Real-time radio mapping using correlation passive receivers

Abstract

Systems and methods are described for mapping locations and characteristics for wireless emitters, optionally including traffic participants such as allowing geolocation or speed measurement information to be tracked in real time. The systems and methods advantageously allow location and emitter class and type to be tracked in real time using a correlation receiver to observe emissions from wireless emitters without decoding or decode information contained in the emissions from the wireless emitters. Real-time geolocation and emitter class information for many receivers in a geographic area can be determined and overlaid on a map or used in autonomous vehicle navigation applications and can be useful in reducing the computational burden associated with tracking the locations of many multiple emitters using direct sensor measurements.

Description

[Technical field]

[0001] This application claims the benefit of and priority to U.S. Provisional Application No. 63 / 193,519, filed May 26, 2021, and U.S. Provisional Application No. 63 / 193,520, filed May 26, 2021, the contents of which are incorporated by reference in their entirety for all purposes. [Background technology]

[0002] Techniques have been developed for the estimation of wideband spectral correlation functions and / or cyclic autocorrelation functions. The spectral correlation functions and cyclic autocorrelation functions can be rich in information and provide statistical insight into the received signal. There is a need in the art for improved methods and systems associated with using the spectral correlation and cyclic autocorrelation information. Summary of the Invention

[0003] Aspects described herein relate to the field of mapping and classification of wireless emitters, with particular application of systems and methods for mapping locations and characteristics associated with wireless emitters by observing emissions from the wireless emitters without decoding or decodeing the information contained in the emissions from the wireless emitters.

[0004] According to an aspect, a method of mapping wireless emitters in a geographic region is provided. In one example, the method of the aspect includes generating signal input pairs by receiving wireless emissions from a plurality of wireless emitters at a first antenna pair, and processing the signal input pairs using a correlation receiver to determine a set of geolocation information for the plurality of wireless emitters. Optionally, the method may further include repeating one or more times generating additional signal input pairs by receiving wireless emissions from the plurality of wireless emitters at additional antenna pairs, and processing the signal input pairs using a correlation receiver to determine an additional set of geolocation information for the plurality of wireless emitters. For example, one or both antennas of the antenna pair are the same or different from one or both antennas of the additional antenna pair. Optionally, the additional set of geolocation information corresponds to more accurate geolocation information for the plurality of wireless emitters.

[0005] In some examples, processing the signal input pairs using the correlation receiver can include determining a time difference of arrival (TDOA) for the wireless radiation received at each antenna of the antenna pair. As an example, processing the signal input pairs using the correlation receiver can include determining an angle of arrival (AoA) for the wireless radiation received at each antenna of the antenna pair. In some examples, the method of mapping wireless emitters in a geographic region further includes overlaying the set of geolocation information for the multiple wireless emitters on geographic or network map data. Optionally, the process of generating the signal input pairs by receiving wireless radiation from multiple wireless emitters at an antenna pair (e.g., one or both antennas of the antenna pair are the same or different from one or both antennas of a further antenna pair) and processing the signal input pairs using the correlation receiver to determine the set of geolocation information for the multiple wireless emitters can be repeated one or more times over time to enable tracking of the geolocation information of the multiple wireless emitters over time.

[0006] In some examples, the correlation receiver can use different antennas to receive the various radio emissions, or can use the same antennas. A group of three or more antennas can be used, for example, in different pairwise combinations to provide different antenna pairs for receiving the various radio emissions. In some cases, the radio emissions can be received at three or more antennas, and the antennas can be paired in different combinations to provide different signal pairs that can be processed by the correlation receiver, for example, to provide more accurate geolocation information.

[0007] The correlation receiver may be useful in processing the signal inputs to mitigate or remove interference from noise, such as natural sources of high frequency radiation. In some examples, processing the signal input pairs using the correlation receiver includes determining a cyclic autocorrelation function or a spectral correlation function of the signal input pairs. Optionally, processing the signal input pairs using the correlation receiver includes removing noise using the cyclic autocorrelation function or the spectral correlation function.

[0008] The correlation receiver may be useful in determining the class or type of multiple wireless emitters by analyzing pairs of signal inputs, for example, an emission signature may be determined and compared to known emission signatures for different classes or types of wireless emitters, and this information may optionally be paired with geolocation information for the multiple wireless emitters.

[0009] In another example, a method of mapping a plurality of wireless emitters in a geographic region includes obtaining a set of signal inputs corresponding to wireless emissions from a plurality of wireless emitters received at three or more antennas, processing the set of signal inputs to determine a plurality of cyclic autocorrelation functions or spectral correlation functions for a plurality of signal input pairs of the set of signal inputs using a correlation receiver, and determining a set of geolocation information of the plurality of wireless emitters using the cyclic autocorrelation functions or spectral correlation functions. Optionally, one or more of the antennas are directly coupled to the correlation receiver. Optionally, one or more of the antennas are located remotely from the correlation receiver. Optionally, determining the set of geolocation information of the plurality of wireless emitters includes determining a set of velocities of the plurality of wireless emitters.

[0010] Advantageously, the methods described herein may determine a set of geolocation information for multiple wireless emitters in real-time or substantially real-time, such as within a short period of reception of wireless emissions (e.g., 10 seconds or less, 5 seconds or less, or 1 second or less). Additionally, the methods of this aspect may be used to simultaneously determine the geolocation information of all detectable emitters within a particular geographic region.

[0011] Optionally, the method may further include overlaying the set of geolocation information onto a geographical, network, or symbolic map or onto the geographical, network, or symbolic map data. Optionally, the method of this aspect may further include transmitting the set of geolocation information, or a subset thereof, to a remote server. In this manner, the geolocation information of the emitters can be determined and, optionally, tracked as a function of time.

[0012] To determine a set of geolocation information for the multiple wireless emitters, the correlation receiver can process the signal inputs in a pairwise manner. For example, a first signal input pair corresponding to signals received at two of the antennas can be processed, a second signal input pair corresponding to signals received at two of the antennas can be processed, and a third signal input pair corresponding to signals received at two of the antennas can be processed. Using three antennas A1, A2, and A3, three pairs can be used: A1 and A2, A2 and A3, and A1 and A3. In some examples, processing the set of signal inputs includes processing multiple signal input pairs from different pairs of three or more antennas using the correlation receiver to determine a set of time delays associated with receiving wireless radiation at the three or more antennas, determining a set of angles of arrival of the wireless radiation at the three or more antennas using the set of time delays, and determining a set of geolocation information for the multiple wireless emitters using the set of angles of arrival. By determining at least three sets of angles of arrival, a location of each wireless emitter can be identified.

[0013] In some examples, additional information about each wireless emitter can be obtained from the cyclic autocorrelation function or the spectral correlation function, which can optionally be useful for fingerprinting and / or tracking wireless emitters over time. In some examples, the method may further include analyzing one or more of the cyclic autocorrelation function or the spectral correlation function to identify a set of classes or types of the plurality of wireless emitters. Optionally, the set of geolocations and the set of classes or types of the plurality of wireless emitters may be overlaid on a geographical, network, or symbolic map or on the geographical, network, or symbolic map data.

[0014] In some examples, various portions of the method may be repeated one or more times. For example, the method may include repeating one or more of: obtaining a set of new signal inputs corresponding to wireless emissions from a plurality of wireless emitters received at three or more antennas; processing the set of new signal inputs to determine a plurality of new cyclic autocorrelation functions or spectral correlation functions for a plurality of signal input pairs of the set of new signal inputs using a correlation receiver; and determining a new set of geolocation information for the plurality of wireless emitters using the new cyclic autocorrelation functions or the new spectral correlation functions. In this manner, the methods described herein may track a set of geolocation information for a plurality of wireless emitters and one or more new sets of geolocation information over time.

[0015] In another aspect, a system for mapping a plurality of wireless emitters in a geographic region is described. An example system of this aspect includes a correlation receiver, three or more antennas disposed in data communication with the correlation receiver, and one or more processors, also in data communication with the correlation receiver. To accomplish the mapping, the correlation receiver may be configured to process a set of signal inputs corresponding to wireless emissions from the plurality of wireless emitters received at the three or more antennas to determine a plurality of cyclic autocorrelation or spectral correlation functions for a plurality of signal input pairs of the set of signal inputs. Additionally, the one or more processors may be configured to determine a set of geolocation information of the plurality of wireless emitters using the cyclic autocorrelation or spectral correlation functions. Optionally, determining the set of geolocation information of the plurality of wireless emitters includes determining a set of velocities of the plurality of wireless emitters.

[0016] Optionally, one or more of the antennas are directly coupled to the correlation receiver. Optionally, one or more of the antennas are located remotely from the correlation receiver. Optionally, determining the set of geolocation information for the multiple wireless emitters occurs in real-time or substantially real-time.

[0017] In some examples, a correlation receiver configured to perform an operation may include arranging elements in a particular configuration such that various signals are generated and / or processed by the arrangement of elements of the correlation receiver. In some examples, a correlation receiver and / or one or more processors configured to perform an operation may optionally include programming these components with instructions, such as processor-executable instructions, which may be stored on one or more non-transitory processor-readable storage media, that when executed by the processor cause the processor to perform the operation.

[0018] In some examples, the one or more processors are further configured to overlay the set of geolocation information onto a geographical, network, or symbolic map, or onto the geographical, network, or symbolic map data. Optionally, the one or more processors are further configured to transmit the set of geolocation information, or a subset thereof, to a remote server.

