

[0088] Embodiments of the present invention include apparatuses and methods for providing signal intelligence and security. Digital communication systems such as cellular, Bluetooth, or WiFi utilize encoded digital signals to improve communication throughput and security. Most of these systems utilize some form of deterministic digital code, such as a Gold code, training sequence, synchronization word, channel characterization sequence, or other form of acquisition code, to facilitate signal acquisition. GNSS transmissions also utilize a repeatedly transmitted acquisition code. Such digital codes are deterministic by the receiver and repeatedly broadcast by the transmitter to enable the receiver to acquire and receive the transmitted signal. Using such deterministic codes in combination with an accurate motion model of the receiver, embodiments of the present invention are useful for identifying the direction of arrival (DoA) of the propagation path between the receiver and the transmitter. Techniques for performing this DoA determination using receiver motion information are known as SUPERCORRELATION™ and are described in U.S. Patent No. 9,780,829, issued October 3, 2017, to the same applicant; U.S. Patent No. 10,321,430, issued June 11, 2019; U.S. Patent 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 hereby incorporated by reference in their entirety. The receiver can use this DoA data to determine information about one or more emitters in the vicinity of the receiver. For example, the DoA data can be used to identify the location of spoof emitters and the location of legitimate emitters. In the future, a map of legitimate emitters may be created using location so that emitters not on the map can be considered unauthorized emitters requiring further investigation.From the DoA data, the user receiver (e.g., a mobile device or a GNSS receiver) may operate to avoid or suppress signals from spoofing emitters so that these illicit emitters are no longer a threat. Using the locations of the illicit emitters, government authorities can identify and disable these emitters.

[0089]

[0089] In an exemplary embodiment, the receiver may be transported through an area containing various emitters and be able to identify signal propagation paths and the locations of each nearby emitter. These emitters may be GNSS satellites, cellular signal transceivers, WiFi transceivers, Bluetooth transceivers, etc. The receiver may be carried by a pedestrian and function via application software to map the emitters within the local area. Alternatively, emitter location and mapping may be performed by moving the receiver using a vehicle on a ground path. In other embodiments, the receiver may be carried by a manned or unmanned (e.g., drone, helicopter, airplane, etc.) aerial vehicle. The functions of the embodiments of the present invention may be incorporated into mobile phones, Internet of Things (IoT) devices, mobile computers, tablets, autonomous vehicle control systems, etc. Embodiments find use on any mobile platform capable of receiving signals that can be correlated with locally generated signals.

[0090]

[0090] As the receiver traverses the area, it collects DoA data of nearby emitters (i.e., within the range of the emitters). The receiver knows its position by using a global navigation satellite system (GNSS) receiver and / or an inertial navigation system. From the position of the receiver and multiple DoA vectors (representing the direction from the receiver to the emitter), embodiments of the present invention calculate the location of the emitter relative to the receiver. The relative location can then be converted to geographical coordinates. Once the emitter location is calculated, a geographical coordinate map showing the locations of the emitters is generated.

[0091]

[0091] In some embodiments, multiple receivers may be used to receive signals cooperatively. In further embodiments, the receiver(s) may receive signals from multiple types of emitters operating in various frequency bands to facilitate collection of information related to many systems to generate a signal profile of a given area. Some embodiments may perform signal processing locally on a mobile platform. In other embodiments, emitter information, receiver movement information, and receiver location information may be collected on the mobile platform and communicated (wired or wirelessly) to a server for remote processing either in real time or later. In some embodiments, the data is stored and processed as needed, for example, when law enforcement agencies require the advanced path of a particular mobile phone or other emitter.

