KR20230165310A - Real-time wireless mapping using correlated passive receivers - Google Patents

Abstract

Systems and methods are described for mapping locations and characteristics of wireless emitters, optionally including traffic participants, to enable real-time tracking of geolocation or speedometry information. Systems and methods advantageously use correlated receivers to observe emissions from wireless emitters without deciphering or decoding information contained in the emissions from the wireless emitters so that location and emitter class and type can be tracked in real time. View real-time geolocation and emitter class information for many receivers in a geographic area, which can be overlaid on maps or used in autonomous vehicle navigation applications, eliminating the computational burden associated with tracking the locations of multiple multiple emitters using direct sensor measurements. Useful for reducing

Description

Real-time wireless mapping using correlated passive receivers

The present invention relates to real-time wireless mapping using correlated passive receivers. This application claims the benefit and priority of 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 for all purposes. The entire contents are incorporated herein by reference.

Techniques for wideband spectral correlation function and/or cyclic-autocorrelation function estimation have been developed. Spectral correlation functions and periodic-autocorrelation functions can provide a wealth of information, providing statistical insight into the received signal. There is a need in the art for improved methods and systems involving the use of spectral correlation and periodic-autocorrelation information.

Aspects described herein relate to the field of mapping and classification of wireless emitters, and decrypting or decoding information contained in emissions from wireless emitters. It relates to specific applications of systems and methods for mapping locations and characteristics associated with a wireless emitter by observing the emissions from the wireless emitter without using the device.

According to one aspect, a method for mapping wireless emitters in a geographic area is provided. In one example, the method of this aspect includes generating a pair of signal inputs by receiving wireless emissions from a plurality of wireless emitters at a first antenna pair; and processing the signal input pair to determine a set of geolocations of the plurality of wireless emitters using a correlation receiver. Optionally, the method further comprises receiving wireless emissions from a plurality of wireless emitters at an additional pair of antennas, thereby generating an additional pair of signal inputs; and processing the signal input pairs using a correlation receiver to determine an additional set of geolocations of the plurality of wireless emitters, repeating one or more times. For example, one or two antennas of a pair of antennas are the same or different than one or two antennas of an additional pair of antennas. Optionally, the set of additional geolocations correspond to more precise geolocations for the plurality of wireless emitters.

In some examples, processing a signal input pair using a correlated receiver may include determining a time difference of arrival (TDOA) for wireless emissions received at each antenna of the antenna pair. By way of example, processing a signal input pair using a correlated receiver may include determining the angle of arrival (AoA) for radio emissions received at each antenna of the antenna pair. In some examples, a method of mapping wireless emitters in a geographic area further includes overlaying a set of geolocations for a plurality of wireless emitters onto geographic or network map data. Optionally, receive radio emissions from a plurality of radio emitters at a pair of antennas to generate a signal input pair (e.g., one or two antennas of a pair of antennas are connected to one or two antennas of a further pair of antennas) The process of processing pairs of signal inputs to determine a set of geolocations of a plurality of wireless emitters using a (same or different from) and a correlation receiver, the This may be repeated one or more times over time to allow geolocation to be tracked.

In some examples, correlated receivers may use different antennas or the same antenna may be used to receive various wireless emissions. For example, groups of three or more antennas may be used in different pairwise combinations to provide different antenna pairs for receiving various radio emissions. In some cases, radio emissions may be received from three or more antennas, which are paired in different combinations to provide different signal pairs for processing by a correlation receiver, for example to provide more accurate geolocation information. can be achieved.

Correlated receivers can be useful for processing signal input to reduce or eliminate interference from noise, such as natural sources of radio frequency emissions.

In some examples, processing a signal input pair using a correlation receiver includes determining a cyclic autocorrelation function or spectral correlation function of the signal input pair. Optionally, processing the signal input pair using a correlation receiver includes removing noise using a periodic autocorrelation function or a spectral correlation function.

A correlation receiver may be useful in determining the class or type of a plurality of wireless emitters by analyzing signal input pairs. For example, emission signatures may be determined and compared to known emission signatures for other classes or types of wireless emitters, and this information may optionally be paired with geolocation information for a plurality of wireless emitters. there is.

In another example, a method of mapping a plurality of wireless emitters in a geographic area includes obtaining a set of signal inputs corresponding to wireless emissions from the plurality of wireless emitters received at three or more antennas. obtaining step; Processing the set of signal inputs using a correlation receiver to determine a plurality of periodic autocorrelation functions or spectral correlation functions for a plurality of pairs of signal inputs of the set of signal inputs; and determining a set of geolocations of the plurality of wireless emitters using a periodic autocorrelation function or a spectral correlation function. Optionally, one or more antennas are connected directly to the correlated receiver. Optionally, one or more antennas are located remote from the correlated receiver.

Optionally, determining the set of geolocations of the plurality of wireless emitters includes determining the set of velocities of the plurality of wireless emitters.

Advantageously, the methods described herein are performed in real time or substantially in real time, e.g., over a short period of time (e.g., 10 seconds or less, 5 seconds or less, or 1 second or less) of reception of the wireless emissions. , which allows determining a set of geolocations of multiple wireless emitters. Additionally, this aspect of the method can be used to simultaneously determine the geolocation of all detectable emitters in a specific geographic area.

Optionally, the method may further include overlaying the geographic, network or symbolic map or set of geographic locations on the geographic, network or symbolic map data.

Optionally, this aspect of the method may further include transmitting the set of geolocations, or a subset thereof, to a remote server. In this way the geolocation of the emitter can be determined and optionally tracked as a function of time.

A correlation receiver may process the signal input in a pair-wise fashion to determine a set of geolocations of a plurality of wireless emitters. For example, a first pair of signal inputs corresponding to received signals from two antennas may be processed, and a second pair of signal inputs corresponding to received signals from two antennas may be processed. inputs) may be processed, and a third pair of signal inputs corresponding to signals received from the two antennas may be processed. Using three antennas A1, A2, and A3, three pairs can be employed: A1 and A2, A2 and A3, and A1 and A3. In some examples, processing a set of signal inputs may involve using a correlation receiver to determine a set of time delays associated with receiving wireless emissions from three or more antennas. Processing the signal input of the pair;

determining a set of angles of arrival of radio emissions from three or more antennas using a set of time delays; and determining a set of geolocations of the plurality of wireless emitters using the set of angles of arrival. By determining at least three sets of angles of arrival, the location of each radio emitter can be pinpointed.

In some examples, additional information about each wireless emitter may be derived from a periodic autocorrelation function or a spectral correlation function, which may optionally be useful for fingerprinting and/or tracking the wireless emitter over time. You can. In some examples, the method 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 a plurality of wireless emitters. Optionally, a set of geolocations and a set of classes or types of a plurality of wireless emitters may be overlaid on a geographic, network or symbolic map or geographic, network or symbolic map data.

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 times obtaining a new set of 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 using a correlation receiver to determine a plurality of new periodic autocorrelation functions or spectral correlation functions for a plurality of pairs of signal inputs among the set of new signal inputs; and determining a new set of geolocations of the plurality of wireless emitters using a new periodic autocorrelation function or a new spectral correlation function. In this way, the methods described herein can track a set of geolocations of a plurality of wireless emitters and a set of one or more new geolocations over time.

In another aspect, a system for mapping a plurality of wireless emitters in a geographic area is described. Exemplary systems of this aspect include a correlation receiver; and three or more antennas positioned in data communication with the correlation receiver, and one or more processors also in data communication with the correlation receiver. To achieve the mapping, a correlation receiver may determine a plurality of periodic autocorrelation functions or spectral correlation functions for a plurality of pairs of signal inputs of a set of signal inputs. It may be configured to process a set of signal inputs corresponding to wireless emissions. Additionally, the one or more processors may be configured to determine a set of geolocations of the plurality of wireless emitters using a periodic autocorrelation function or a spectral correlation function. Optionally, determine a set of geographic locations.

The plurality of wireless emitters includes determining a speed set of the plurality of wireless emitters.

Optionally, one or more antennas are coupled directly to the correlated receiver. Optionally, one or more antennas are located remote from the correlated receiver. Optionally, determining the set of geolocations of the plurality of wireless emitters occurs in real time or substantially real time.

In some examples, a correlation receiver configured to perform an operation may include arranging elements of the correlation receiver in particular configurations such that various signals are generated and/or processed depending on the arrangement of the elements. In some examples, the correlation receiver and/or one or more processors configured to perform the operations may include programming these components with instructions, such as processor-executable instructions, which may be stored in one or more non-transitory processor-readable stores. It can be selectively stored on a medium and, when executed by a processor, causes the processor to perform an operation.