[0019] In some examples, processing the set of signal inputs includes processing a plurality of pairs of signal inputs from different pairs of three or more antennas using a correlation receiver to determine a set of time delays associated with receiving the wireless radiation at the three or more antennas, determining a set of angles of arrival of the wireless radiation at the three or more antennas using the set of time delays, and determining a set of geolocations of the plurality of wireless emitters using the set of angles of arrival. In some examples, the one or more processors are further configured to analyze one or more of the cyclic autocorrelation function or the spectral correlation function to identify a set of classes or types of the plurality of wireless emitters. Optionally, the one or more processors are further configured to overlay the set of geolocations and the set of classes or types of the plurality of wireless emitters onto a geographical map, a network map, or a symbolic map, or onto the geographical map data, the network map data, or the symbolic map data.

[0020] In some examples, the correlation receiver is further configured to repeat one or more times: obtaining a set of new signal inputs corresponding to wireless emissions from a plurality of wireless emitters received at the three or more antennas; processing the set of new signal inputs to determine, using the correlation receiver, a plurality of new cyclic autocorrelation functions or new spectral correlation functions for a plurality of signal input pairs of the set of new signal inputs. In some examples, the one or more processors are further configured to repeat one or more times: determining a set of new geolocations of the plurality of wireless emitters using the new cyclic autocorrelation functions or new spectral correlation functions; and tracking the set of geolocations of the plurality of wireless emitters and the one or more new geolocations over time.

[0021] Many advantages are achieved by the present invention over the prior art. For example, the described aspects provide a method and system for real-time processing of radio frequency (RF) input signals, which allows for real-time passive tracking of transmitter location and type without requiring the ability to decode the content of the RF input signal. These and other embodiments of the present invention, along with many of its advantages and features, are described in more detail in conjunction with the following text and accompanying figures.

[0022] Aspects described herein also relate to the field of mapping and classification of wireless emitters and reflections of radiation from wireless emitters, with particular application of the disclosed systems and methods to mapping locations and characteristics of traffic participants for use by autonomous vehicles by observing active emissions or radiation reflections from the traffic participants.

[0023] According to an aspect, a method for determining geolocation information of traffic participants is provided. The method includes generating a signal input pair by receiving wireless radiation associated with a plurality of traffic participants at an antenna pair, and processing the signal input pair using a correlation receiver to determine a set of geolocation information and speed measurement information for the plurality of traffic participants. Optionally, the method may include generating an additional signal input pair by receiving an additional wireless radiation associated with the plurality of traffic participants at an antenna pair, and processing the additional signal input pair using a correlation receiver to determine an additional set of geolocation information or speed measurement information for the plurality of traffic participants. Optionally, the method may include determining speed measurement information (e.g., speed vectors) for the plurality of traffic participants based on the set of geolocation information for the plurality of traffic participants and the time differences therebetween. In some examples, the additional signal pairs can be used to determine more accurate geolocation information and speed measurement information for the plurality of traffic participants, such as by receiving the additional signal input pair using at least one different antenna or at least one antenna displaced from the antenna used to receive the preceding signal input pair.

[0024] The geolocation and speed information may be provided to and used by the autonomous vehicle, such as to provide information about the traffic environment to recognize and detect other traffic participants and their speeds and projected routes. Example traffic participants include, but are not limited to, vehicles (e.g., internal combustion engine vehicles, electric drive vehicles, bicycles), pedestrians, etc.

[0025] In some examples, the wireless radiation associated with the traffic participant includes wireless radiation generated by a wireless emitter at the traffic participant. For example, such a wireless emitter may be a component of a vehicle, such as, for example, a collision transducer, a parking emitter, a wireless transmitter, etc. In some examples, such a wireless emitter may be a wireless device carried by a driver or passenger of the vehicle. In some examples, such a wireless emitter may be a wireless device carried by a pedestrian.

[0026] However, in some examples, a traffic participant may not carry or house a wireless device that generates the wireless radiation. In such cases, the wireless radiation associated with the traffic participant may include wireless radiation reflected by the traffic participant. For example, such wireless radiation may be reflected by a vehicle body. Optionally, the method may further include generating new wireless radiation and sending the new wireless radiation toward one or more traffic participants to generate reflected radiation, which may then be received at the antenna pair and geolocation information and / or speed information for the traffic participants without their own wireless device may be determined.

[0027] Optionally, the correlation receiver and / or antenna pair is located in an autonomous vehicle, such as an autonomous vehicle that is a traffic participant. In some cases, the method may include providing, such as by wireless communication, the set of geolocation information of the plurality of traffic participants and the speeds of the plurality of traffic participants to other autonomous vehicles that are traffic participants.

[0028] In some examples, the correlation receiver and / or antenna pair may not be a component of any traffic participant, but may instead be located at a location outside the traffic environment. For example, the method may further include providing, such as via wireless communication, the set of geolocation information of the plurality of traffic participants and the speeds of the plurality of traffic participants to an autonomous vehicle that is a traffic participant.

[0029] It will be appreciated that processing the signal input pairs using the correlation receiver can include determining a time difference of arrival (TDOA) for the radio radiation received at each antenna of the antenna pair. As an example, processing the signal input pairs using the correlation receiver can include determining an angle of arrival (AoA) for the radio radiation received at each antenna of the antenna pair. Optionally, the process of generating the signal input pairs by receiving radio radiation at the antenna pair and processing the signal input pairs using the correlation receiver to determine a set of geolocation information for the traffic participants can determine the geolocation information of all traffic participants simultaneously. Optionally, the process of generating the signal input pairs by receiving radio radiation at the antenna pair and processing the signal input pairs using the correlation receiver to determine a set of geolocation information for multiple traffic participants can be repeated one or more times to enable tracking of the geolocation information and speeds of multiple traffic participants over time.

[0030] ] In some examples, the correlation receiver can use different antennas or the same antennas to receive radio emissions from multiple traffic participants. In some examples, the correlation receiver can use different antennas or the same antennas to receive radio emissions from multiple traffic participants over time. A group of three or more antennas can be used, for example, in different pairwise combinations to provide different antenna pairs for receiving various radio emissions. In some cases, a single radio emission can be received at three or more antennas. The antennas can be paired in different combinations to provide different signal pairs. These signal pairs can be processed by the correlation receiver, for example, to obtain more accurate geolocation information.

[0031] The correlation receiver may be useful in processing the signal inputs to mitigate or remove interference from noise, such as natural sources of high frequency radiation. In some examples, processing the signal input pairs using the correlation receiver includes determining a cyclic autocorrelation function or a spectral correlation function of the signal input pairs. Optionally, processing the signal input pairs using the correlation receiver includes removing noise using the cyclic autocorrelation function or the spectral correlation function.

[0032] The correlation receiver may be useful in determining the class or type of wireless emitter by analyzing pairs of signal inputs, for example, a radiation signature may be determined and compared to known radiation signatures for different classes or types of wireless emitters, and this information may optionally be paired with geolocation information for multiple traffic participants.

[0033] In one aspect, the disclosure provides a method for determining location and speed measurement information of traffic participants by an autonomous vehicle, such as for use in determining navigation instructions for the autonomous vehicle. In some examples, the method of this aspect includes obtaining a set of signal inputs corresponding to wireless emissions associated with a plurality of traffic participants received at three or more antennas, processing the set of signal inputs to determine a plurality of cyclic autocorrelation functions or spectral correlation functions for a plurality of signal input pairs of the set of signal inputs using a correlation receiver, determining a set of geolocation information and / or speed measurement information for the plurality of traffic participants using the cyclic autocorrelation functions or spectral correlation functions, and determining, by a data processor in the autonomous vehicle, navigation instructions for the autonomous vehicle using the set of geolocation information and / or the speed measurement information. In some examples, the correlation receiver may be a component of the autonomous vehicle, and the autonomous vehicle corresponds to a traffic participant of the plurality of traffic participants, while other examples may use a correlation receiver separate from the autonomous vehicle. In some examples, the wireless emissions associated with the traffic participants may include wireless emissions generated by a wireless emitter at the traffic participant (e.g., a wireless emitter in a vehicle or a wireless emitter carried by a pedestrian). Optionally, the radio emissions associated with the traffic participant include radio emissions reflected by the traffic participant.

[0034] As described in more detail herein, the signal inputs can be processed using a correlation receiver to obtain information about the emissions. In an example, processing the set of signal inputs includes processing a plurality of pairs of signal inputs from different pairs of three or more antennas using the correlation receiver to determine a set of time delays associated with receiving the wireless emissions at the three or more antennas, determining a set of angles of arrival of the wireless emissions at the three or more antennas using the set of time delays, and determining a set of geolocation information of the plurality of wireless emitters using the set of angles of arrival. In some examples, the method of this aspect may further include analyzing one or more of the periodic autocorrelation function or the spectral correlation function to identify a set of classes or types of the plurality of wireless emitters.

[0035] In some cases, more accurate geolocation information is useful or desirable for use by the autonomous vehicle. In such cases, additional signal inputs may be acquired. For example, the method may further include repeating the acquiring and processing one or more times and determining additional or more accurate geolocation information and speed measurement information for the multiple traffic participants.