[0092]

[0092] FIG. 1 shows a block diagram of scenario 100 having at least one receiver 102 for receiving signals from emitters 106, 108, and 110, according to at least one embodiment of the present invention. In other embodiments, multiple receivers 102 may be deployed to collect emitter information. Emitters 106, 108, 110 may be legitimate emitters (communication or positioning emitters) or illegitimate emitters (jammers or spoofers). Emitters 106, 108, 110 may be stationary or mobile. Each of the at least one receiver 102 includes an emitter locator 104 configured to receive and process signals transmitted by emitters 106, 108, 110 (although three emitters are shown, receiver 102 can process signals from any number of emitters). Signals from legitimate emitters 106 and 110 may be intended to communicate, for example, with a mobile device 114, such as a cell phone, laptop computer, tablet, Internet of Things (IoT) device, autonomous vehicle, etc. The mobile device may communicate with emitters 106, 110 using cellular signals, such as CDMA, GSM, etc., that support cellular standards including, but not limited to, 3G, 4G, LTE, and / or 5G standards. Alternatively or in addition, legitimate emitters 106, 110 may be WiFi or Bluetooth, or other communication devices that communicate with each other or with mobile device 114. Further, legitimate emitters 106, 110 may be satellite-based transmitters of GNSS signals.

[0093] Scenario 100 may include at least one unauthorized emitter 108, such as a jammer or spoofing device, that may target a mobile device such as device 114. The intention of the jammer is to interfere with the reception of transmissions from legitimate emitters 106, 108. The jammer may transmit a signal similar to the legitimate emitter signal to overwhelm or confuse the signal processing capabilities of the target receiver. On the other hand, a spoofing device transmits a signal similar to the legitimate emitter signal so that the target receiver may acquire the spoofed signal and even process it as if it were legitimate.

[0094]

[0094] The receiver 102 includes an emitter locator 104 that operates to accurately identify the locations of emitters 106, 108, 110 according to at least one embodiment of the present invention. The emitter locator 104 may identify the locations of both legitimate and unauthorized emitters, or the locator 104 may identify the locations of only unauthorized emitters. As is apparent from this description, the purpose of the emitter locator is to provide signal intelligence for transmissions occurring in its vicinity. Signal intelligence may be used to take measures to improve the signal security of the transmission user, such as avoiding or suppressing the reception of unauthorized transmissions and disabling unauthorized emitters.

[0095]

[0095] In one embodiment, the emitter locator 104 within at least one receiver 102 receives and processes emitter transmissions locally within the receiver. In other embodiments, the receiver-based emitter locator 104 can collect data regarding emitter transmissions and receiver parameters (e.g., movement, location of the receiver, etc.). The emitter data may be communicated immediately to the server 112 through the communication network 114 or stored for later communication. The server 112 includes an emitter locator 104 for processing the emitter data to determine the emitter location. The emitter data can be processed in real time or later. In other embodiments, the emitter data may be processed partially at the receiver 102 and partially at the server 112.

[0096]

[0096] As will be described in detail below, the emitter locator 104 (whether receiver-based or server-based) uses the SUPERCORRELATION (trademark) technique as described in U.S. Patent No. 9,780,829, issued October 3, 2017, to the same applicant; U.S. Patent No. 10,321,430, issued June 11, 2019; U.S. Patent 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 hereby incorporated by reference in their entirety). This technique determines the direction of arrival (DoA) of signals received by the receiver from emitters 106, 108, 110 (i.e., the received signals). As the receiver 102 moves (represented by arrow 118), the emitter locator 104 calculates movement information representing the movement of the receiver 102. The movement information is used to perform movement compensation correlation of the received signals. From the movement compensation correlation process, the emitter locator 104 estimates the DoA of the received signals. The emitter locator 104 determines the locations of emitters 106, 108, 110 using the receiver positions along the DoA data. As will be described in detail below, the intersection of a plurality of DoA vectors generated as the receiver moves along path 118 identifies the locations of emitters 106, 108, 110.

[0097]

[0097] From the signal DoA data, the receiver 102 or the server 112 may create a map of emitter locations. In one embodiment, the location information may be stored in the receiver and later downloaded to a mapping application. In an alternative embodiment, the emitter locations may be transmitted continuously, periodically, or intermittently via cellular or WiFi communication to a server 112 where a mapping application creates a map of the emitter locations.