In some examples, the one or more processors are further configured to overlay a geographic, network, or symbolic map or set of geolocations on geographic, network, or symbolic map data. Optionally, the one or more processors are further configured to transmit the set or subset of geolocations to a remote server.

In some examples, processing a set of signal inputs may involve using a correlation receiver to determine a set of time delays associated with receiving wireless emissions from three or more antennas. Processing the signal input of the pair; determining a set of angles of arrival of radio emissions from three or more antennas using a 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 periodic 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 superimpose the set of geolocations and the set of classes or types of the plurality of wireless emitters onto the geographic, network or symbolic map or geographic, network or symbolic map data.

In some examples, a correlation receiver may be configured to obtain a new set of signal inputs corresponding to wireless emissions from a plurality of wireless emitters received at three or more antennas; and processing the set of new signal inputs using the correlation receiver to determine a plurality of new periodic autocorrelation functions or spectral correlation functions for the plurality of pairs of signal inputs. It is further configured to repeat more than once. In some examples, the one or more processors are configured to determine a new set of geolocations of the plurality of wireless emitters using a new periodic autocorrelation function or a new spectral correlation function; and repeat one or more times tracking the set of geolocations of the plurality of wireless emitters and one or more new sets of geolocations over time.

Many advantages are achieved by the present invention over the prior art. For example, aspects described include methods and systems for real-time processing of radio frequency (RF) input signals that can passively track the location and type of transmitter in real time without requiring the ability to decode the content of the RF input signal. provides. These and other embodiments of the invention, along with their many advantages and features, are described in more detail below and with reference to the accompanying drawings.

Aspects described herein also provide for determining the location and characteristics of traffic participants for use by autonomous vehicles by observing the active emissions or emission reflections of traffic participants. It relates to the field of mapping and classification of wireless emitters and reflections of emissions from wireless emitters, with specific applications of the disclosed systems and methods for mapping.

According to one aspect, a method for determining the geographic location of traffic participants is provided. The method includes generating a pair of signal inputs by receiving radio emissions associated with a plurality of traffic participants at a pair of antennas; and processing the signal input pairs using a correlation receiver to determine a set of geolocation and velocimetry information for a plurality of traffic participants. Optionally, the method includes generating additional signal input pairs by receiving additional wireless emissions associated with a plurality of traffic participants at a pair of antennas; and processing the additional signal input pairs using a correlation receiver to determine an additional set of geolocation or speedometry information for the plurality of traffic participants. Optionally, the method may include determining speed measurement information (e.g., speed vectors) for a plurality of traffic participants based on multiple sets of geographic locations for the plurality of traffic participants and time differences between them. . In some examples, the additional signal pair may be connected to the plurality of traffic signals, for example, by receiving the additional signal input pair using at least one different antenna or at least one antenna that has been moved from the antenna used to receive the previous signal input pair. It can be used to determine more accurate geolocation and speed measurement information for participants.

Geolocation and speed information may be provided and used by autonomous vehicles, such as providing information about the traffic environment to recognize and detect other traffic participants and their speeds and predicted routes. Exemplary traffic participants include, but are not limited to, vehicles (e.g., internal combustion engine vehicles, electric-powered vehicles, bicycles), pedestrians, etc.

In some examples, wireless emissions associated with a traffic participant include wireless emissions generated by the traffic participant's wireless emitter. For example, such wireless emitters may be components of a vehicle, such as collision transducers, parking emitters, wireless radio transmitters, etc. In some examples, such wireless emitter may be a wireless device carried by the driver or passenger of the vehicle. In some examples, such wireless emitters may be wireless devices carried by pedestrians.

However, in some instances, traffic participants may not carry or contain wireless devices that produce wireless emissions. In such cases, the wireless emissions associated with the traffic participants may include wireless emissions reflected by the traffic participants. For example, these radio emissions may be reflected by the vehicle body. Optionally, the method may further include generating new wireless emissions and directing the new wireless emissions to one or more traffic participants, so that the geolocation and/or speed to be determined for traffic participants that do not have wireless devices of their own. It produces reflected emissions that allow information to be received by the antenna.

Optionally, the correlated 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 a set of geolocations of the plurality of traffic participants and a set of speeds of the plurality of traffic participants to another autonomous vehicle that is a traffic participant, such as by wireless radio communication.

In some examples, a correlated 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, by wireless radio communication or the like, a set of geolocations of the plurality of traffic participants and a set of speeds of the plurality of traffic participants to the autonomous vehicle that is a traffic participant.

It will be appreciated that processing a signal input pair using a correlated receiver may include determining the time difference of arrival (TDOA) for radio emissions received at each antenna of the antenna pair. By way of example, processing a signal input pair using a correlated receiver may include determining the angle of arrival (AoA) for radio emissions received at each antenna of the antenna pair. Optionally, the process of generating a pair of signal inputs by receiving radio emissions from one antenna pair, and processing the pair of signal inputs using a correlation receiver to determine a set of geolocations of the traffic participants, includes: The location can be determined simultaneously. Optionally, the process of generating a pair of signal inputs by receiving radio emissions from one antenna pair and processing the pair of signal inputs using a correlation receiver to determine a set of geolocations of a plurality of traffic participants over time. This may be repeated more than once to track the geographic location and speed of multiple traffic participants.

In some examples, the correlated receiver may use different antennas or the same antenna may be used to receive wireless emissions from multiple traffic participants. In some examples, a correlated receiver may use different antennas or the same antenna may be used to receive wireless emissions from multiple traffic participants over time. For example, groups of three or more antennas may be used in different pairwise combinations to provide different antenna pairs for receiving various radio emissions. In some cases, a single radio emission may be received by three or more antennas, which combine in different ways to provide different signal packages that can be processed by a correlated receiver, for example to provide more accurate geolocation information. can form a pair.

Correlated receivers can be useful for processing signal input to reduce or eliminate interference from noise, such as natural sources of radio frequency emissions. In some examples, processing a signal input pair using a correlation receiver includes determining a cyclic autocorrelation function or spectral correlation function of the signal input pair. Optionally, processing the signal input pair using a correlation receiver includes removing noise using a periodic autocorrelation function or a spectral correlation function.

Correlation receivers can be useful in determining the class or type of a wireless emitter by analyzing the signal input pair. For example, emission signatures can be determined and compared to known emission characteristics for various classes or types of wireless emitters.

This information may optionally be paired with geolocation information for multiple traffic participants.

In one aspect, the present invention provides a method for determining traffic participant location and speed measurement information by an autonomous vehicle for use in determining commands 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 using a correlation receiver to determine a plurality of periodic autocorrelation functions or spectral correlation functions for a plurality of pairs of signal inputs of the set of signal inputs; determining a set of geolocation and/or speed measurement information for a plurality of traffic participants using a periodic autocorrelation function or a spectral correlation function; and using the set of geolocation and/or speed measurement information by a data processor of the autonomous vehicle to determine navigation commands for the autonomous vehicle. In some examples, the correlation receiver may be a component of an autonomous vehicle, where the autonomous vehicle corresponds to a traffic participant among a plurality of traffic participants, while in other examples the correlation receiver may employ a correlation receiver remotely from the autonomous vehicle. In an example, wireless emissions associated with a traffic participant may include wireless emissions generated by the traffic participant's wireless emitters, such as wireless emitters in vehicles or carried by pedestrians. Optionally, the wireless emissions associated with the traffic participants include wireless emissions reflected by the traffic participants.

As described in more detail herein, a correlation receiver can be used to process the signal input to obtain information about the emissions. In an example, processing a set of signal inputs may include receiving a plurality of signals from different pairs of three or more antennas using a correlation receiver to determine a set of time delays associated with receiving wireless emissions from the three or more antennas. Processing signal input pairs; determining a set of angles of arrival of radio emissions from three or more antennas using a 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 method of this aspect may further include analyzing one or more of a periodic autocorrelation function or a spectral correlation function to identify a set of classes or types of a plurality of wireless emitters.

In some cases, more accurate geolocation is useful or desirable for use in autonomous vehicles. In this case, additional signal input can be obtained. for example,

The method may further include repeating the obtaining and processing steps one or more times and determining additional or more accurate geolocation and speed measurement information for a plurality of traffic participants.

In some cases, traffic participants may not contain wireless emitters, but it may still be desirable and possible to track such traffic participants using the techniques described herein. For example, radio emissions may be reflected from traffic participants (e.g., outside a vehicle body or other component), and these reflected emissions may be used to generate signal input. In some examples, the method may further include generating new wireless emissions and directing the new wireless emissions to a plurality of traffic participants, wherein the wireless emissions include reflections of the new wireless emissions from at least one traffic participant. .