[0036] In some cases, a traffic participant may not include a wireless emitter, but it may still be desirable and possible to track such a traffic participant using the techniques described herein. For example, wireless emissions may be reflected from the traffic participant (e.g., off a vehicle body or other component), and these reflected emissions may be used to generate a signal input. In some examples, the method may further include generating new wireless emissions and sending the new wireless emissions toward the multiple traffic participants, where the wireless emissions include reflections of the new wireless emissions from at least one traffic participant.

[0037] If the correlation receiver is remote from the autonomous vehicle, the method may further include wirelessly transmitting the set of geolocation information and the speed measurement information to the autonomous vehicle for use in determining or applying navigation instructions for the autonomous vehicle. Several methods can be used to share the geolocation information and the speed measurement information with other autonomous vehicles, since not all vehicles may include a correlation receiver but may still benefit from the information. In some examples, the method may include or may further include providing the set of geolocation information and the speed measurement information to other autonomous vehicles corresponding to a traffic participant of the plurality of traffic participants.

[0038] In another aspect, systems such as a system for determining location and speed measurement information of traffic participants are described herein. An example system of this aspect may include three or more antennas, a correlation receiver arranged in data communication with the three or more antennas, e.g., the correlation receiver configured to process a set of signal inputs corresponding to wireless emissions associated with a plurality of traffic participants received at the three or more antennas to determine a plurality of cyclic autocorrelation functions or spectral correlation functions for a plurality of signal input pairs of the set of signal inputs, and one or more processors. The one or more processors may be configured to determine a set of geolocation information and / or speed measurement information for the plurality of traffic participants using the cyclic autocorrelation functions or spectral correlation functions, and to determine navigation instructions for the autonomous vehicle using the set of geolocation information and / or the speed measurement information. Optionally, the correlation receiver and the one or more processors are components of the autonomous vehicle. Optionally, the correlation receiver and the one or more processors are remote from the autonomous vehicle, and the one or more processors may be further configured to transmit the set of geolocation information and / or the speed measurement information to the autonomous vehicle.

[0039] In some examples, this may include arranging elements of a correlation receiver in a particular configuration such that various signals are generated and / or processed by an arrangement of elements. In some examples, configuring the correlation receiver and / or one or more processors to perform operations may include programming these components with instructions, such as processor-executable instructions, which may optionally be stored in one or more non-transitory processor-readable storage media, that when executed by the processor cause the processor to perform the operations.

[0040] The correlation receiver may optionally be further configured to repeat one or more times obtaining a set of new signal inputs corresponding to wireless emissions associated with a plurality of traffic participants received at the three or more antennas and processing the set of new signal inputs to determine, using the correlation receiver, a plurality of new periodic autocorrelation functions or spectral correlation functions for a plurality of signal input pairs of the set of new signal inputs. The one or more processors may optionally be further configured to determine further or more accurate geolocation and speed measurement information for the plurality of traffic participants.

[0041] In some examples, processing the set of signal inputs includes processing a plurality of pairs of signal inputs from different pairs of three or more antennas using a correlation receiver to determine a set of time delays associated with receiving the wireless emissions at the three or more antennas, determining a set of angles of arrival of the wireless emissions at the three or more antennas using the set of time delays, and determining a set of geolocation information of the plurality of wireless emitters using the set of angles of arrival. In some examples, the one or more processors are further configured to analyze one or more of a periodic autocorrelation function or a spectral correlation function to identify the set of classes or types of the plurality of wireless emitters.

[0042] Optionally, the wireless radiation associated with the traffic participant includes wireless radiation generated by a wireless emitter at the traffic participant. Optionally, a traffic participant of the plurality of traffic participants includes a vehicle or a pedestrian. Optionally, the wireless radiation associated with the traffic participant includes wireless radiation reflected by the traffic participant.

[0043] Optionally, the one or more processors are further configured to provide the set of geolocation information and the speed measurement information to one or more other autonomous vehicles corresponding to a traffic participant of the plurality of traffic participants.

[0044] The present embodiments and examples described herein achieve many advantages over the prior art. For example, the described aspects provide a method and system for real-time processing of radio frequency (RF) input signals, which enables real-time passive tracking of transmitter location and type for use in autonomous driving applications without requiring the ability to decode the content of the RF input signal. These and other embodiments and examples, along with many of their advantages and features, are described in more detail in conjunction with the following text and accompanying figures.

[0045] Aspects of the present disclosure will now be described more fully below with reference to the accompanying drawings, which are intended to be read in conjunction with both this summary, the detailed description, and any exemplary, preferred and / or specific embodiments specifically described or otherwise disclosed. However, various aspects may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided merely as examples so that this disclosure will be thorough and complete, and will fully convey its full scope to those skilled in the art. [Brief description of the drawings]

[0046] [Figure 1] 1 is a schematic diagram showing reception of radio radiation at two different antennas and the angle of arrival of the radio radiation; [Diagram 2]1 is a schematic diagram of an example correlation receiver system in accordance with some examples of the present disclosure. [Diagram 3] FIG. 1 is a three-dimensional plot illustrating an example cyclic autocorrelation function. [Figure 4] FIG. 2 is a two-dimensional plot illustrating an example cyclic autocorrelation function. [Diagram 5] FIG. 11 is a two-dimensional plot illustrating another example cyclic autocorrelation function for a time-delayed signal. [Figure 6] 1 is a schematic diagram of an example correlation receiver system in accordance with some examples of the present disclosure. [Figure 7] 1 is a schematic diagram of a distribution of multiple antenna systems and / or correlation receiver systems over a geographical area. [Figure 8] FIG. 1 illustrates an example plot showing geolocation information of detected wireless emitters. [Figure 9] FIG. 1 illustrates an example plot showing geolocation information of detected wireless emitters overlaid with emitter characteristics. [Figure 10] FIG. 1 illustrates a simplified flowchart detailing a method for mapping a plurality of wireless emitters within a geographic region, according to certain examples of the present disclosure. [Figure 11] 1 is a schematic diagram of a number of traffic participants and the use of a correlation receiver system used to determine geolocation information of the traffic participants; [Figure 12] FIG. 2 illustrates a simplified flowchart detailing a method for determining location and / or speed measurements of a traffic participant, according to some examples of the present disclosure. [Figure 13] FIG. 2 illustrates a simplified flowchart detailing a method for determining location and / or speed measurements of a traffic participant, according to some examples of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0047] Electromagnetic (e.g., radio frequency) emissions produced by wireless emitters (e.g., cell phones or other radio frequency devices) are typically broadcast by the wireless emitters and received by appropriate base stations (e.g., cell phone base stations). Wireless service providers, such as cellular service providers, have the ability to receive, decode, and decode transmissions produced by wireless emitters operating on their networks. This allows the wireless providers to obtain a wealth of information about the signals broadcast by the wireless emitters, including access to the data content within the transmissions. In some cases, the wireless emitters can determine their location, such as by receiving transmissions from a global positioning satellite (GPS), and this information can be provided to the wireless service provider as data content in the transmission. In addition to using GPS location information, wireless service providers can also obtain triangulated location information for the emitters using multiple base stations.

[0048] Without access to the signal content of the transmissions or the service provider's network, it may be difficult or impractical to determine location information for a large number of emitters in a dense geographic area. Generally, geolocation of emitters requires cooperation by the network operator or emitters, and in their absence (where cooperative access to multiple networks and emitters is not feasible), it is not possible to map all emitters of interest.

[0049] However, because wireless emitters broadcast their transmissions as physical electromagnetic radiation, they can generally be detected by any system with suitable antennas located within a suitable detection range, provided the receiver has the ability to distinguish noise and interference from the emitter signal. This can be accomplished without decoding or decode the information content, and location information about the wireless emitter can be determined based on the received power of the radiation, the frequency of the radiation, etc. This can also be accomplished without decoding or decode the information content, and location information about the wireless emitter can be determined based on the received power and the frequency of the radiation, etc. In such a system, if the radiation can be detected using multiple antennas separated by known distances, further details such as more precise location information can be obtained (e.g., using triangulation or similar techniques).

[0050] Modern wireless transmissions typically involve digitally modulated signals that encode digital data using one or more modulation techniques, such as using keying techniques like phase shift keying (PSK), frequency shift keying (FSK), amplitude shift keying (ASK), or quadrature amplitude modulation (QAM), or other modulation techniques. These modulated signals may contain characteristics that are repeated in nature, and the underlying data contained therein may be encoded or encrypted using a variety of techniques.

[0051] Also, different types of wireless emitters may emit with different physical characteristics, such as frequency, bandwidth, modulation type or rate, bit rate, etc., which may also vary based on the wireless service being used or based on the wireless service provider's configuration. For example, using known wireless emitter capabilities, specific information about individual wireless emitters can be determined by detecting physical electromagnetic emissions, again without decoding or decrypting the content.

[0052] Where multiple or millions of wireless emitters are distributed throughout a city or other geographic area, a network of antennas may be provided to allow for tracking of the locations of the wireless emitters, but such a network would be comparable to existing base station networks (e.g., cellular networks) and would require infrastructure, equipment, and access to physical locations to install the antennas, which would be subject to various regulations, franchise requirements, ownership or lease requirements, etc., increasing the complexity of such a network and limiting its feasibility.