[0098]

[0098] In an alternative embodiment, the received signal may be processed to determine the time of arrival (TOA) or time difference of arrival (TDOA) information of the signal. As is known in the art, TOA and TDOA information may be used for emitter location calculation. Such calculations may be used to enhance DoA vector processing to improve the speed at which a location solution is obtained. Additionally, TOA and / or TDOA information may be used to identify delayed received signals indicative of non-line-of-sight (NLOS) signal paths. The DoA vectors associated with NLOS signals may be removed from the emitter location calculation to reduce the computational load and / or remove a source of location error.

[0099]

[0099] FIG. 2 is a block diagram of a receiver 102 according to at least one embodiment of the present invention. The receiver 102 includes a mobile platform 206, an antenna 202, a receiver front end 204, a signal processor 206, and a motion module 228. The receiver 102 may form part of a laptop computer, a mobile phone, a tablet computer, an Internet of Things (IoT) device, an unmanned aerial vehicle, a mobile computing system within an autonomous vehicle, a vehicle operated by a human, and the like.

[0100]

[0100] In the receiver 102, the mobile platform 200 and the antenna 202 are an inseparable unit in which the antenna 202 moves with the mobile platform 200. The operation of the SUPERCORRELATION™ technique operates based on determining the movement of the signal receiving antenna. Any reference to movement herein refers to the movement of the antenna 202. In some embodiments, the antenna 202 may be separate from the mobile platform 200. In such a situation, the motion estimation used in the motion compensation correlation process is the movement of the antenna 202. In most scenarios, the movement of the mobile platform 200 is the same as the movement of the antenna 202, and thus, in the following description, it is assumed that the movements of the platform 200 and the antenna 202 are the same.

[0101]

[0101] The mobile platform 200 includes a receiver front end 204, a signal processor 206, and a motion module 228. The receiver front end 204 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 204 is a digital signal containing data. The data of interest is a deterministic training or acquisition code, such as a Gold code, used by the emitter to synchronize the transmission to the transceiver.

[0102]

[0102] The signal processor 206 includes at least one processor 210, a support circuit 212, and a memory 214. The at least one processor 210 can be any form of processor or combination of processors, including but not limited to a central processing unit, microprocessor, microcontroller, field programmable gate array, graphics processing unit, digital signal processor, etc. The support circuit 212 may include well-known circuits and devices that facilitate the functions of the processor(s). The support circuit 212 can include one or more of power supplies, clock circuits, analog-to-digital converters, communication circuits, caches, displays, and / or the like, or combinations thereof.

[0103]

[0103] Memory 214 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. Memory 214 stores software and data including, for example, signal processing software 216, emitter location software 208, and data 218. Data 218 includes receiver location 220, direction-of-arrival (DOA) vector 222 (collectively DoA data), emitter location 224, and various data used to perform SUPERCORRELATION™ processing. When executed by one or more processors 210, signal processing software 216 performs motion-compensated correlation on the received signal to estimate the DOA vector of the received signal. The motion-compensated correlation process will be described in detail below. The operation of signal processing software 216 functions as emitter locator 104 of FIG. 1.

[0104]

[0104] As will be described in detail below, DOA vector 222 and receiver location 220 are used by emitter location software 208 to determine the location of each emitter. Data 218 stored in memory 214 may also include signal estimates, correlation results, motion compensation information, motion information, motion and other parameter hypotheses, location information, and the like.

[0105]

[0105] The motion module 228 generates a motion estimate of the receiver 102. The motion module 228 may include an inertial navigation system (INS) 230 and a global navigation satellite system (GNSS) receiver 226 such as GPS, GLONASS, GALILEO, BEIDOU, etc. The INS 230 may include one or more of, but is not limited to, a gyroscope, a magnetometer, an accelerometer, etc. To facilitate motion compensation correlation, the motion module 222 generates motion information (sometimes referred to as a motion model) including at least the velocity of the antenna 202 in the direction of the target emitter, i.e., the estimated direction of the source of the received signal. In some embodiments, the motion information may also include an estimated value of the orientation or direction of the platform, including, but not limited to, the pitch, roll, and yaw of the platform 200 / antenna 202. Generally, the receiver 102 may test all directions and iteratively narrow the search to one or more directions of interest.