If the correlation receiver is remote from the autonomous vehicle, the method may further include wirelessly transmitting a set of geolocation and velocity information to the autonomous vehicle for use in determining or applying commands to the autonomous vehicle. You can. Some methods could be used to share geolocation and speedometry information with other autonomous vehicles, as not all vehicles will include correlation receivers, but still benefit from the information. In some examples, the method may include or further include providing a set of geolocation and speed measurement information to another autonomous vehicle corresponding to a traffic participant in the plurality of traffic participants.

In another aspect, a system is described herein, such as a system for determining traffic participant location and speed measurement information. An exemplary system of this aspect may include three or more antennas, a plurality of periodic autocorrelation functions or a spectral correlation function for a plurality of pairs of signal inputs among a set of signal inputs. It may include a correlation receiver positioned in data communication with three or more antennas, one or more processors, such as a correlation receiver configured to process a set of signal inputs corresponding to radio emissions associated with traffic participants. there is. The one or more processors determine a set of geolocation and/or speedometry information for a plurality of traffic participants using a periodic autocorrelation function or a spectral correlation function; and determine navigation instructions for the autonomous vehicle using the set of geolocation and/or geometric information. Optionally, the correlation receiver and one or more processors are components of the autonomous vehicle.

Optionally, the correlation receiver and the one or more processors may be remote from the autonomous vehicle and the one or more processors may be further configured to transmit a set of geolocation and/or velocity information to the autonomous vehicle.

In some examples, a correlation receiver configured to perform an operation may include placing elements of the correlation receiver in a particular configuration such that various signals are generated and/or processed depending on the placement of the elements. In some examples, the correlation receiver and/or one or more processors configured to perform the operations may include programming these components with instructions, such as processor-executable instructions, which may be stored in one or more non-transitory processor-readable stores. It can be selectively stored on a medium and, when executed by a processor, causes the processor to perform an operation.

The correlation receiver optionally iterates one or more times to obtain a new set of signal inputs corresponding to radio emissions associated with a plurality of traffic participants received from three or more antennas; and using a correlation receiver to process the set of new signal inputs to determine a plurality of new periodic autocorrelation functions or spectral correlation functions for the plurality of pairs of signal inputs. It is further configured to repeat more than once. One or more processors may optionally be further configured to determine additional or more accurate geolocation and speed measurement information for a plurality of traffic participants.

In some examples, processing a set of signal inputs may involve using a correlation receiver to determine a set of time delays associated with receiving wireless emissions from three or more antennas. Processing the signal input of the pair; determining a set of angles of arrival of radio emissions from three or more antennas using a 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 periodic autocorrelation function or the spectral correlation function to identify a set of classes or types of the plurality of wireless emitters.

Optionally, the wireless emissions associated with the traffic participant include wireless emissions generated by the traffic participant's wireless emitters. Optionally, the traffic participant in the plurality of traffic participants includes a vehicle or a pedestrian. Optionally, the wireless emissions associated with the traffic participants include wireless emissions reflected by the traffic participants.

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

Many advantages are achieved over the prior art through this embodiment and the embodiments described herein. For example, the described aspect is a wireless device that can passively track the location and type of transmitter in real time for use in autonomous driving applications, without requiring the ability to decode the content of the RF input signal. Provides a method and system for real-time processing of frequency (RF) input signals.

These and other embodiments of the examples, along with their many advantages and features, are described in greater detail with reference to the text below and the accompanying drawings.

Aspects of the disclosure will now be more fully described below with reference to the accompanying drawings, which are to be read in conjunction with this summary, the detailed description, and any exemplary, preferred and/or specific embodiments specifically discussed or disclosed. It is intended. However, the present invention may be implemented in many different forms and is not limited to the embodiments described herein; Rather, these embodiments are provided by way of example only, so that this disclosure will be thorough and complete, and will fully convey its entire scope to those skilled in the art.
Figure 1 is a schematic diagram showing the angle of arrival of radio emissions and the reception of radio emissions from two different antennas.
2 provides a schematic diagram of an example correlated receiver system in accordance with some examples of the present disclosure.
Figure 3 provides a three-dimensional plot illustrating an example periodic autocorrelation function.
Figure 4 provides a two-dimensional plot illustrating an example periodic autocorrelation function.
Figure 5 provides a two-dimensional plot illustrating another example periodic autocorrelation function for a time-delayed signal.
6 provides a schematic diagram of an example correlated receiver system according to some examples of the present disclosure.
7 schematically depicts the distribution of multiple antenna systems and/or correlated receiver systems over a geographic area.
Figure 8 provides an example plot showing the geographic location of detected wireless emitters.
Figure 9 provides an example plot showing the geolocation of detected wireless emitters overlaid with emitter characteristics.
FIG. 10 provides a simplified flow diagram detailing a method for mapping a plurality of wireless emitters in a geographic area in accordance with some examples of the present disclosure.
Figure 11 provides a schematic diagram of the use of a plurality of traffic participants and a correlation receiver system used to determine the geolocation of the traffic participants.
12 provides a simplified flow diagram detailing a method for determining traffic participant location and/or speed measurements in accordance with some examples of the present disclosure.
FIG. 13 provides a simplified flow diagram detailing a method for determining traffic participant location and/or speed measurements in accordance with some examples of the present disclosure.

Electromagnetic (e.g. radio frequency) emissions generated by a wireless emitter (e.g. a cell phone or other radio frequency device) are typically broadcast by the radio emitter and received by an appropriate base station (e.g. a cell tower). Wireless service providers, like cellular service providers, have the ability to receive, decipher, and decode transmissions from wireless emitters operating on their network. This allows wireless providers to obtain rich information about the signals broadcast by wireless emitters, including access to the data content of the transmissions. In some cases, a wireless emitter may be able to locate itself, for example, by receiving transmissions from a Global Positioning Satellite (GPS), and this information may 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 use multiple base stations to obtain triangulation location information for emitters.

Without access to the signal content of the transmission 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. Emitter geolocation typically requires the cooperation of network operators or emitters, without which it is impossible to map all emitters of interest (unless joint access to multiple networks and emitters is feasible). .

However, because wireless emitters broadcast their transmissions as physical electromagnetic emissions, they are generally detectable by any system equipped with an appropriate antenna located within an appropriate detection range, provided the receiver has the ability to distinguish noise and interference from the emitter signal. It can be. This can be achieved without deciphering or decoding the information content, whereby location information for a wireless emitter can be determined based on the received power of the emission, the frequency of the emission. This can be accomplished without deciphering or decoding the information content, whereby location information for a wireless emitter can be determined based on the received power and emitting frequency. In such systems, if emissions can be detected using multiple antennas separated by a known distance, additional details, such as more accurate location information (e.g. using triangulation or similar techniques), can be obtained.

Modem wireless transmissions typically include digital modulated signals, where digital data may be expressed as phase-shift keying (PSK), frequency-shift keying ( Using one or more modulation techniques, such as using keying techniques such as FSK, amplitude-shift keying (ASK), Quadrature Amplitude Modulation (QAM), or other modulation techniques. It is encoded. These modulated signals may contain repetitive characteristics in nature, and the underlying data they contain may be encoded or encrypted using a variety of techniques.

Moreover, different types of wireless emitters will emit with different physical characteristics such as frequency, bandwidth, modulation type or rate, bit rate, etc., which may vary depending on the wireless service in use or 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 physical electromagnetic emissions without having to decode or decipher the content.

Using many or millions of wireless emitters distributed throughout a city or other geographic area, a network of antennas can be built to allow tracking the location of the wireless emitters, but such networks are comparable to traditional base station networks (e.g. cellular networks). Installation of antennas may require access to infrastructure, equipment and physical locations, which may be subject to various regulations, franchise requirements, ownership or lease requirements, etc., which adds to the complexity and impracticality of such networks. limit.

According to embodiments described herein, a class of receivers is provided that overcomes these problems, allowing tracking of many wireless emitters in a geographic area or traffic environment using a small set of antennas. For example, a correlated receiver may be used. Unlike conventional receivers that contain only a single antenna, correlated receivers have two inputs to accommodate at least two antennas. This can allow the correlated receiver to determine the time difference for the radiated signals received at the two antenna inputs and the frequency of arrival difference for the radiated signals received at the two antenna inputs, which can allow for accurate positioning of the wireless emitter. there is. . It will be appreciated that these aspects may be used interchangeably in some cases, as time-of-arrival differences may be used and angles of attack of radiated signals incident on the two antenna inputs may be derived from each other. Additionally, the emission signals received from the two antenna inputs may be combined with signals generated from background emissions (e.g., generated by wireless emitters) to provide a modulation signature of the received signal, such as to provide emission characteristics of the received signal or to aid in emitter classification. can be correlated to remove noise (e.g. natural noise) to identify and extract signals (such as artificial or man-made signals).