[0053] According to the embodiments described herein, a class of receivers is provided that can overcome such problems, allowing a small set of antennas to be used to track many wireless emitters in a geographic region or traffic environment. For example, a correlation receiver can be used. In contrast to conventional receivers that include only a single antenna, the correlation receiver has two inputs to accommodate at least two antennas. This allows the correlation receiver to determine the time difference for the radiated signals received at the two antenna inputs and the frequency difference of arrival for the radiated signals received at the two antenna inputs, thereby enabling accurate location determination of the wireless emitter. It will be appreciated that the time difference of arrival can be used and the angle of attack of the radiated signals incident on the two antenna inputs can be derived from each other, and these aspects may be used interchangeably in some cases. Furthermore, the radiated signals received from the two antenna inputs can be correlated to remove noise (e.g., natural noise), identify and extract originating signals (e.g., man-made or artificial signals such as those generated by wireless emitters) from background radiation, provide radiation characteristics of the received signals, or provide modulation signatures of the received signals to assist, for example, in emitter classification.

[0054] Correlation receivers can be used to determine the location and classification of wireless emitters at distances well outside the typical operating range required for wireless communication. This may be true because data in the electromagnetic radiation does not need to be recovered by the correlation receiver, effectively reducing the required signal-to-noise ratio and allowing correlation receivers to be placed much farther away than would be required for a typical base station. A typical base station typically establishes a bidirectional link with the wireless emitters and, as a result, is often placed in reasonable proximity to the wireless emitters. In this way, a single or small set of correlation receivers can be placed within or at the edge of a geographic region and still be useful in tracking the location and characteristics of emitters across the geographic region.

[0055] Advantageously, the location information can be used by autonomous vehicles to reduce the computational burden that might otherwise result from location processing using sensor data (e.g., by ultrasonic ranging, etc.).

[0056] In one aspect, a real-time correlation receiver, such as for geolocation of a wireless communication device, is described. In some examples, the real-time correlation receiver includes signal inputs obtained from two spatially separated antennas capable of receiving radio frequency signals in a spectral range greater than 10 MHz, a real-time correlator operating on the two signal inputs in either the time domain or the frequency domain, and a processor that measures or determines one or more of a time difference of arrival between the two signal inputs, an angle of attack of electromagnetic radiation incident on the two antenna inputs, and / or a frequency difference of arrival between the two signal inputs.

[0057] In another aspect, a real-time correlation receiver for geolocation of traffic participants and the like is described, which may be useful, for example, in autonomous driving applications. In some examples, the real-time correlation receiver includes signal inputs obtained from two spatially separated antennas capable of receiving radio frequency signals in a spectral range above 10 MHz, a real-time correlator operating on the two signal inputs in either the time domain or the frequency domain, and a processor that measures or determines one or more of a time difference of arrival between the two signal inputs, an angle of attack of electromagnetic radiation incident on the two antenna inputs, and / or a frequency difference of arrival between the two signal inputs.

[0058] Advantageously, the real-time correlation receiver described herein can remove or separate man-made emissions by removing naturally occurring emission noise or interference. Optionally, the real-time correlation receiver may separate moving and fixed emissions, such as for purposes of identifying user or emitter classes.

[0059] In some examples, the correlation is initiated or performed by digitizing the input signals and computing their Fourier transform to calculate the spectral correlation. In some examples, the correlation is realized or performed by varying the delay between the two signal inputs, multiplying the two, and taking a time integral of the product. Optionally, the delay function is realized or performed using a variable length physical waveguide. Optionally, the delay function is realized or performed using a combination of a tunable oscillator and a dispersive waveguide. Optionally, the multiplication function is realized or performed by an optical or high frequency mixer element. Optionally, the multiplication function is realized or performed by a coherent optical detector.

[0060] Various outputs of the real-time correlation receiver may be used. In some examples, the output is a Spectral Correlation Function (SCF) or a Cyclic Autocorrelation Function (CAF). Optionally, the real-time correlation receiver may generate SCF and CAF outputs for purposes of determining the geolocation of the emitter and its velocity measurement. Optionally, the real-time correlation receiver may generate SCF and CAF outputs for purposes of identifying the type of service the emitter is using. Optionally, the real-time correlation receiver may generate SCF and CAF outputs for purposes of identifying physical parameters of the emitter. Without limitation, example physical parameters may include one or more of the following: frequency and operating band of the emission, modulation cycle, coding type used to modulate the emission, spectral and time response of the transmitter generating the emission, hardware type including the particular emitter, or directivity of the emission.

[0061] The real-time correlation receiver can operate at a variety of high frequencies. In some examples, the operating range is 10 kHz to 4 GHz. In some examples, the operating range is 10 kHz to 30 GHz. In some examples, the operating range is 10 kHz to 110 GHz. Optionally, the real-time correlation receiver operates in the LTE spectrum range. Optionally, the real-time correlation receiver operates in the 5G spectrum range. Optionally, the real-time correlation receiver can have or provide a geolocation accuracy of 2 feet or better, for example, for radiation in a range of 10 feet to 100 feet away. Optionally, the real-time correlation receiver can have or provide a geolocation accuracy of 2 feet or better, for example, for radiation in a range of 100 feet to 1000 feet away.

[0062] In some examples, the real-time correlation receiver may share its output with a different, spatially separate real-time correlation receiver, such as at a remote vehicle or traffic participant. Optionally, the two signal inputs are achieved by accessing different pairs of spatially separated antennas. In some cases, the real-time correlation receiver includes or is equipped with more than two antennas. Optionally, the real-time correlation receiver may include or access multiple antennas in a pair-wise manner using two inputs.

[0063] The geolocation data obtained by the real-time correlation receiver can be used in various applications. In an example, the radiated geolocation data generated by the real-time correlation receiver can be transposed on a geographic map. In an example, the radiated geolocation data generated by the real-time correlation receiver can be transposed on a network map. In an example, the radiated geolocation data generated by the real-time correlation receiver can be transposed on a symbolic map, such as a symbolic map used to facilitate exchange of services or used to promote communication security. Optionally, the radiated geolocation data generated by the real-time correlation receiver can be used to provide location-specific services and information.

[0064] The geolocation data obtained by the real-time correlation receiver can be used in various applications. For example, the geolocation information can correspond to the geolocation information of emissions associated with a vehicle carrying at least one wireless emitter (e.g., a wireless communication device). In some examples, the emissions and / or the geolocation information can be associated with an internal combustion engine vehicle or an electric engine vehicle. Optionally, the emissions and / or the geolocation information can be associated with a non-engine propulsive traffic participant, such as a pedestrian or a bicycle. Optionally, the emissions can be reflected emissions, such as reflected from a vehicle or a traffic participant, such as a pedestrian. Optionally, the emissions can originate from a ranging or collision avoidance transmitter of the vehicle, and / or such emissions from a ranging or collision avoidance transmitter of the vehicle can be reflected by other traffic participants.

[0065] Optionally, the real-time correlation receiver may calculate velocity measurement information for the emitter, such as by monitoring or tracking the geolocation information as a function of time. Velocity measurement information may optionally be determined for multiple or all emissions identified or detected.

[0066] Correlation receivers can be used to enable location information for wireless emitters to be determined, and emitter characteristics to be determined. All of this is based on simply detecting the presence of wireless radiation, without decoding or decoding the data in the wireless radiation. Because the presence of wireless radiation can be detected at a much greater range than that required to decode or decode the data, the signal-to-noise ratio can be much smaller than that required for wireless communication, and the useful range for a correlation receiver can be much greater than that for wireless communication. Correlation receivers can also improve the rejection of noise, such as background or natural high frequency noise, because they can operate using pair-wise combination of signals from multiple antenna inputs.

[0067] A variety of different correlation receivers can be used, such as cyclostationary receivers. However, such receivers, when used for real-time detection of radio frequency radiation, may be limited to GHz-scale frequency ranges or less if conventional (all-electronic implementations) are used. Hybrid correlation receivers, combining analog and digital processing, are useful for scaling the effective frequency range to tens of GHz while still operating in real time and providing extension to frequencies with shorter nominal propagation ranges. Further details on spectral correlation and analysis can be found in U.S. Patent Application No. 16 / 236,038 (filed December 28, 2018), Publication No. US2019 / 0339548 (published November 7, 2019), now U.S. Patent No. 11,137,627 (incorporated herein by reference).

[0068] Correlation Receiver System A time modulated signal x(t) can be analyzed using spectral correlation, such as to determine characteristics about the signal itself without evaluating the data content in the signal. Spectral correlation has been used in signal detection, for example in telecommunication systems. The spectral correlation function of a cyclostationary process describes the cross-spectral density (or coherence) of all pairs of frequency-shifted versions of a time series. By computing the spectral correlation, the stochastic part of the cyclostationary process (i.e., noise) disappears while the deterministic part with periodic characteristics appears.