[0106]

[0106] FIG. 3 shows a scenario 300 of the operation of the receiver 102 of FIGS. 1 and 2 according to at least one embodiment of the present invention. Scenario 300 includes the receiver 102 moving from position 1 to position 2 along path 302 and then to position 3 along path 304. As the receiver 102 traverses the area, the receiver 102 calculates a DoA vector 306 at position 1, 308 at position 2, and 310 at position 3. The three DoA vectors 306, 308, and 310 intersect at the location 312 of the emitter 106. Although three discrete positions are described as the locations where the DoA vectors are calculated, in other embodiments, the DoA vectors may be calculated periodically, intermittently, or continuously as the receiver moves. Additional vectors can be used to converge the solution to the exact emitter location. Further, the emitter 106 may be moving so that the convergence point can be tracked as it moves. The receiver 102 may be a single receiver or multiple different receivers that coordinate their data collection efforts. The DoA vectors are processed at a remotely located server and the emitter's location can be determined using vectors from different receivers.

[0107]

[0107] In an urban environment, some of the DoA vectors 302, 304, 306 are line-of-sight (LOS), and some of the DoA vectors 314 are non-line-of-sight (NLOS), i.e., the LOS vectors represent signals transmitted directly from the emitter 106 to the receiver 102, while the NLOS vectors may be reflected from structures 316 near the receiver 102. In one embodiment, received signals that can result in NLOS vectors (e.g., unwanted signals) can be ignored in DoA and location calculations. In another embodiment, as more DoA vectors are collected and processed, the LOS vectors converge to a particular location, e.g., location 312. Additionally, if TOA or TDOA information is available, this information may be used to remove DoA vectors of NLOS paths, because the arrival time is abnormal (delayed) for NLOS signals relative to LOS signals, i.e., the time information of NLOS signals includes a delay compared to LOS signals.

[0108]

[0108] In other embodiments, the structure 316 may be modeled with a building model. The building model can be used in conjunction with ray-tracing techniques to determine the DoA of the reflected signal. As a result, the path of the reflected emitter signal is estimated, and the reflected signal may be used in emitter location calculations.

[0109]

[0109] In other embodiments, one or more receivers 102 may collect all emitter signals, LOS and NLOS, over a period while the receiver traverses an area. These collected signals may be processed using the emitter location techniques described herein to create a signal profile of an area. The signal pattern includes DoA vector intersection regions that identify emitter locations. In some embodiments, a Bayesian estimator may be used to compare various hypotheses regarding the emitter location using the information provided by the available measurements.

[0110] Typically, the vector intersection location 312 is not a point, but rather an area or region due to the probabilistic nature of the DoA vectors, i.e., the determined direction of each vector has an uncertainty caused by measurement error and the intersection forms an area rather than a point. The intersection region forms the maximum value that defines the location of the emitter 106.

[0111]

[0111] Since the position of the receiver 102 is known by GNSS and / or INS calculations, the geographic location coordinates of the receiver 102 may be converted to the geographic location coordinates of the emitter location 312. Thus, a geographic location map of the emitter location may be generated. This scenario shows a receiver 102 that calculates the location 312 of a single emitter 106, but in various other embodiments, the receiver 102 may generate the locations of many nearby emitters sequentially and / or simultaneously.

[0112]

[0112] The foregoing embodiments perform emitter vector and location determination within the receiver 102. In other embodiments, data for generating DoA vectors, the DoA vectors themselves, location information, etc. (i.e., emitter data) may be transmitted from the receiver to a server (112 in FIG. 1) for processing to generate the emitter location.

[0113]

[0113] FIG. 4 is a flow diagram of an operating method 400 of signal processing software 216 according to at least one embodiment of the present invention. The method 400 can be implemented in software, hardware, or a combination of both (e.g., using the signal processor 206 of FIG. 2).