It is possible to use correlated receivers to determine the location and classification of wireless emitters at distances well outside the typical operational range required for wireless communications. This effectively reduces the required signal-to-noise ratio, since the data from the electromagnetic emissions does not need to be recovered by the correlated receiver, allowing the correlated receiver to be located much further away than would be necessary for a typical receiver, which is typically the case for wireless It establishes a two-way link with the emitter and, as a result, is often located reasonably close to the wireless emitter. In this way, a single or small set of correlated receivers can be located in a geographic region or at the edge of a geographic region and still be useful for tracking the location and characteristics of emitters throughout the geographic region.

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

In one aspect, a real-time correlation receiver, such as a geolocation device, is described. In some examples, a real-time correlation receiver is

Signal inputs derived from two spatially separated antennas capable of receiving radio-frequency signals in a spectral range greater than 10 MHz; A real-time correlator that operates on two signal inputs in the time or frequency domain; and a processor that measures or determines one or more of the difference in time of arrival between the two signal inputs, the angle of attack of electromagnetic radiation incident on the two antenna inputs, and/or the difference in frequency of arrival between the two signal inputs. .

In another aspect, real-time correlation receivers, such as the geolocation of traffic participants, which may be useful for example in autonomous driving applications, are described. In some examples, a real-time correlated receiver may include signal inputs derived from two spatially separated antennas capable of receiving radio frequency signals in a spectral range greater than 10 MHz; A real-time correlator that operates on two signal inputs in the time or frequency domain; and a processor that measures or determines one or more of the difference in time of arrival between the two signal inputs, the angle of attack of electromagnetic radiation incident on the two antenna inputs, and/or the difference in frequency of arrival between the two signal inputs. .

Advantageously, the real-time correlation receiver described herein can reject or isolate man-made emissions by removing naturally occurring emission noise or interference. Optionally, the real-time correlation receiver can separate moving and stationary emissions for the purpose of identifying user classes or emitter classes.

In some examples, the correlation begins or is performed by digitizing the input signal and calculating the Fourier transform to calculate the spectral correlation. In some examples, correlation is realized or performed by varying the delay between two signal inputs, multiplying them, and performing a time integration of the product.

Optionally, the delay function is implemented or performed using a variable length physical waveguide. Optionally, a delay function may be implemented or performed using a combination of a tunable oscillator and a distributed waveguide. Optionally, the multiplication function is realized or performed by optical or radio frequency mixer elements. Optionally, the multiplication function is realized or performed by a coherent optical detector.

Various outputs of the real-time correlation receiver may be used. In some examples, the output is a spectral correlation function (SCF) or cyclical autocorrelation function (CAF). Optionally, a real-time correlation receiver can generate SCF and CAF outputs to determine the geolocation and velocity measurements of the emitter. Optionally, the real-time correlation receiver may generate SCF and CAF outputs for the purpose of identifying the type of service the emitter is using. Optionally, the real-time correlation receiver can generate SCF and CAF outputs for the purpose of identifying the physical parameters of the emitter. Without limitation, exemplary physical parameters include the emission frequency and operating band, the modulation period, the type of coding used to modulate the emissions, the spectral and temporal response of the transmitter generating the emissions, the type of hardware comprising the particular emitter, or the directivity of the emissions. It may include one or more of the following.

Real-time correlation receivers can operate over a variety of radio frequencies. In some examples the operating range is 10kFIz to 4GHz. In some examples the operating range is 10kHz to 30GHz. In some examples the operating range is 10kHz to 110GHz. 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, a real-time correlation receiver may have or provide geolocation accuracy of better than 2 feet for emissions ranging from 10 feet to 100 feet away. Optionally, a real-time correlation receiver may have or provide geolocation accuracy of better than 2 feet for emissions ranging from 100 feet to 1000 feet away.

In some examples, a real-time correlation receiver may share output with other spatially distinct real-time correlation receivers, such as remote vehicles or traffic participants. Optionally, two signal inputs are realized by accessing different pairs of spatially separated antennas. In some cases, the real-time correlation receiver includes or is equipped with two or more antennas. Optionally, the real-time correlation receiver may include or access multiple antennas in a pairwise manner using two inputs.

Geolocation data acquired by real-time correlation receivers can be used in a variety of applications. For example, emission geolocation data generated by a real-time correlation receiver can be shifted across a geographic map. For example, emission geolocation data generated by a real-time correlation receiver can be shifted across a network map. In one example, emitted geolocation data generated by a real-time correlation receiver may be used to facilitate exchange of services or placed on a symbolic map, such as a symbolic map, used to facilitate communications security. Optionally, emitted geolocation data generated by a real-time correlation receiver may be used to provide location-specific services and information.

Geolocation data acquired by real-time correlation receivers can be used in a variety of applications. For example, the geolocation may correspond to the geolocation of the emission associated with a vehicle carrying at least one wireless emitter (e.g., a wireless communication device).

In some examples, emissions and/or geolocation may be associated with internal combustion engine vehicles or electric engine vehicles.

Optionally, the emissions and/or geolocation may be associated with traffic participants lacking engine propulsion, such as pedestrians or bicycles. Optionally, the emissions may be reflected emissions, such as those reflected from traffic participants such as vehicles or pedestrians. Optionally, emissions may originate from the vehicle's ranging or collision avoidance transmitters and/or these emissions from the vehicle's ranging or collision avoidance transmitters may be reflected by other traffic participants.

Optionally, a real-time correlation receiver can calculate velocimetry information for the emitter, such as monitoring or tracking geolocation as a function of time. Velocity information can be selectively determined for multiple or all identified or detected emissions.

Correlation receivers can be used to allow the location information of a wireless emitter to be determined and to allow determination of emitter characteristics, all based on simply detecting the presence of the wireless emission without decoding or deciphering the data of the wireless emission. Because the presence of radio emissions can be detected over a much wider range than needed to decode or decode data, the signal-to-noise ratio can be much smaller than that required for wireless communications, so the effective range of a correlated receiver is greater than that required for wireless communications. It could be much bigger. Additionally, because correlated receivers can operate using pairwise combinations of multiple antenna input signals, correlated receivers can also improve noise rejection, such as background or natural radio frequency noise.

A variety of different correlated receivers may be used, such as cyclostationary receivers. However, such receivers used for real-time detection of radio frequency emissions, if conventional (all electronic implementations) are used, may be limited to the GHz scale frequency range or less. Combining analog and digital processing, hybrid correlated receivers are useful for extending useful frequency ranges to tens of GHz, while operating in real time to extend nominal propagation ranges to shorter frequencies. Additional details on spectral correlation and analysis are published in US Patent Application Serial No. 16/236,038, filed December 28, 2018, and US 2019/0339548, filed November 7, 2019, now US Patent Publication No. 11,137,627. , which is incorporated herein by reference.

Correlative Receiver System

A time-modulated signal x(t) can be analyzed using spectral correlation, such as to determine properties about the signal itself, without evaluating its data content. Spectral correlation has been used for signal detection in communication systems, etc. The spectral correlation function of a cyclostationary process describes the cross-spectral density or coherence of every pair of frequency-shifted versions of a time series. Computing the spectral correlation removes the stochastic part (i.e. noise) of the cyclic stationary process and reveals the deterministic part with cyclic features.

Periodic and higher-order (cumulative) analyzes are based on the fact that signal and noise have different correlation (i.e. moment) properties. A signal x(t) containing modulation, such as radio emission, has an intrinsic periodic autocorrelation defined as the Fourier transform and delayed copy of the signal, as shown in equation (1) has

(One)

Those skilled in the art will recognize equation (1) as the Wigner function, which roughly describes how spectral density changes over time. spectral correlation function is the periodic autocorrelation as shown in equation (2) is the Fourier response of .

(2)

Periodic autocorrelation function of modulated signal and/or spectral correlation function The technology for determining is U.S. Patent Application No. 16/236,038, filed on December 28, 2018, and U.S. Patent Publication No. 2019/0339548, published on November 7, 2019, and is currently described in U.S. Patent Registration No. 11,137,627. periodic autocorrelation function or spectral correlation function It will be understood that once one of the is available or determined, the other can be obtained directly as they are related to each other by Fourier as explained above.

Obtaining the periodic autocorrelation function and/or spectral correlation function of the wireless emission allows determining characteristic information about the emission, such as carrier frequency, bandwidth, bit rate, and modulation type. For use in determining geolocation information for an emitter, multiple spatially separated antennas can be used in a variation of cyclic autocorrelation, here referred to as cyclic cross correlation. If two antennas are separated by a distance from each other, both will receive the same radio emissions, but there will be a time delay t _D between the received signals, which may be a function of the distance between the antennas. Instead of determining the correlation (autocorrelation) of the received signal x(t) with itself, two different antennas ( ), the received signals can be correlated with each other.