[0069] Cyclostationarity and higher order (cumulant) analysis are based on the fact that the correlation (i.e., moment) properties of signals and noise are different. A signal with modulation x(t), e.g., radio emissions, has an inherent periodic autocorrelation function defined as the Fourier transform of the signal and its delayed copies, as shown in equation (1):

number

number

number

number

number

[0070] Periodic autocorrelation function of a modulated signal

number

number

number

number

[0071] Obtaining a cyclic autocorrelation function and / or a spectral correlation function of a wireless emission may allow for determining characteristic information about the emission, such as carrier frequency, bandwidth, bit rate, modulation type, etc. For use in determining geolocation information about an emitter, multiple spatially separated antennas may be used in a variation of the cyclic autocorrelation, referred to herein as cyclic cross-correlation. If two antennas are separated from each other by a distance, they may both receive the same wireless emission, but there may be a time delay t between the received signals. D , which is a function of the distance between the antennas. Instead of determining the correlation of the received signal x(t) with itself (autocorrelation), the signals received at two different antennas (x1(t) and x2(t)) can be correlated with each other.

number

number

[0072] FIG. 2 is a block diagram of a correlation system 200 useful for determining periodic autocorrelation, periodic cross-correlation, and / or spectral correlation functions. The correlation system 200 may provide a means for solving the Wigner equation (i.e., Equation (1)) and its variants in the optical domain without the iterative calculations typically required to obtain the solution. With reference to FIG. 2, the correlation system 200 may include a master laser 205, a first optical tuner 215, a dispersive element 225, a second optical tuner 230, and an optical comb filter 240. The master laser 205 may be, for example, without limitation, a low linewidth semiconductor laser or other laser. The master laser 205 may generate a self-referenced optical frequency comb signal 210 of signals at different optical wavelengths (i.e., colors, or tones). The tones of the optical frequency comb signal 210 may be modulated in the first optical tuner 215 by a first input signal corresponding to a radio frequency (RF) signal received at a first antenna 220. The x1(t) first optical tuner 215 may generate N spectral copies of the first input signal x1(t) at the tones of the optical frequency comb signal 210.

[0073] The N spectral copies of the first input signal x1(t) may be sent to a dispersive element 225. The dispersive element 225 may be an optical fiber dispersive element, such as, without limitation, a single mode fiber or other dispersive element. The dispersive element 225 determines a wavelength-dependent time delay τ between adjacent spectral copies of the first input signal x1(t). k The time delay corresponds to a phase shift in the frequency domain. A delayed spectral copy of the first input signal x1(t) (i.e., x1(t-τ1)...x1(t-τ N )) may be sent to the second optical modulator 230.

[0074] The second optical modulator 230 may modulate the delayed spectral copy of the first input signal x1(t) with a conjugate x2*(t) of the second input signal x1(t) corresponding to a radio frequency (RF) signal received at the second antenna 235, which may include a time delayed version of the first input signal x1(t). The second optical modulator 230 modulates the conjugate modulated spectral copy of the delayed spectral copy (i.e., x2*(t)x1(t-τ1)...x2*(t)x1(t-τ N )) which results in the conjugate modulation of the delayed spectral copies of the input signal x1(t) being integrated to obtain the cyclic autocorrelation or cross-correlation coefficients.

number

[0075] The conjugate-modulated spectral copy may be sent to an optical comb filter 240, which may be, for example, without limitation, a high-resolution etalon or other optical comb filter. The optical comb filter 240 performs integration of the conjugate-modulated spectral copy to eliminate all the time delays τ k For example, the Nth integrated conjugate-modulated spectral copy may be generated for each repetition frequency α i For (i=1,2,...N) τ N Cyclic autocorrelation coefficients corresponding to delays

number

[0076] 2 further includes components for reading out the cyclic autocorrelation coefficients. For example, correlation system 200 may include a radio frequency (RF) oscillator 245, a third optical dimmer 250, e.g., a single sideband (SSB) modulator or other modulator, an optical wavelength splitter 260, a 90° hybrid optical module 265, and multiple detectors D1-D2. N 270. A plurality of detectors D1 to D N 270 may be a coherent receiver. RF oscillator 245 may generate a swept frequency. The signal generated by master laser 205 and the swept frequency generated by RF oscillator 245 may be input to third optical dimmer 250.

[0077] The third optical tuner 250 may shift the signal generated by the master laser 205 in frequency, for example, by several gigahertz or other amount, and may use this frequency-shifted signal to generate a second optical frequency comb 255. The frequency pitch of the second optical frequency comb 255 may be the same as the original frequency comb 210 used to spectrally clone the input signal x1(t). However, the comb teeth of the second optical frequency comb 255 may be swept by several gigahertz following the swept RF oscillation 245. The generated frequency comb may be referred to herein as a swept optical sampling signal. The swept optical sampling signal may be swept at a rate lower than the frequency of the master laser signal, for example, at a frequency of about 25 kHz or other frequency.

[0078] The swept optical sampling signal and the integrated conjugate modulated spectral copy may be combined by a 90° hybrid optical module 265. The 90° hybrid optical module 265 may function as a coherent receiver and may output four signals: the modulation signal plus the local oscillator signal, the modulation signal minus the local oscillator signal, the conjugate of the modulation signal plus the local oscillator signal, and the conjugate of the modulation signal minus the local oscillator signal. The output signals of the hybrid optical module 265 may be input to the optical wavelength demultiplexer 260.

[0079] The optical wavelength demultiplexer 260 may include multiple demultiplexer modules. In some embodiments, four demultiplexer modules may be used. Each demultiplexer module may be configured to demultiplex one output of the hybrid optical module 265. The demultiplexed signals may be detected by multiple detectors 270. Multiple detectors D1-D N 270 may be a coherent detector. In some embodiments, each coherent detector may include two balanced detectors, each balanced detector may have two PIN diodes (i.e., a total of four PIN diodes for each coherent detector). N Each of the detectors D1-D270 receives a signal from each of a plurality of demultiplexer modules. For example, in an embodiment using four demultiplexer modules, each of the detectors D1-D270 receives a signal from each of the plurality of demultiplexer modules. N receives a signal from each demultiplexer module, i.e., each detector D1 to D N receives four signals.

[0080] Detectors D1 to D N Each of the τ k The cyclic autocorrelation (cross-correlation) coefficients may be coherently detected for each of the detectors D1 to D N streams the coefficients simultaneously,

number

number

number

[0081] Correlation system 200 may include other components, such as processors, input or output devices, control devices, memory devices, storage devices, and the like, in addition to those illustrated in FIG. 2. It will be appreciated that correlation system 200 provides only one example of a correlation receiver, and other implementations may be used instead. For example, certain aspects of correlation system 200 may be implemented using digital system components. For example, all-electronic implementations of correlation receivers may be used, as well as hybrid correlation receivers that combine analog and digital signal processing cores. In some examples, when analog signals from an antenna are measured as a function of time, these analog signals may be quantized using one or more analog-to-digital converters. A Fast Fourier Transform (FFT) may be performed on the digital data to obtain the frequency spectrum of the signal received at the antenna.

[0082] Figures 3, 4 and 5 show the cyclic autocorrelation function for a 1 GHz symbol rate BPSK signal with a root raised cosine filter for antennas spaced 1 m apart, showing both the symbol-based and carrier frequency-based features. In Figure 3, the plot shows the data as a 3D plot, while Figure 4 shows the same data as a 2D plot. In Figure 5, the symbol-based feature is centered at τ=0 ns, and the delay time t between the signals received at the two antennas is t D In Fig. 5, the symbol-based feature is shifted to the right and centered at τ = 0.5 ns, and the delay time t Dis approximately 0.5 ns. Based on this information, and using Equation 4 above, the angle of arrival for the signal shown in Figure 4 is 90°, and the angle of arrival for the signal shown in Figure 5 is 81°.

[0083] In some examples, in contrast to the configuration in correlation system 200 shown in FIG. 2, determining the periodic autocorrelation or spectral correlation function can be accomplished using an antenna that is remote from the correlation system. For example, correlation system 600 shown in FIG. 6 accommodates other components that allow for the use of a remote antenna, similar to correlation system 200. For example, instead of an antenna being directly coupled to the first optical dimmer and the second optical dimmer, correlation system 600 includes a first input subsystem 620 coupled to the first optical dimmer 615 and a second input subsystem 635 coupled to the second optical dimmer 630. Although illustrated as separate subsystems in FIG. 6, input subsystems 620 and 635 can be the same component. Correlation system 600 can include other components beyond those illustrated, such as a processor, an input or output device, a control device, a memory device, a storage device, etc.

[0084] Input subsystems 620 and 635 receive remote modulated signals x instead of the modulated signals provided by antennas 220 and 230 in correlation system 200. γ (t), where the remote modulated signal x γ (t) may correspond to an antenna signal received at correlation system 600 from a remote antenna system. For example, FIG. 6 illustrates three remote antenna systems 650, 651, and 652, each including its own antenna 655, 656, and 657, respectively. Remote antenna systems 650, 651, and 652 may include components for acquiring, digitizing, and transmitting signals received at the corresponding antennas as digital data to correlation system 600. Here, first and second input subsystems 620 and 635, respectively, may use the digital data to modulate a modulated signal xγ (t) and can be provided to the first and second optical modulators 615 and 630. For example, the remote antenna systems 650, 651, and 652 can include amplifiers, analog-to-digital converters, and other components to receive, digitize, and / or process the radiated signals received at the corresponding antennas and communicate the received signals as digital data to the correlation system 600 (e.g., via wireless or wired digital communication). In some examples, the remote antenna systems can include processors or other components to convert the received and digitized radiated signals, for example, to determine a Fourier transform of the radiated signals and / or to determine the conjugate of the radiated signals or the Fourier transform, and / or to compress or encode the digital data. Although three remote antenna systems 650, 651, and 652 are shown in FIG. 6, any desired number of additional antenna systems can be used. Additionally, while one or more antennas may be directly incorporated into the correlation system 600, various advantages may be obtained by using multiple remote antennas.