[0114]

[0114] Method 400 begins at 402 and proceeds to 404 where signals are received at a receiver from at least one remote source (e.g., transmitters such as emitters 106, 108, 110 of FIG. 1) in the manner described with respect to FIG. 1. Each received signal includes a synchronization or acquisition code, such as a Gold code, extracted from a radio frequency (RF) signal received by an antenna. The process of down-converting the RF signal and extracting the digital code is well known in the art. At 406, method 400 receives motion information from motion module 228 of FIG. 2. The motion information includes an estimate of the motion of receiver 102 of FIG. 1, which is, for example, one or more of speed, orientation, direction, etc.

[0115]

[0115] In some embodiments, the receiver uses a single local oscillator to receive emitter signals and to receive GNSS signals. Thus, prior to processing the emitter signals, the SUPERCORRELATION (trademark) technique is applied to the GNSS signals to facilitate improvement in position accuracy and to correct for local oscillator instability. As a result, the receiver position is very accurate and the local oscillator is stable over a long period of time such that a very long coherent integration time (e.g., 1 second) can be used for the processing of both GNSS signals and emitter signals.

[0116]

[0116] In 408, method 400 generates a plurality of phaser sequence hypotheses related to the direction of the target of the received signal. Each phaser sequence hypothesis includes a time-series phase offset estimate value that varies according to parameters such as the movement of the receiver, frequency, DoA of the received signal, etc. The signal processing correlates a local code encoded in the local signal with the same code encoded in the received RF signal. In one embodiment, the phaser sequence hypothesis is used to adjust the carrier phase of the local signal with sub-wavelength accuracy. In some embodiments, such adjustment or compensation may be performed by adjusting the local oscillator signal, the received signal(s), or the correlation result to generate a phase-compensated correlation result. The signal and / or correlation result is a complex signal including an in-phase component (I) and a quadrature phase component (Q). The method applies each phase offset within the phaser sequence to the corresponding complex sample within the signal or correlation result. If the phase adjustment includes an adjustment for the component of the movement of the receiver in the estimated direction of the emitter, the result is a movement-compensated correlation result. For each received signal, in 410, method 400 correlates the received signal with a set of (a plurality of) direction hypotheses that include an estimated value of the phase offset sequence required to accurately correlate the received signal arriving from a specific direction over a long coherent integration period (e.g., 1 second). There is a set of hypotheses representing the search space for each received signal and each parameter of the target, such as the movement of the receiver and / or the signal DoA.

[0117]

[0117] The motion estimate is typically a hypothesis of the motion in the direction of the target emitter that transmitted the received signal, i.e., if the rogue emitter is the target emitter, it generates a search space of hypotheses that includes the component of the receiver's motion in the direction of the rogue emitter. At initialization, the direction of the target is unknown or may be inaccurately estimated. As a result, an exhaustive search technique can be used to search over all directions and correlate the signals received in all directions to identify one or more directions of the target. The comparison of the correlation results over all directions enables method 400 to narrow the search space. The initial search may be intensive, but subsequent processing only requires tracking the receiver's motion and the signal DoA at the receiver as these hypotheses' true values have a very strong correlation between code iterations as their parameters evolve. As a result, subsequent compensation is performed over a narrow search space.

[0118]

[0118] In one embodiment, if a signal from a given emitter has been previously received, the set of hypotheses for the newly received signal includes a group of phaser sequence hypotheses that use the predicted frequency and frequency rate and / or the last frequency and the last frequency rate used when receiving the previous signal from that particular emitter. The values can be centered around the last value used or the last value offset and used further, by prediction of further offsets based on the expected movement of the receiver. At 410, method 400 correlates each received signal with the set of hypotheses for that signal. The hypotheses are used as parameters for forming a phase compensation phaser to phase compensate the correlation process. Thus, the phase compensation may be applied to the received signal, the local frequency source (e.g., oscillator signal), or the correlation result value. In addition to searching across the DoA space, method 400 may also apply hypotheses related to other variables (parameters) such as the oscillator frequency for correcting frequency and / or phase drift, or the orientation to ensure that the correct motion compensation is applied. The number of hypotheses may not be the same for each variable. For example, the search space may include 10 hypotheses for searching the DoA and 2 hypotheses for searching the receiver motion parameters such as speed, i.e., a total of 20 hypotheses (10×2). The result of the correlation process is a plurality of phase compensation correlation results, one phase compensation correlation result value for each hypothesis of each received signal.