(3)

The value of τ for periodic cross-correlation is shifted by the time delay t _D between receiving signals from different antennas. The maximum finding algorithm can quickly estimate the angle of arrival (AoA) of the signal based on the line between the antennas. Figure 1 shows an overview of the geometry of the two antennas for the emitter, showing the distance d between the antennas and the angle of arrival Q, where the cosine function defines the relationship between θ, d and t _D :

(4)

Figure 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 transformations in the optical domain without performing the iterative calculations normally required to obtain a solution. You can. Referring to FIG. 2, the correlation system 200 includes a master laser 205, a first optical modulator 215, a dispersive element 225, and a second optical modulator ( It may include a second optical modulator (230) and an optical comb filter (240). The master laser 205 may be, for example, but is not limited to a low-linewidth semiconductor laser or another laser. The master laser 205 may generate a self-referenced optical frequency comb signal 210 consisting of signals of different optical wavelengths (i.e., colors or tones). The tone of the optical frequency comb signal 210 is transmitted to the first optical modulator by the first input signal x ₁ (t) corresponding to the RF (Radio Frequency) signal received from the first antenna 220. It can be modulated in (modulator) 215. The first optical modulator 215 may generate N spectral copies of the first input signal x ₁ (t) for the tones of the optical frequency comb signal 210.

N spectral copies of the first input signal x ₁ (t) may be sent to the dispersion element 225. Dispersing element 225 may be, but is not limited to, a fiber optic dispersing element, such as a single mode fiber or other dispersing element. Dispersive element 225 may produce a wavelength-dependent time delay, τ _k , between adjacent spectral copies of the first input signal x ₁ (t). Time delay corresponds to phase shifts in the frequency domain. Delayed spectral copy of the first input signal x ₁ (t) (i.e. ) may be transmitted to the second optical modulator 230.

The second optical modulator 230 converts a delayed spectral copy of the first input signal x ₁ (t) into a second input signal x ₂ (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 x 1 (} t). The second optical modulator 230 provides a conjugate modulated spectral copy of the delayed spectral copy (i.e. ) can be created. terms from equation (3) integrated to obtain the periodic autocorrelation or cross-correlation coefficient due to the conjugate modulation of the delayed spectral copy of the input signal x ₁ (t) The practical creation of occurs.

The conjugate modulated spectral copy may be sent to optical comb filter 240. Optical comb filter 240 may be, for example, but is not limited to a fine resolution etalon or other optical comb filter. The optical comb filter 240 integrates the conjugate modulated spectral copies to produce integrated conjugate modulated spectral copies corresponding to cyclic autocorrelation coefficients for all time delays τ _k . can be performed. For example, the Nth integral conjugate modulation spectrum copy has the periodic autocorrelation coefficient corresponding to a delay τ _N at each periodic frequency α _i can have a complete set of , where i = 1,2,..., N. As a result, the full complement of N integrated spectral copies forms a complete periodic autocorrelation table, eliminating the need for full-velocity FFT calculations in the photon or electronic domains.

The correlation system 200 shown in FIG. 2 further includes components for reading periodic autocorrelation coefficients. For example, correlation system 200 may include a radio frequency (RF) oscillator 245, a third optical modulator 250, such as a single sideband (SSB) modulator. or other modulators, an optical wavelength demultiplexer (260), a 90° hybrid optical module (265), and a plurality of detectors D ₁ -D _N (270). The plurality of detectors D ₁ -D _N 270 may be coherent receivers. RF oscillator 245 may generate a sweep frequency. The signal generated by the master laser 205 and the sweep frequency generated by the RF oscillator 245 may be input to the third optical modulator 250.

The third optical modulator 250 may shift the signal generated by the master laser 205 in frequency, for example by several gigahertz or some other amount, and this frequency shifted signal may be transmitted to the second optical frequency comb 255. Can be used to create . The second optical frequency comb 255 may have the same frequency pitch as the original frequency comb 210 used to spectrally replicate the input signal x ₁ (t); However, the comb teeth of the second optical frequency comb 255 can sweep by several gigahertz according to the sweep RF oscillation 245. The generated frequency comb may be referred to herein as a swept optical sampling signal. The swept optical sampling signals may sweep at a rate lower than the frequency of the master laser signal, for example a frequency of about 25 kHz or another frequency.

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 acts as a coherent receiver and transmits four signals: modulated signal + local oscillator signal, modulated signal - local oscillator signal, modulated signal + conjugate of local oscillator signal, modulated signal - is the conjugate of the local oscillator signal. The output signal of the hybrid optical module 265 may be input to the optical wavelength demultiplexer 260.

The optical wavelength demultiplexer 260 may include a plurality of demultiplexer modules. In some implementations, four demultiplexer modules may be used. Each demultiplexer module may be configured to demultiplex one output of hybrid optical module 265. The demultiplexed signal may be detected by a plurality of detectors 270. The plurality of detectors D ₁ -D _N 270 may be coherent detectors. In some embodiments, each coherent detector may include two balanced detectors, each balanced detector having two PIN diodes (i.e., a total of four PIN diodes for each coherent detector). ) has. Each of the plurality of detectors D ₁ -D _N 270 receives a signal from each of the plurality of demultiplexer modules. For example, for an implementation using four demultiplexer modules, each detector D _I -D _N receives a signal from each demultiplexer module, that is, each detector D _I -D _N receives four signals.

Each detector D _I -D _N can consistently detect the periodic autocorrelation (cross-correlation) coefficient for every time delay τ _k of the associated tone from the integrated conjugate modulation spectrum copy. Detector D _I -D _N is Coefficients such as coefficients can be streamed simultaneously, Is It is streamed simultaneously after counting, etc. The detector D _I -D _N can output the detected periodic autocorrelation coefficient as a function of time. Accordingly, correlation system 200 may provide for efficiently determining periodic autocorrelation or cross-correlation coefficients. The detected coefficients can be digitized using, for example, an analog-to-digital (A/D) converter and a spectral correlation function is calculated.

Correlation system 200 may include other components than those shown in FIG. 2, such as processors, input or output devices, control devices, memory devices, storage devices, etc. It will be appreciated that correlation system 200 provides only one example of a correlation receiver and that other implementations may be used instead. For example, certain aspects of correlation system 200 may be implemented using digital system components. For example, not only can all-electronic implementations of correlated receivers be used, but hybrid correlated receivers that combine analog and digital signal processing cores can also be used. In some examples, when analog signals from an antenna are measured as a function of time, such analog signals may be quantized using one or more analog-to-digital converters. To obtain the frequency spectrum of the received signal at the antenna, a fast Fourier transform (FFT) can be performed on the digital data.

Figures 3, 4, and 5 show periodic autocorrelation function plots for a 1 GHz symbol rate BPSK signal using a root raised cosine filter for antennas spaced 1 m apart, showing both symbol-based and carrier frequency-based features. In Figure 3, the plot shows the data as a three-dimensional plot, and Figure 4 shows the same data as a two-dimensional plot. In Figure 5, the symbol-based features are centered around τ = 0 ns, which indicates that the delay time to between the received signals at the two antennas is approximately 0 ns. In Figure 5, the symbol-based features are shifted to the right and centered at τ = 0.5 ns, which indicates that the delay time τ _D between the received signals at the two antennas is approximately 0.5 ns. Based on this information and using equation (4) above, the angle of arrival of the signal shown in Figure 4 is 90°, and the angle of arrival of the signal shown in Figure 5 is 81°.

In some examples, determining the periodic autocorrelation or spectral correlation function may be accomplished using an antenna that is remote from the correlation system, in contrast to the configuration of correlation system 200 shown in FIG. 2. For example, Figure 6 shows a correlation system 600 similar to correlation system 200 that includes other components to enable the use of remote antennas. For example, instead of the antenna being coupled directly to the first optical modulator and the second optical modulator, the correlation system 600 may have a first input coupled to the first optical modulator 615. It includes a first input subsystem 620 and a second input subsystem 635 coupled to a second optical modulator 630. Although illustrated as a subsystem in FIG. 6, input subsystems 620 and 635 may be the same component. Correlation system 600 may include other components than those illustrated, such as processors, input or output devices, control devices, memory devices, storage devices, etc.