[0085] For example, by using remote antenna systems, correlation system 600 can obtain periodic autocorrelation or spectral correlation functions in a pair-wise manner between any or all antenna pairs, as desired. In the configuration illustrated in FIG. 6, for example, input subsystem 620 can use antenna signals from remote antenna system 650 and input subsystem 635 can use antenna signals from remote antenna system 651. Additionally or alternatively, input subsystem 620 can use antenna signals from remote antenna system 651 and input subsystem 635 can use antenna signals from remote antenna system 652. Additionally or alternatively, input subsystem 620 can use antenna signals from remote antenna system 652 and input subsystem 635 can use antenna signals from remote antenna system 650. Reverse antenna pair assignments may be used. In this manner, each of the three antenna pairs may be used to determine the angle of arrival of the received radiation, and the angle of arrival may be used to determine the precise location of the emitter.

[0086] Emitter Location Tracking 7 illustrates a schematic diagram of a multiple antenna system 700 arranged about a geographic area including an emitter 785 that generates radio frequency radiation 790. The geographic area may be a city, a town, or any desired subset thereof. In some examples, the geographic area may be a cell or portion thereof within a cellular network, such as a macrocell area, a microcell area, etc.

[0087] In this example, the antenna system 700 may include a remote antenna system or correlation system, whereby the antennas 751, 752, 753, and 754 receive periodic autocorrelation functions and / or spectral correlation functions for the radiation 790 and delay times t DThe angles of arrival may be used in any pair-wise combination to determine the angle of arrival at the emitter 785 by determining: Using the angle of arrival, geolocation information (e.g., geographic coordinates relative to the antennas) can be determined for the emitter 785. If the absolute geographic coordinates of one or more of the antennas are known, the geolocation information can be absolute geographic coordinates (e.g., x and y, or latitude and longitude, etc.) relative to the emitter.

[0088] If multiple emitters 785 are present within a geographic region, geolocation information for each emitter can be similarly obtained in the same manner and using the same antenna pair, provided the antennas are capable of receiving the emissions. In some cases, narrowband antennas can be used to sensitively monitor a subset of the radio frequency spectrum, but mixed signal receivers can cover a much larger band of the radio frequency spectrum to determine geolocation information for a greater number and variety of emitters. Advantageously, geolocation information for all emitters 785 can be obtained simultaneously using pair-wise antennas as described herein to obtain periodic autocorrelation and / or spectral correlation functions.

[0089] It will be appreciated that the antenna system 700 can be located at a very long distance from the emitter 785 and still be useful for determining geolocation and other information. For example, the signal-to-noise ratio required to determine the geolocation of the emitter 785 by the techniques described herein can be significantly less than the signal-to-noise ratio required to receive and decode the data transmission made by the emitter 785. A correlation receiver can be used to determine the location and classification of a wireless emitter at a distance well outside the typical operating range required for wireless communication. This may be true because data in the electromagnetic radiation does not need to be recovered by the correlation receiver, effectively reducing the required signal-to-noise ratio and allowing the correlation receiver to be located much farther than would be required for a typical base station. A typical base station typically establishes a bidirectional link with the wireless emitter and, as a result, is often located in reasonable proximity to the wireless emitter. In this manner, a single or small set of correlation receivers can be located within or at the edge of a geographic region and still be useful for tracking the location and characteristics of the emitter across the geographic region. Furthermore, correlation receivers useful in the systems and methods described herein can provide high discrimination against noise. For example, a cyclic autocorrelation function and / or a spectral correlation function can confine noise to specific locations because the signal is correlated to itself. In a spectral correlation function, the noise is confined to a specific correlation or repetition frequency (α=0), while the modulated signal can rise above the detection floor elsewhere to provide a modulation signature. In a cyclic autocorrelation function, the noise is confined to the origin of the map at a specific correlation or repetition frequency (α) and time delay (τ).

[0090] With geolocation information available for multiple emitters, such information can be overlaid on a map or other coordinate system to show the distribution of emitter locations. Figure 8 shows an example coordinate system showing the x and y coordinates of various different emitters 885 in an 8 km x 10 km geographic area, as determined by the correlation system described herein using at least three antennas in a pair-wise manner, as previously described.

[0091] Additional information about each emitter can be determined by further examining the cyclic autocorrelation function and / or the spectral correlation function obtained to determine the geolocation information of the emitter 885. For example, the location and number of features in the cyclic autocorrelation function and / or the spectral correlation function can provide a physical signature that provides details about the emitter, since different types of wireless emitters emit with different physical characteristics, such as the frequency and operating band of the emission, the modulation cycle, the coding type used to modulate the emission, the spectrum and time response of the transmitter generating the emission, etc., which may also vary based on the wireless service in use, based on the hardware type that includes the particular emitter, or based on the configuration of the wireless service provider. For example, using known wireless emitter capabilities, specific information about individual wireless emitters can be determined by detecting the physical electromagnetic emissions, again without decoding or decoding the content. This can be achieved by analyzing the amplitude or phase of the features in the cyclic autocorrelation function and / or the spectral correlation function, and / or by using a pattern matching function against the known signature. Further details regarding techniques for analyzing signals using correlation receivers are provided in U.S. Patent Application Serial No. 17 / 681,629, which is incorporated herein by reference in its entirety. In some cases, a database of known emitter types can be used to match the physical signature information to the emitter type, class, manufacturer, and / or model.

[0092] In some examples, the emitter type or class may be paired or overlaid with a map or other coordinate system to show the distribution of emitter locations and their type or class. Figure 9 shows an example coordinate system showing the x and y coordinates of various different emitters 985 in an 8 km by 10 km geographic area, including a type or class identifier. This information may be shown, for example, when the map or coordinate system is displayed on a graphical user interface, as icon information for the emitters, or in a configuration that allows for zooming in to expand details about a particular emitter.

[0093] 10 is a simplified flow chart illustrating a method 1000 of mapping multiple wireless emitters in a geographic region according to an embodiment of the present invention. At block 1005, a signal input pair is generated by receiving wireless emissions from multiple wireless emitters at an antenna pair. The distance between the antennas in the pair may be known, and wireless signals may be received at each antenna, possibly at different times. For example, each antenna may generate a time-dependent modulated voltage signal, which may be provided as an input signal to a correlation receiver.

[0094] In block 1010, the signal input pairs are processed by a correlation receiver to determine a set of geolocation information for multiple wireless emitters. As a first step in the process, the time-dependent voltage signal may be quantized using an analog-to-digital converter or the like. Optionally, a Fourier transform of the time-dependent signal may be performed to convert the signal into frequency space. The signal may then be spectrally correlated using an autocorrelation function to extract features such as time difference of arrival (TDOA) or angle of arrival (AoA) to be determined, and the features may be used to determine the geolocation information of the wireless emitters.

[0095] At block 1015, an emission signature may optionally be determined for the signal input pair to determine a set of multiple classes or types of wireless emitters. For example, the emission signature may identify the physical parameters of the wireless emitter (e.g., frequency capability, bit rate capability, etc.) and the class(es) of service (e.g., service provider) that the wireless emitter is using. This information may also be combined with geolocation information.

[0096] At block 1020, the geolocation information may be evaluated to determine whether geolocation information for the multiple wireless emitters has been obtained with sufficient accuracy. If not, process 1000 may branch at decision point 1025 to block 1030, where additional signal inputs may be generated by receiving additional wireless emissions from the multiple wireless emitters, such as using one or more different antennas, or one or more antennas displaced from those used in block 1005. The process may return to block 1010, where processing may be repeated on the additional signal inputs to determine updated geolocation information for the multiple wireless emitters.

[0097] If, at block 1020, it is determined that the geolocation information has been obtained with sufficient accuracy, the process 1000 may branch at decision point 1025 to block 1035. Here, the geolocation information may be overlaid on a map, such as a geographical map, optionally with class or type information. The process of generating a signal by receiving wireless emissions and processing to determine the geolocation information may be repeated as a function of time, allowing the geolocation information of multiple wireless emitters to be tracked over time. Advantageously, continuous tracking of the geolocation information combined with a corresponding class or type of wireless emitter allows individual wireless emitters to be accurately tracked. The geolocation information, type or class information, mapping information, etc. may be provided as a data stream to one or more receivers.

[0098] It should be appreciated that the specific steps illustrated in FIG. 10 provide a particular method for mapping wireless emitters within a geographic region in accordance with an embodiment of the present invention. Alternative embodiments may perform other sequences of steps. For example, alternative embodiments of the present invention may perform the steps outlined above in a different order. Additionally, individual steps illustrated in FIG. 10 may include multiple sub-steps that may be performed in various orders as appropriate for the individual step. Additionally, additional steps may be added or removed depending on the particular application. Those skilled in the art will recognize numerous variations, modifications, and alternatives.

[0099] Tracking the location of transit participants 11 shows a schematic diagram of multiple traffic participants. The illustrated traffic participants include vehicles 1150 and 1155 as well as a pedestrian carrying a wireless emitter 1185 (e.g., a cellular phone) that generates radio frequency radiation 1190.