[0119]

[0119] At 412, method 400 processes the correlation results to find the "best" or optimal result for each received signal. The correlation output may be a single value representing the parameter hypothesis (preferred hypothesis) that provides the optimal or best correlation output. Generally, to find the optimal correlation output corresponding to one or more preferred hypotheses, a cost function is applied to the correlation values for each received signal, e.g., the maximum correlation value is associated with the preferred hypothesis of the correct signal DoA.

[0120]

[0120] In 414, method 400 identifies the DoA vector of each received signal from the optimal correlation result of the signals. The received signals along the DoA vector usually have the strongest signal-to-noise ratio and represent the line-of-sight (LOS) reception between the emitter and the receiver. Thus, by using motion-compensated correlation, receiver 102 can identify the DoA vector of the received signal(s). Method 400 ends at 416.

[0121]

[0121] In other embodiments, instead of using the correlation value of the maximum magnitude, other test criteria may be used. For example, method 400 may monitor the progress of the correlation when a hypothesis is 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 the peaks of the correlation plot). In other embodiments, for example, additional hypotheses may be tested in addition to the DoA hypothesis to ensure that the motion compensation (i.e., speed and direction) is correct.

[0122]

[0122] FIG. 5 is a flowchart of an operation method 500 of location software 288 according to at least one embodiment of the present invention. Method 500 may be implemented locally within the receiver or remotely on the server. When implemented remotely, the DoA vector or the data for generating the DoA vector is transmitted from the receiver to the remote server for processing according to method 500.

[0123]

[0123] Method 500 starts at 502 and proceeds to 504, where method 500 receives the DoA vector of a specific emitter. At 506, method 500 determines the location where the DoA vectors intersect. The emitter location is relative to the location of the receiver. This process may be iterative as additional DoA vectors are generated, or may be calculated when a predefined number (e.g., 3, 5, 10, etc.) of DoA vectors have been determined. In some embodiments, TOA or TDOA information can be used to enhance the location calculation. For example, time information regarding the time at which a signal is received at various receiver locations can be used to identify LOS signals versus NLOS signals. For example, NLOS signals have a delayed reception time compared to LOS signals. Then, the DoA vectors associated with the NLOS signals may be removed from the set of vectors used to determine the emitter location.

[0124]

[0124] At 508, method 500 calculates the geographic location coordinates of the emitter location by converting the known geographic location coordinates of the receiver to the emitter location determined at 506. At 510, the method updates a map or database using the emitter geographic location such that a comprehensive list of emitter locations is created. At 512, the method queries whether a set of DoA vectors for another emitter is available for processing. If the query is answered affirmatively, method 500 returns to 504 to process additional DoA vectors. If the query is answered negatively, method 500 ends at 514.

[0125]

[0125] Embodiments of the present invention may be used to collect emitter data over time without processing the data, i.e., the emitter and receiver data are stored for subsequent processing as needed. For example, an autonomous vehicle can collect and store emitter and receiver data that will be processed after a traffic accident occurs. This processing may indicate that a GNSS spoofing emitter may have malfunctioned the vehicle's GNSS receiver and caused it to follow an incorrect route.

[0126]

[0126] Embodiments of the present invention may be used to process the collected mobile phone data. In this case, the mobile phone is the target emitter, and a patrol car having the above-described receiver embodiments collects emitter data for subsequent processing. When necessary, the emitter data from a receiver known to be in a crime area may be processed to determine the movement of a specific mobile phone over a specific period. Evidence of such movement can form useful evidence in an investigation.

[0127]

[0127] Once an unauthorized emitter is found, the emitter locator 104 may be a function of the mobile device such that the mobile device can take measures to suppress signals arriving from the DoA of the emitter using the location of the emitter. Such measures may involve changing the antenna pattern of the mobile device or may involve using the SUPERCORRELATION™ technique to suppress the reception of signals from the location of the emitter and / or enhance the reception of signals from legitimate emitters.