Input subsystems 620 and 635 may provide a remote modulated signal x _r (t) instead of the modulated signal provided by antennas 220 and 230 of correlation system 200. Here, the remote modulated signal x _r (t) may correspond to an antenna signal received in the correlation system 600 from a remote antenna system. For example, Figure 6 shows three remote antenna systems 650, 651, and 652, each containing its own antennas 655, 656, and 657. Remote antenna systems 650, 651, and 652 may include components for acquiring, digitizing, and transmitting signals received from the corresponding antennas as digital data for correlation system 600, wherein first and second Input subsystems 620 and 635 may use digital data to generate a modulation signal x _r (t) and provide it to first and second optical modulators 615 and 630, respectively. For example, remote antenna systems 650, 651, 652 may be configured to receive, digitize, and/or process radiated signals received at those antennas and communicate the received signals as digital data to correlation system 600 (e.g. may include amplifiers, analog-to-digital converters, and other components (via wireless or wired digital communications). In some examples, a remote antenna system may be configured to, for example, determine the Fourier transform of the emission signal, determine the conjugate of the emission signal or the Fourier transform, and/or compress or encode the digital data. It may include a processor or other component for converting. Although three remote antenna systems 650, 651, and 652 are shown in Figure 6, any number of additional antenna systems may be used. Additionally, although one or more antennas may be integrated directly into correlation system 600, the use of multiple remote antennas may provide various advantages.

For example, by using a remote antenna system, correlation system 600 can obtain periodic autocorrelation or spectral correlation functions pairwise between any or all antenna pairs as desired. For example, as shown in FIG. 6, input subsystem 620 can use an antenna signal from remote antenna system 650, and input subsystem 635 can use an antenna signal from remote antenna system 651. Signals can be used. Additionally or alternatively, input subsystem 620 may use an antenna signal from a remote antenna system 651 and input subsystem 635 may use an antenna signal from a remote antenna system 652. can be used. 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. Converse pairs of antenna assignment may also be used. In this way, each of the three pairs of antennas can be used to determine the angle of arrival of the received emission, and using the angle of arrival the exact location of the emitter can be determined.

Tracking Emitters Locations

FIG. 7 provides a schematic diagram of a plurality of antenna systems 700 positioned around a geographic area containing emitters 785 that produce radio frequency emissions 790 . The geographic area can be a city, town, or any desired subset thereof. In some examples, a geographic area may be a cell or portion of a cellular network, such as a macrocell area, microcell area, etc.

In this example, antenna system 700 may include a remote antenna system or a correlation system such that antennas 751, 752, 753, and 754 have a periodic autocorrelation function and/or a spectral correlation function for emission 790 and Any pairwise combination can be used to determine the angle of arrival for the emitter 785 by determining the time delay. Using the angle of arrival, the geographic location for emitter 785 (e.g., relative geographic coordinates from the antenna) can be determined. If the absolute geographic coordinates of one or more antennas are known, the geolocation may be the absolute geographic coordinates for the emitter (e.g. x and y or latitude and longitude, etc.).

When multiple emitters 785 are present in a geographic area, the geolocation for each emitter can be similarly obtained using the same pair of antennas in the same manner, provided that 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 also cover very wide bands of the radio frequency spectrum, providing geolocation for large numbers and diverse emitters. You can decide.

Advantageously, obtaining periodic autocorrelation functions and/or spectral correlation functions using pair-wise antennas described herein can be used to simultaneously obtain geolocation for all emitters 785. there is.

It will be appreciated that antenna system 700 can be located at a very large distance from 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 emitter 785 according to the techniques described herein is greater than the signal-to-noise ratio required to receive and decode data transmissions made by emitter 785. It can be quite small. It is possible to use correlated receivers to determine the location and classification of wireless emitters at distances well outside the normal operating range required for wireless communications. This effectively reduces the required signal-to-noise ratio, since the data from the electromagnetic emissions does not need to be recovered by the correlated receiver, allowing the correlated receiver to be located much further away than would be necessary for a typical receiver, which is typically the case for wireless It establishes a two-way link with the emitter and, as a result, is often located reasonably close to the wireless emitter. In this way, a single or small set of correlated receivers can be located in a geographic region or at the edge of a geographic region and still be useful for tracking the location and characteristics of emitters throughout the geographic region. Additionally, correlated receivers useful in the systems and methods described herein can provide high discrimination against noise. For example, periodic autocorrelation functions and/or spectral correlation functions can confine noise to a specific location because the signals are self-correlated. In the spectral correlation function, the noise is limited to a specific correlation frequency or periodic frequency (α = 0), while the modulated signal can rise above the detection layer elsewhere and provide a modulation signature. In periodic autocorrelation functions, the noise is limited to a specific correlation frequency or the origin of the periodic frequency (α) and time delay (τ) maps.

Using 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. 8 is an example showing the x and y coordinates of various different emitters 885 over an 8 km x 10 km geographic area as determined by the correlation system described herein, using at least three antenna pairs, as described above. Provides a coordinate system.

Additional information for each emitter may be determined by further examining the obtained periodic autocorrelation function and/or spectral correlation function to determine the geographic location of emitter 885. Various types of radio emitters are characterized by, for example, the location and number of features of the periodic autocorrelation function and/or the spectral correlation function, the emission frequency and operating band, the modulation period, the type of coding used to modulate the emission, and the method of generating the emission. They can provide a physical signature that reveals details about the emitter, such as the emitter's various physical characteristics, such as its spectral and temporal response, the wireless service it is using, the type of hardware that makes up a particular emitter, or the configuration of its wireless service provider. It may vary depending on. For example, using known wireless emitter capabilities, specific information about individual wireless emitters can be determined by detecting physical electromagnetic emissions without having to decode or decipher the content. This can be achieved by analyzing the amplitude or phase of the feature in a periodic autocorrelation function and/or a spectral correlation function and/or using a pattern matching function for known signatures. Details of techniques for analyzing signals using correlated receivers are described in U.S. Patent Application 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 physical signature information to the type, class, manufacturer and/or model of the emitter.

In some examples, a type or class of emitter may be paired or overlaid with a map or other coordinate system to show emitter locations and the distribution of that type or class. Figure 9 provides an example coordinate system showing the x and y coordinates of a variety of different emitters 985 over an 8 km x 10 km geographic area and including identifiers of the type or class. This information may be provided as icon information for the emitter or in a configuration that can be expanded to provide extended details about a specific emitter, such as when a map or coordinate system is displayed in a graphical user interface.

FIG. 10 is a simplified flow diagram illustrating a method 1000 of mapping a plurality of wireless emitters in a geographic area in accordance with an embodiment of the present invention. At block 1005 a signal input pair is created by receiving wireless emissions from a plurality of wireless emitters at a pair of antennas. The distance between a pair of antennas can be known, and wireless signals can be received at different times from each antenna. For example, each antenna can generate a time-dependent modulated voltage signal that can be provided as an input signal to a correlated receiver.

At block 1010, the signal input pairs are processed by a correlation receiver to determine a set of geolocations for a plurality of wireless emitters. Time-dependent voltage signals can be quantized, such as using an analog-to-digital converter as the first step in the process. Optionally, the signal can be converted to frequency space by performing a Fourier transform of the time-dependent signal. The signals can then be spectrally correlated using an autocorrelation function, which allows extracting features such as time difference of arrival (TDOA) or angle of arrival (AoA), which in turn determine the geolocation of the radio emitter. It can be used to

At block 1015, emission signatures may be selectively determined for a signal input pair to determine a class or type set of a plurality of wireless emitters. For example, an emission signature can identify the physical parameters of a wireless emitter (e.g., frequency performance, bitrate performance, etc.) and the class of service (e.g., service provider) that the wireless emitter uses. This information may be combined with geolocation.

At block 1020, geolocation information may be evaluated to determine whether geolocation for a plurality of wireless emitters has been obtained with sufficient precision. Otherwise, process 1000 may branch from decision point 1025 to block 1030, where additional signal inputs may be connected to one or more different antennas or channels displaced from those used in block 1005. It may be generated by receiving additional wireless emissions from a plurality of wireless emitters, such as using more than one antenna. The process may return to block 1010, where the process may be repeated for additional signal inputs to determine updated geolocation for the plurality of wireless emitters.

Once it is determined at block 1020 that the geolocation has been obtained with sufficient precision, process 1000 may branch at decision point 1025 to block 1035, wherein the geolocation is optionally classified into a class or class on a map, such as a geographic map. Can be nested with type information. The process of receiving wireless emissions to generate a signal and determining geolocation may be repeated as a function of time to enable tracking the geolocation of a plurality of wireless emitters over time. Advantageously, continuous tracking of geolocation coupled with a corresponding class or type of wireless emitter can ensure that individual wireless emitters are accurately tracked. Geolocation information, type or class information, mapping information, etc. may be provided as a data stream to one or more recipients.

It should be understood that the specific steps illustrated in FIG. 10 provide specific methods for mapping wireless emitters in a geographic area in accordance with embodiments of the present invention. Other sequences of steps may also be performed according to alternative embodiments. For example, alternative embodiments of the invention may perform the steps described above in a different order. Additionally, the individual steps shown in FIG. 10 may include multiple substeps that can be performed in various orders as appropriate for the individual steps. Additionally, additional steps may be added or removed depending on the specific application. Those skilled in the art will recognize various variations, modifications and alternatives.