[0100] In this example, vehicle 1150 may include a correlation system and may include antennas 1151 and 1152, and vehicle 1155 may include a remote antenna system and may include antenna 1156. In some examples, vehicles 1150 or 1155 may be equipped with additional or fewer antennas than those illustrated. For example, vehicle 1150 may use pairwise combinations of various antennas 1151, 1152, and 1156 to determine the angle of arrival at emitter 1185 using a periodic autocorrelation function and / or a spectral correlation function for radiation 1190 and a time delay t D In some examples, antennas of the fixed antenna system 1153 may be used for pair-wise combining and determining the angle of arrival to the emitter 1185. Using the angle of arrival, geolocation information (e.g., relative geographic coordinates from the antenna) can be determined for the emitter 1185.

[0101] Although a single emitter is illustrated in FIG. 11, each of the vehicles 1150 and 1155, and any other traffic participants or other emitters, may be present in the area, and geolocation information for each emitter may be obtained in the same manner, and using the same or different antenna pairs. In some cases, narrowband antennas may be used to sensitively monitor a subset of the high frequency spectrum, but a mixed signal receiver may cover a much larger band of the high frequency spectrum, allowing geolocation information for a large number and type of emitters to be determined. Advantageously, geolocation information for all emitters may be obtained simultaneously using pair-wise antennas as described herein to obtain periodic autocorrelation and / or spectral correlation functions.

[0102] It will be appreciated that the antenna systems and correlation systems used to determine geolocation information can be located at extremely long distances from the emitters / traffic participants and still be useful for determining geolocation information and other information. For example, the signal-to-noise ratio required to determine the geolocation information of an emitter / traffic participant by the techniques described herein can be significantly less than the signal-to-noise ratio required to receive and decode the data transmissions made by the emitters / traffic participants. A correlation receiver can be used to determine the location and classification of a wireless emitter / traffic participant at a distance well outside the typical operating range required for wireless communication, although in traffic situations the range is typically very close. This may be true because data in the electromagnetic radiation does not need to be recovered by the correlation receiver, effectively reducing the required signal-to-noise ratio and allowing the correlation receiver to be located much farther away than would be required for a typical base station. A typical base station typically establishes a bidirectional link with the wireless emitter and, as a result, is often located in reasonable proximity to the wireless emitter. In this way, one or more fixed antenna systems can be located proximally from the traffic area adjacent to the vehicle of interest, and still provide a useful input signal to the correlation receiver system that allows the determination of the geolocation tracking of the emitter in the traffic flow. Furthermore, the correlation receiver useful in the systems and methods described herein can provide high discrimination against noise. For example, a cyclic autocorrelation function and / or a spectral correlation function can confine noise to a specific location because the signal is correlated to itself. In a spectral correlation function, the noise is confined to a specific correlation or repetition frequency (α=0), while the modulated signal can rise above the detection floor elsewhere to provide a modulation signature. In a cyclic autocorrelation function, the noise is confined to a specific correlation or repetition frequency (α) and the origin of the time delay (τ) map.

[0103] With geolocation information available for multiple emitters / traffic participants, such information can be used in conjunction with other information available to a vehicle (e.g., a self-driving or autonomous vehicle) to mitigate or reduce the computational burden on the vehicle from generating and / or processing short-range, computationally intensive signals, such as LiDAR signals, or otherwise assist the vehicle in determining the locations of various traffic participants.

[0104] In some examples, some traffic participants may not include wireless emitters, but the systems, methods, and techniques described herein may still be useful for determining geolocation information for at least some of these traffic participants. For example, a correlation receiver or antenna system may generate wireless emissions that are intended to be at least partially reflected from the traffic participants, and then switch to a receive mode in which the reflected emissions are monitored in the same manner as active emissions are analyzed herein. In some cases, the potential wireless emissions may intentionally include specific radiation characteristics, such as frequency, bandwidth, modulation type, etc., to provide easy discrimination against other wireless emissions or noise, but this is merely optional, since the systems and methods described herein may strongly discriminate against noise or other emissions due to the cross-correlation aspects of the receiver.

[0105] In some cases, the geolocation information of any traffic participant may be overlaid on a map, coordinate system, or other user interface to visualize the distribution of emitter locations, etc. Additional information about each emitter may be determined by further examining the cyclic autocorrelation function and / or the spectral correlation function obtained to determine the geolocation information of the emitter. For example, the location and number of features in the cyclic autocorrelation function and / or the spectral correlation function may provide a physical signature that provides details about the emitter, since different types of wireless emitters emit with different physical characteristics, such as the frequency and operating band of the emission, the modulation cycle, the coding type used to modulate the emission, the spectrum and time response of the transmitter generating the emission, etc., which may also vary based on the wireless service in use, the hardware type that includes the particular emitter, or based on the configuration of the wireless service provider. For example, using known wireless emitter capabilities, specific information about individual wireless emitters may be determined by detecting the physical electromagnetic emissions, again without decoding or decoding the content. This can be accomplished by analyzing the amplitude or phase of features in the periodic autocorrelation function and / or the spectral correlation function, and / or by using pattern matching functions against known signatures. Further details regarding techniques for analyzing signals using correlation receivers are described in U.S. Patent Application Serial No. 17 / 681,629, which is incorporated by reference in its entirety. In some cases, a database of known emitter types can be used to match the physical signature information to emitter types, classes, manufacturers, and / or models. In some examples, the emitter types or classes can be paired or overlaid with a map or other coordinate system to show the distribution of emitter locations and their types or classes.This information may be shown, for example, as icon information for the emitters when a map or coordinate system is displayed on a graphical user interface, or in a configuration where expanded detail about a particular emitter can be zoomed in.

[0106] FIG. 12 is a simplified flow chart illustrating a method 1200 of determining location and / or speed measurements of traffic participants, such as by an autonomous vehicle, according to an example for use in determining navigation instructions. At block 1205, a signal input pair is generated by receiving radio emissions associated with multiple traffic participants at an antenna pair. The distance between the antennas in the pair may be known, and the radio emissions may be received at each antenna, possibly at different times. For example, each antenna may generate a time-dependent modulated voltage signal, which may be provided as an input signal to a correlation receiver. The antennas may be located in or on the autonomous vehicle, although embodiments are contemplated in which the antennas are located outside the autonomous vehicle and the signal inputs are transmitted wirelessly to the autonomous vehicle.

[0107] At block 1210, the signal input pairs are processed by a correlation receiver in the autonomous vehicle to determine a set of geolocations of the multiple traffic participants and optionally speed measurements. As a first step in the process, the time-dependent voltage signal may be quantized using an analog-to-digital converter or the like. Optionally, a Fourier transform of the time-dependent signal may be performed to convert the signal into frequency space. The signal may then be spectrally correlated using an autocorrelation function to extract features such as time difference of arrival (TDOA) or angle of arrival (AoA) to be determined, and the features may be used to determine the geolocations of the multiple traffic participants or wireless emitters associated with the traffic participants. Optionally, an emission signature may be determined for the first signal input pair to determine a class or type of wireless emitter associated with the multiple traffic participants. For example, the emission signature may identify the physical parameters of the wireless emitter (e.g., frequency capability, bit rate capability, etc.) and the class of service (e.g., service provider) that the wireless emitter is using. This information may be combined with the geolocation information.

[0108] At block 1215, the geolocation information and speed measurement information may be evaluated to determine whether geolocation information and speed measurements for the traffic participants have been obtained with sufficient accuracy. If not, the process 1200 may branch at decision point 1220 to block 1225. Here, further signal inputs may be generated by receiving further wireless emissions associated with the multiple traffic participants, for example, by using one or more different antennas, or one or more antennas displaced from those used at block 1205. This may of course be the case if the antennas are in or on the autonomous vehicle and the autonomous vehicle is moving. The process may return to block 1210, where the processing may be repeated for the further signal inputs to determine updated speed measurements and geolocation information for the multiple traffic participants. Optionally, the further signals and processing may be used to determine acceleration, a predicted path, a predicted location, or a predicted speed.

[0109] If it is determined at block 1215 that the geolocation and speed measurement information has been obtained with sufficient accuracy, then process 1200 may branch at decision point 1220 to block 1230, where the geolocation and speed measurement information may be provided to the autonomous vehicle. The process may take place within the autonomous vehicle so that the information can be used by the autonomous vehicle itself to determine navigation instructions. In some cases, the geolocation and speed measurement information may be wirelessly communicated to other autonomous vehicles. In some cases, further geolocation and speed measurement information may also be received from other autonomous vehicles and used along with the geolocation and speed measurement information determined by the autonomous vehicle to determine navigation instructions.

[0110] 13 is a simplified flow chart illustrating a method 1300 of determining location and / or speed measurements of a traffic participant according to an example. At block 1305, a signal input pair is generated by receiving radio emissions associated with multiple traffic participants at an antenna pair, such as antennas located outside a particular autonomous vehicle for which navigation directions are to be determined. The distance between the antennas in the pair may be known, and the radio emissions may be received at each antenna, possibly at different times. For example, each antenna may generate a time-dependent modulated voltage signal, which may be provided as an input signal to the correlation receiver.