[0128]

[0128] Here, a plurality of examples are given to illustrate various features, and it is not intended to be so limited. Any one or more of the features may not be limited to the specific examples presented herein, regardless of the order, combination, or connection described. In fact, it should be understood that any combination of the features and / or elements described above as examples, including any variations or modifications that are not listed but are possible to achieve, is contemplated. Unless otherwise specified, any one or more of the features can be combined in any order.

[0129]

[0129] As described above, the drawings are presented herein for illustrative purposes and do not imply any structural limitations unless otherwise specified. Various modifications to any of the structures shown in the figures are considered to be within the scope of the invention presented herein. The present invention is not intended to be limited to any scope of the language of the claims.

[0130]

[0130] When "coupled" or "connected" is used, unless otherwise specified, the limitation that the coupling or connection is limited to a physical coupling or connection is not implied, and instead, it should be read to include communication couplings including wireless transmission and protocols.

[0131]

[0131] Any block, step, module, or other described herein may represent one or more instructions stored in a non-transitory computer-readable medium as software and / or implemented by hardware. Any such block, module, step, or other may be implemented by various combinations of software and / or hardware in an automated manner, including the use of dedicated hardware designed to achieve such purposes. As described above, any number of blocks, steps, or modules may be implemented in any order or not implemented at all, substantially simultaneously, i.e., within the tolerance of the system executing the blocks, steps, or modules.

[0132]

[0132] Although not limited, it should be understood that when conditional language including "can", "could", "may" or "might" is used, the related features or elements are not essential. Thus, when conditional language is used, elements and / or features should be understood as optionally present in at least some instances and, unless otherwise specified, do not necessarily condition anything.

[0133]

[0133] When a list is presented in the alternative or conjunctive (e.g., one or more of A, B, and / or C), it is understood to include any one or more combinations of any number of the listed elements (e.g., A, AB, AC, ABC, ABB, etc.) unless otherwise stated. It should be understood that when "and / or" is used, the elements may be combined in the alternative or conjunctive.

[0134]

[0134] While the foregoing is directed to embodiments of the present invention, other and further embodiments of the present invention may be devised without departing from its basic scope, which is determined by the following claims.

Claims

1. A method for obtaining authenticity information about a remote source, comprising: at a receiver, receiving a signal from the remote source in a first direction; providing a local signal; determining movement of the receiver; providing a correlation 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 correlation signal based on the determined movement in the first direction to provide a priority gain to the signal received along the first direction; identifying a remote source vector corresponding to a part of the propagation path of the received signal, the part being identical to the remote source, based on the correlation; generating the authenticity information about the remote source according to the remote source vector of the received signal; A method comprising the above steps.

2. The method according to claim 1, wherein the authenticity information is generated according to the signal type of the received signal.

3. The method according to claim 1 or 2, comprising generating the authenticity information to indicate that the remote source is an unauthorized source when an angle formed by the remote source vector and a horizontal direction is smaller than a predetermined threshold angle.

4. The method according to any one of claims 1 to 3, comprising generating the authenticity information to indicate that the remote source is an authorized source when an angle formed by the remote source vector and a horizontal direction is greater than a predetermined threshold angle.

5. The method further comprises: for each of a plurality of signals received at the receiver from the remote source, each of the signals being received in a respective first direction; providing respective local signals; determining respective movements of the receiver; providing respective correlation signals by correlating the respective local signals with the received signals; Based on the respective determined movements in the respective first directions, providing motion compensation for at least one of the respective local signals, the received signals, and the respective correlation signals to provide a priority gain to the signals received along the respective first directions; Identifying, based on the correlation, each remote source vector corresponding to a part of the propagation path of the received signal, wherein the part coincides with the remote source; The method according to any one of claims 1 to 4, further comprising.