Tracking Locations of Traffic Participants

Figure 11 provides a schematic diagram of a plurality of traffic participants.

Illustrative traffic participants include pedestrians and vehicles 1150 and 1155 carrying wireless emitters 1185 (e.g., cell phones) that generate radio frequency emissions 1190.

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, vehicle 1150 or 1155 may be provided with additional or fewer antennas than shown. For example, vehicle 1150 may use various antennas 1151 to determine the angle of arrival for emitter 1185 by determining the time delay and/or periodic autocorrelation function for emission 1190. A pairwise combination of 1152, 1156) can be used. In some examples, the antennas of fixed antenna system 1153 may be used for pairwise coupling and determination of the angle of arrival for emitter 1185. Using the angle of arrival, the geographic location for the emitter 1185 (e.g., relative geographic coordinates from the antenna) can be determined.

Although only a single emitter is illustrated in Figure 1, each vehicle 1150, 1155 and any other traffic participant or other emitter may be present in the area, and the geolocation for each emitter may be located in the same manner using the same antenna pair or It can be similarly obtained using different antenna pairs. In some cases, narrowband antennas can be used to sensitively monitor a subset of the radio frequency spectrum, but mixed-signal receivers can also cover very wide bands of the radio frequency spectrum, providing geolocation for large numbers and diverse emitters. You can decide. Advantageously, obtaining periodic autocorrelation functions and/or spectral correlation functions using pair-wise antennas described herein can be used to obtain geolocation for all emitters simultaneously.

It will be appreciated that the antenna systems and correlation systems used to determine geolocation can be located at very large distances from the emitter/traffic participant and still be useful for determining geolocation and other information. For example, the signal-to-noise ratio required to determine the geographic location of an emitter/traffic participant according to the techniques described herein may be significantly less than the signal-to-noise ratio required to receive and decode data transmissions made by the emitter/traffic participant. You can. Correlative receivers can be used to determine the location and classification of radio emitters/traffic participants at distances well outside the normal operating range required for wireless communications, but depending on traffic conditions, the range is typically very close. This effectively reduces the required signal-to-noise ratio, since the data from the electromagnetic emissions does not need to be recovered by the correlated receiver, allowing the correlated receiver to be located much further away than would be necessary for a typical receiver, which is typically the case for wireless It establishes a two-way link with the emitter and, as a result, is often located reasonably close to the wireless emitter.

In this way, one or more fixed antenna systems can be located close to the immediate traffic area of the vehicle of interest, but still provide useful input signals to the correlated receiver system to determine the geolocation of the emitter in the traffic flow. Additionally, correlated receivers useful in the systems and methods described herein can provide high discrimination against noise. For example, periodic autocorrelation functions and/or spectral correlation functions can confine noise to a specific location because the signals are self-correlated. In the spectral correlation function, the noise is limited to a certain correlation frequency or periodic frequency (a = 0), while the modulated signal can rise above the detection layer elsewhere and provide a modulation signature. In periodic autocorrelation functions, the noise is limited to a specific correlation frequency or the origin of the periodic frequency (a) and time delay (t) maps.

Along with geolocation information available for multiple emitters/traffic participants, such information can be used in conjunction with other information available to the vehicle (e.g. self-driving or self-driving), for short-range calculations such as LiDAR signals. It could alleviate or reduce the computational burden on vehicles from generating and/or processing intensive signals, or it could help vehicles determine the location of various traffic participants.

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 correlated receiver or antenna system may generate radio emissions that are intended to be reflected at least partially from traffic participants, and then into a receiving mode where the reflected emissions are monitored in the same way as active emissions are analyzed. You can switch. In some cases, the frequency of the expected wireless emissions may be intentionally included, such as specific emission characteristics, such as bandwidth, modulation type, etc., to provide easy differentiation from other wireless emissions or noise, but the systems and methods described herein This is only an option depending on the system and method, as the cross-correlation aspect of the receiver can strongly identify noise or other emissions.

In some cases, the geolocation of any traffic participant may be overlaid on a map, coordinate system, or other user interface, such as visualizing the distribution of emitter locations. Additional information about each emitter can be determined by further examining the obtained periodic autocorrelation function and/or spectral correlation function to determine the geolocation of the emitter. Various types of radio emitters are characterized by, for example, the location and number of features of the periodic autocorrelation function and/or the spectral correlation function, the emission frequency and operating band, the modulation period, the type of coding used to modulate the emission, and the method of generating the emission. They can provide a physical signature that reveals details about the emitter, such as the emitter's various physical characteristics, such as its spectral and temporal response, the wireless service it is using, the type of hardware that makes up a particular emitter, or the configuration of its wireless service provider. It may vary depending on. For example, using known wireless emitter capabilities, specific information about individual wireless emitters can be determined by detecting physical electromagnetic emissions without having to decode or decipher the content. This can be achieved by analyzing the amplitude or phase of the feature in a periodic autocorrelation function and/or a spectral correlation function and/or using a pattern matching function for known signatures. Details of techniques for analyzing signals using correlated receivers are described in U.S. Patent Application 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 physical signature information to the type, class, manufacturer and/or model of the emitter. In some examples, a type or class of emitter may be paired or overlaid with a map or other coordinate system to display emitter locations and the distribution of that type or class. This information may be provided as icon information for the emitter or in a configuration that can be expanded to provide extended details about a specific emitter, such as when a map or coordinate system is displayed in a graphical user interface.

12 is a simplified flow diagram illustrating a method 1200 of determining traffic participant location and/or speed measurements, such as by an autonomous vehicle, for use in determining commands. At block 1205 a signal input pair is created by receiving radio emissions associated with a plurality of traffic participants at a pair of antennas. The distance between a pair of antennas can be known and radio emissions can be received at different times from each antenna. For example, each antenna can generate a time-dependent modulated voltage signal that can be provided as an input signal to a correlated receiver. The antenna may be located within or on the autonomous vehicle, but embodiments are contemplated where the antenna is located outside the autonomous vehicle and signal input is transmitted wirelessly to the autonomous vehicle.

At block 1210, the signal input pairs are processed by the autonomous vehicle's correlation receiver to determine a set of geolocations of a plurality of traffic participants and, optionally, a speed measurement. Time-dependent voltage signals can be quantized, such as using an analog-to-digital converter as the first step in the process. Optionally, the signal can be converted to frequency space by performing a Fourier transform of the time-dependent signal. The signals can then be spectrally correlated using an autocorrelation function, allowing features such as time difference of arrival (TDOA) or angle of arrival (AoA) to be extracted, which can then be used to identify multiple traffic participants or traffic participants. It can be used to determine the geolocation of associated radio emitters. Optionally, an emission signature may be determined for the first signal input pair to determine the class or type of wireless emitter associated with the plurality of traffic participants. For example, an emission signature can identify the physical parameters of a wireless emitter (e.g., frequency performance, bitrate performance, etc.) and the class of service (e.g., service provider) that the wireless emitter uses. This information may be combined with geolocation.

At block 1215, the geolocation and speed measurement information may be evaluated to determine whether the geolocation and speed measurements for the traffic participant were obtained with sufficient precision. Otherwise, process 1200 may branch from decision point 1220 to block 1225, where additional signal input may be provided from one or more different antennas or one or more antennas displaced from those used in block 1205. This may be generated by receiving additional radio emissions associated with multiple traffic participants, such as when the antenna is in or on the autonomous vehicle and the autonomous vehicle is moving. The process may return to block 1210, where processing may be repeated for additional signal inputs to determine updated speed and geolocation information for a plurality of traffic participants. Optionally, acceleration, predicted path, predicted position, or predicted velocity may also be determined using additional signals and processing.

Once it is determined that geolocation and velocity information has been obtained with sufficient precision at block 1215, process 1200 may branch at decision point 1220 to block 1230, where geolocation and Speed measurement information can be provided to autonomous vehicles. This process can occur within an autonomous vehicle, so the information can be used by the autonomous vehicle itself to determine navigation commands. In some cases, geolocation and speed measurement information can be transmitted wirelessly to other autonomous vehicles. In some cases, additional geolocation and velocity information may be received from another autonomous vehicle and used in conjunction with the geolocation and velocity information determined by the autonomous vehicle to determine navigation commands.

13 is a simplified flow diagram illustrating a method 1300 of determining traffic participant location and/or speed measurements according to one example. At block 1305 a signal input pair is created by receiving radio emissions associated with a plurality of traffic participants at a pair of antennas, such as an antenna located outside the specific autonomous vehicle for which navigation commands are to be determined. The distance between a pair of antennas can be known and radio emissions can be received at different times from each antenna. For example, each antenna can generate a time-dependent modulated voltage signal that can be provided as an input signal to a correlated receiver.