[0111] In block 1310, the signal input pairs are processed by a correlation receiver to determine a set of geolocations of the multiple traffic participants and optionally speed measurements. The correlation receiver may be located outside a particular autonomous vehicle for which navigation instructions are to be determined, e.g., a particular autonomous vehicle that is a traffic participant among the multiple traffic participants. As a first step in the process, the time-dependent voltage signal may be quantized using an analog-to-digital converter or the like. Optionally, a Fourier transform of the time-dependent signal may be performed to convert the signal into frequency space. The signal may then be spectrally correlated using an autocorrelation function, so that features such as time difference of arrival (TDOA) or angle of arrival (AoA) can be extracted to be determined. The features may then be used to determine geolocations of the multiple traffic participants or wireless emitters associated with the traffic participants. Optionally, a radiation signature may be determined for the first signal input pair to determine a class or type of wireless emitter associated with the multiple traffic participants. For example, the emission signature can identify the physical parameters of the wireless emitter (e.g., frequency capabilities, bit rate capabilities, etc.) and the class of service (e.g., service provider) that the wireless emitter is using. This information may be combined with geolocation information.

[0112] At block 1315, the geolocation information and speed measurement information may be evaluated to determine whether geolocation information and speed measurements for the traffic participants have been obtained with sufficient accuracy. If not, the process 1300 may branch at decision point 1320 to block 1325, where further signal inputs may be generated by receiving further wireless emissions associated with the multiple traffic participants, such as using one or more different antennas, or one or more antennas displaced from those used at block 1305. The process may return to block 1310, where the processing may be repeated on the further signal inputs to determine updated speed measurements and geolocation information for the multiple traffic participants. Optionally, the further signals and processing may be used to determine acceleration, a predicted path, a predicted location, or a predicted speed.

[0113] If at block 1315 it is determined that the geolocation information and speed measurement information have been obtained with sufficient accuracy, process 1300 may branch at decision point 1320 to block 1330, where the geolocation information and speed measurement information may be provided to the autonomous vehicle via wireless data communication, etc. Optionally, the antenna pair and / or correlation receiver may be located at a fixed location outside of a particular autonomous vehicle. Optionally, the antenna pair and / or correlation receiver may be located in other autonomous vehicles, such as other autonomous vehicles that are traffic participants of a plurality of traffic participants.

[0114] The process of generating and processing signals by receiving radio emissions can be used to simultaneously determine geolocation information for as many traffic participants as are within the detection range of the antenna. Similarly, the process of generating signals by receiving radio emissions and processing to determine geolocation information can be repeated for radio emitters as a function of time, allowing the geolocation information of the radio emitters to be tracked over time. Advantageously, continuous tracking of geolocation information combined with a corresponding class or type of radio emitter allows individual radio emitters to be accurately tracked and their location predicted. The geolocation information, type or class information, speed measurement information, etc. can be optionally provided as a data stream to one or more other traffic participants.

[0115] It should be understood that the specific steps illustrated in Figures 12 and 13 provide a specific method for determining geolocation information of traffic participants according to some examples. Other order of steps may be performed according to alternative embodiments. For example, the steps outlined above may be performed in a different order in alternative embodiments. Also, the individual steps illustrated in Figures 12 and 13 may include multiple sub-steps that may be performed in various orders as appropriate for the individual step. Also, additional steps may be added or removed depending on the particular application. Those skilled in the art will recognize many variations, modifications, and alternatives.

[0116] As used herein, "comprising" is synonymous with "including," "containing," or "characterized by," is inclusive or open-ended, and does not exclude further, unrecited elements or method steps. As used herein, "consisting of" excludes any element, step, or ingredient not specified in the claim element. As used herein, "consisting essentially of" does not exclude steps or materials that do not materially affect the basic and novel characteristics of the claim. Any recitation herein of the term "comprising," particularly in the description of a component of a composition or the description of an element of a device, is understood to encompass compositions and methods consisting essentially of and consisting of the recited components or elements. The embodiments illustratively described herein may suitably be practiced in the absence of any element(s) or limitation(s) not specifically disclosed herein.

[0117] Moreover, the terms and expressions employed herein are used as terms of description rather than of limitation, and the use of such terms and expressions is not intended to exclude any equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the invention as claimed. Thus, while the present invention has been specifically disclosed by preferred embodiments and optional features, it should be understood that modifications and variations of the concepts disclosed herein may be effected by those skilled in the art, and that such modifications and variations are considered to be within the scope of the invention as defined by the appended claims.

Claims

1. 1. A method of mapping a plurality of wireless emitters within a geographic region, the method comprising: obtaining a set of signal inputs corresponding to wireless emissions from the plurality of wireless emitters received at three or more antennas; processing the set of signal inputs to determine a plurality of periodic autocorrelation functions or spectral correlation functions for a plurality of signal input pairs of the set of signal inputs using a correlation receiver; analyzing one or more of the cyclic autocorrelation functions or the spectral correlation functions to identify a set of classes or types of the plurality of wireless emitters; determining a set of geolocation information for the plurality of wireless emitters using the cyclic autocorrelation function or the spectral correlation function; A method comprising:

2. The method of claim 1 , further comprising overlaying the set of geolocation information onto a geographical, network, or symbolic map or data.

3. The method of claim 1 , further comprising transmitting the set of geolocation information or a subset of the geolocation information to a remote server.

4. Processing the set of signal inputs comprises: processing a plurality of pairs of signal inputs from different pairs of the three or more antennas using the correlation receiver to determine a set of time delays associated with receiving the wireless radiation at the three or more antennas; determining a set of angles of arrival of the wireless radiation at the three or more antennas using the set of time delays; determining the set of geolocation information for the plurality of wireless emitters using the set of angles of arrival; The method of claim 1 , comprising:

5. The method of claim 1 , wherein one or more of the antennas are directly coupled to the correlation receiver or one or more of the antennas are located remotely from the correlation receiver.

6. 2. The method of claim 1, further comprising overlaying the set of geolocation information and the set of classes or types of the plurality of wireless emitters onto a geographical, network, or symbolic map or data.

7. The method of claim 1 , wherein determining the set of geolocation information for the plurality of wireless emitters occurs in real-time or substantially real-time.

8. obtaining a set of new signal inputs corresponding to wireless emissions from the plurality of wireless emitters received at the three or more antennas; processing the set of new signal inputs to determine new cyclic autocorrelation functions or new spectral correlation functions for a plurality of signal input pairs of the set of new signal inputs using the correlation receiver; determining a set of new geolocation information for the plurality of wireless emitters using the new cyclic autocorrelation function or the new spectral correlation function; Repeating one or more times; tracking the set of geolocation information and one or more new sets of geolocation information for the plurality of wireless emitters over time; The method of claim 1 further comprising:

9. The method of claim 1 , wherein determining the set of geolocation information for the plurality of wireless emitters comprises determining a set of velocities for the plurality of wireless emitters.

10. A system for mapping a plurality of radio emitters in a geographical area, configured to perform a method according to any one of claims 1 to 9.

11. 1. A method for determining location and speed measurement information of traffic participants by an autonomous vehicle, the method comprising: obtaining a set of signal inputs corresponding to wireless emissions associated with a plurality of traffic participants received at three or more antennas; processing the set of signal inputs to determine a plurality of periodic autocorrelation functions or spectral correlation functions for a plurality of signal input pairs of the set of signal inputs using a correlation receiver; determining a set of geolocation information and / or speed measurement information for the plurality of traffic participants using the cyclic autocorrelation function or the spectral correlation function; determining, by a data processor within the autonomous vehicle, navigation instructions for the autonomous vehicle using the set of geolocation information and / or speed measurement information; and analyzing one or more of the cyclic autocorrelation functions or the spectral correlation functions to identify a set of classes or types of emitters associated with the plurality of traffic participants.

12. The method of claim 11 , further comprising repeating the obtaining and processing one or more times and determining further or more accurate geolocation and speed measurement information for the plurality of traffic participants.

13. Processing the set of signal inputs comprises: processing a plurality of pairs of signal inputs from different pairs of the three or more antennas using the correlation receiver to determine a set of time delays associated with receiving the wireless radiation at the three or more antennas; determining a set of angles of arrival of the wireless radiation at the three or more antennas using the set of time delays; determining the set of geolocation information for the plurality of traffic participants using the set of angles of arrival; The method of claim 11 , comprising:

14. The method of claim 11 , wherein wireless emissions associated with a traffic participant include wireless emissions generated by a wireless emitter at said traffic participant.

15. The method of claim 11 , wherein a traffic participant of the plurality of traffic participants includes a vehicle or a pedestrian.

16. The method of claim 11 , wherein the radio radiation associated with a traffic participant comprises radio radiation reflected by said traffic participant.

17. generating a new wireless emission; and transmitting the new wireless emission toward the plurality of traffic participants; The method of claim 11 , wherein the radio emissions include reflections of the new radio emissions from at least one traffic participant.

18. The method of claim 11 , further comprising providing the set of geolocation information and the speed measurement information to another autonomous vehicle corresponding to a traffic participant of the plurality of traffic participants.

19. The method of claim 11 , wherein the correlation receiver is a component of the autonomous vehicle, the autonomous vehicle corresponding to a traffic participant of the plurality of traffic participants.

20. The correlation receiver is remote from the plurality of traffic participants, and the method further comprises:

12. The method of claim 11, comprising wirelessly transmitting the set of geolocation information and speed measurement information to the autonomous vehicle for use in determining or applying the navigation instructions for the autonomous vehicle.

21. A system for determining location and speed measurement information of traffic participants, configured to carry out a method according to any one of claims 11 to 20.

22. The method of claim 1, wherein the set of classes or types of the plurality of wireless emitters identifies a model, manufacturer, physical parameters, or service provider for at least one of the plurality of wireless emitters.

Images