6. The method is Further comprising generating location information of the remote source by identifying one or more locations where two or more of the respective remote source vectors of the plurality of received signals intersect; The method according to claim 5, wherein the legitimacy information is generated according to the location information.

7. The step of generating the legitimacy information according to the location information is Obtaining reference location data indicating one or more legitimate signal sources; Generating the legitimacy information based on a comparison between the generated location information and the reference location data; The method according to claim 6, comprising.

8. Obtaining reference geographical data corresponding to one or more geographical regions and including information indicating the expected presence of legitimate sources therein; Generating the legitimacy information according to the generated location information and the reference geographical data; The method according to claim 6 or 7, further comprising.

9. The reference geographical data includes expected source type information corresponding to the one or more geographical regions, The method according to claim 8, wherein the legitimacy information is generated according to a comparison between the source type information and one or more identified types of the plurality of received signals.

10. Further comprising generating source movement information indicating the movement state of the remote source based on the plurality of remote source vectors; The method according to any one of claims 5 to 9, wherein the legitimacy information is generated according to the source movement information.

11. Obtaining reference source movement data indicating the expected movement state of a legitimate remote source; generating the legitimacy information according to the generated source movement information and the reference source movement data; The method according to claim 10, further comprising.

12. The method includes generating first location information of the remote source by identifying one or more locations where two or more first sets of the plurality of remote source vectors intersect; generating second location information of the remote source by identifying one or more locations where two or more second sets different from the first set of the plurality of remote source vectors intersect; generating the source movement information based on the first location information and the second location information; The method according to claim 10 or 11, further comprising.

13. The generated source movement information includes a generated source movement path based on the first location information and the second location information, The reference source movement data includes an expected legitimate source movement path, The method according to claim 12, wherein the legitimacy information is generated according to a comparison between the generated source movement path and the expected source movement path.

14. The method according to any one of claims 1 to 13, further comprising storing the legitimacy information of the remote source in a remote source legitimacy dataset.

15. When the legitimacy information indicates that the remote source is an illegal source, performing a legitimacy verification for the remote source using the received signal; updating the legitimacy information according to the result of the legitimacy verification; The method according to any one of claims 1 to 14, further comprising.

16. The signal is a first positioning signal, and the legitimacy verification is performing a first positioning calculation based on a plurality of received positioning signals including the first positioning signal to obtain first location information of the receiver; performing a second positioning calculation based on a plurality of received positioning signals excluding the first positioning signal to obtain second location information of the receiver; obtaining a comparison between the first location information and the second location information; The method according to claim 15, including.

17. The method according to claim 15 or 16, wherein the validity verification includes obtaining source quality parameters of the remote source using the received signal.

18. The method according to claim 17, wherein the source quality parameters are obtained by calculating the quality of the frequency standard component of the remote source based on the received signal.

19. The method according to any one of claims 15 to 18, wherein the validity verification is based on the monitored polarization state of the received signal.

20. A system comprising: a local signal generator configured to provide a local signal; a receiver configured to receive a signal from a remote source in a first direction; a motion module configured to provide a determined movement of the receiver; a correlation unit configured to provide a correlation signal by correlating the local signal with the received signal; a motion compensation unit configured to provide motion compensation for at least one of the local signal, the received signal, and the correlation signal based on the determined movement in the first direction; a source vector unit configured to identify a remote source vector corresponding to a part of the propagation path of the received signal that matches the remote source based on the correlation; a validity information unit configured to generate validity information according to the remote source vector of the received signal; A system comprising the above.

21. A computer program product including executable instructions, which, when executed by a processor, cause the processor to: receive a signal from the remote source in a first direction at a receiver; provide a local signal; determine a movement of the receiver; provide a correlation signal by correlating the local signal with the received signal; provide motion compensation for at least one of the local signal, the received signal, and the correlation signal based on the determined movement in the first direction to provide a priority gain to a signal received along the first direction; identify a remote source vector corresponding to a part of the propagation path of the received signal, the part matching the remote source, based on the correlation. generating the authenticity information about the remote source according to the remote source vector of the received signal; A computer program product that causes steps including this to be performed.

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