At block 1310, the signal input pairs are processed by a correlation receiver to determine a set of geolocations and optionally speed measurements of a plurality of traffic participants. The correlation receiver may be located external to a particular autonomous vehicle for which navigation commands are to be determined, such as a particular autonomous vehicle that is a traffic participant among a plurality of traffic participants. Time-dependent voltage signals can be quantized, such as using an analog-to-digital converter as the first step in the process. Optionally, the signal can be converted to frequency space by performing a Fourier transform of the time-dependent signal. The signals can then be spectrally correlated using an autocorrelation function, allowing features such as time difference of arrival (TDOA) or angle of arrival (AoA) to be extracted, which can then be used to identify multiple traffic participants or traffic participants. It can be used to determine the geolocation of associated radio emitters. Optionally, an emission signature may be determined for the first signal input pair to determine the class or type of wireless emitter associated with the plurality of traffic participants. For example, an emission signature can identify the physical parameters of a wireless emitter (e.g., frequency performance, bitrate performance, etc.) and the class of service (e.g., service provider) that the wireless emitter uses. This information may be combined with geolocation.

At block 1315, the geolocation and speed measurement information may be evaluated to determine whether the geolocation and speed measurements for the traffic participant were obtained with sufficient precision. Otherwise, process 1300 may branch from decision point 1320 to block 1325, where additional signal input may be provided from one or more different antennas or one or more antennas displaced from those used in block 1305. may be generated by receiving additional wireless emissions associated with a plurality of traffic participants, such as using . The process may return to block 1310, where processing may be repeated for additional signal inputs to determine updated speed and geolocation information for a plurality of traffic participants.

Optionally, acceleration, predicted path, predicted position, or predicted velocity may also be determined using additional signals and processing.

Once it is determined that geolocation and velocity information has been obtained with sufficient precision at block 1215, process 1200 may branch at decision point 1220 to block 1230, where geolocation and Speed measurement information may be provided to the autonomous vehicle, for example, through wireless data communication. Optionally, a pair of antennas and/or correlated receivers may be located at a fixed location outside the particular autonomous vehicle. Optionally, the pair of antennas and/or correlation receivers may be located on another autonomous vehicle, such as another autonomous vehicle that is a traffic participant among a plurality of traffic participants.

The process of generating a signal by receiving and processing radio emissions can be used to simultaneously determine the geolocation for as many traffic participants as are within the antenna's detection range. Similarly, the process of receiving wireless emissions to generate a signal and processing to determine geolocation can be repeated as a function of time for a wireless emitter so that the geolocation of the wireless emitter can be tracked over time. Advantageously, continuous tracking of geolocation coupled with a corresponding class or type of wireless emitter can enable individual wireless emitters to be accurately tracked and predicted to be located. Geolocation information, type or class information, speed measurement information, etc. may optionally be provided as a data stream to one or more other traffic participants.

Certain steps illustrated in FIGS. 12 and 13 provide certain methods for determining the geographic location of a traffic participant, according to some examples. Other sequences of steps may also be performed according to alternative embodiments. For example, alternative embodiments may perform the steps described above in a different order. Additionally, Figures 12 and 13 show that individual steps may include multiple sub-steps that may be performed in a variety of orders as appropriate for the individual steps. Additionally, additional steps may be added or removed depending on the specific application. Those skilled in the art will recognize various variations, modifications and alternatives.

As used herein, “comprising” is synonymous with “including,” “containing,” or “characterized by,” and is inclusive, open, or additional. , does not exclude elements or method steps not mentioned. As used herein, “consisting of” excludes any element, step or ingredient not specified in the claim elements. As used herein, “consisting essentially of” does not exclude materials or steps that do not materially affect the basic and novel nature of the claims. Any reference herein to the term “comprising,” particularly in a description of a component of a composition or a description of an element of a device, refers to compositions and methods that essentially consist of and consist of the components or elements mentioned. It is understood that The invention described by way of example herein may be practiced without any element(s), limitation or limitation not specifically disclosed herein.

The terms and expressions used are intended to be terms of description and not limitation, and there is no intention in the use of such terms and expressions to exclude equivalents or portions of the features shown and described, but within the scope of the claimed invention. It is recognized that many variations are possible. Accordingly, although the present invention has been specifically disclosed in terms of preferred embodiments and optional features, modifications and variations of the concepts disclosed herein may be made by those skilled in the art, and such modifications and variations are defined in the present invention as defined by the appended claims. It should be understood that it is considered to be within the scope of.

Claims (40)

A method for mapping a plurality of wireless emitters in a geographic area, comprising:
The above method is,
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 using a correlation receiver to determine a plurality of periodic autocorrelation functions or spectral correlation functions for a plurality of pairs of signal inputs among the set of signal inputs, and
determining a set of geolocations of the plurality of wireless emitters using the periodic autocorrelation function or the spectral correlation function.
Including,
method.
According to paragraph 1,
Overlaying said set of geographic locations on a geographic, network or symbolic map or geographic, network or symbolic map data.
Containing more,
method.
According to paragraph 1,
transmitting the set of geolocations or a subset thereof to a remote server.
Containing more,
method.
According to paragraph 1,
Processing the set of signal inputs includes:
processing a plurality of signal input pairs 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 emissions from the three or more antennas;
determining a set of angles of arrival of the wireless emission at the three or more antennas using the set of time delays, and
determining the set of geolocations of the plurality of wireless emitters using the set of angles of arrival.
Including,
method.
According to paragraph 1,
One or more of the antennas,
coupled directly to the correlation receiver, or
One or more of the antennas,
located remotely from the correlation receiver,
method.
According to paragraph 1,
analyzing one or more of the periodic autocorrelation function or the spectral correlation function to identify a class or type set of the plurality of wireless emitters.
Containing more,
method.
According to clause 6,
overlaying the set of geolocations and the set of classes or types of the plurality of wireless emitters onto a geographic, network or symbolic map or geographic, network or symbolic map data,
Including more,
method. According to paragraph 1,
Determining the set of geolocations of the plurality of wireless emitters comprises:
occurring in real time or substantially in real time;
method.
According to paragraph 1,
steps repeated one or more times,
obtaining a new set of 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 using the correlation receiver to determine a plurality of new periodic autocorrelation functions or spectral correlation functions for a plurality of pairs of signal inputs of the set of new signal inputs, the new periodic autocorrelation functions determining a new set of geolocations of the plurality of wireless emitters using a correlation function or the new spectral correlation function, and
Repeating the steps of tracking the set of geolocations of the plurality of wireless emitters and one or more new sets of geolocations over time one or more times.
Containing more,
method.
According to paragraph 1,
Determining the set of geolocations of the plurality of wireless emitters comprises:
determining a speed set of the plurality of wireless emitters.
Including,
method.
A system for mapping a plurality of wireless emitters in a geographic area, comprising:
The system is,
correlated receiver,
three or more antennas positioned to communicate data with the correlated receiver, and
One or more processors configured to determine a set of geolocations of the plurality of wireless emitters using a periodic autocorrelation function or a spectral correlation function.
Including,
The correlation receiver is,
A signal input corresponding to radio emissions from a plurality of radio emitters received at the three or more antennas to determine a plurality of the periodic autocorrelation functions or the spectral correlation function for a plurality of signal input pairs of the set of signal inputs. configured to process a set of,
system.
According to clause 11,
The one or more processors:
further configured to overlay the set of geolocations on a geographic, network or symbolic map or geographic, network or symbolic map data,
system.
According to clause 11,
The one or more processors:
further configured to transmit the set of geolocations or a subset thereof to a remote server,
system.
According to clause 11,
Processing the set of signal inputs includes:
processing a plurality of signal input pairs 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 emissions from the three or more antennas;
using the set of time delays to determine a set of angles of arrival of the wireless emission at the three or more antennas, and
determining the set of geolocations of the plurality of wireless emitters using the set of angles of arrival.
Including,
system.
According to clause 11,
One or more of the antennas,
coupled directly to the correlation receiver, or
One or more of the antennas,
located remotely from the correlation receiver,
system.
According to clause 11,
The one or more processors:
further configured to analyze one or more of the periodic autocorrelation function or the spectral correlation function to identify a class or type set of the plurality of wireless emitters.
system.
According to clause 16,
The one or more processors:
further configured to overlay the set of geolocations and the set of classes or types of the plurality of wireless emitters onto a geographic, network or symbolic map or geographic, network or symbolic map data.
system.
According to clause 11,
Determining the set of geolocations of the plurality of wireless emitters comprises:
occurring in real time or substantially in real time;
system.
According to clause 11,
The correlation receiver is,
Obtaining a new set of signal inputs corresponding to wireless emissions from the plurality of wireless emitters received at the three or more antennas, and
Processing the set of new signal inputs using the correlation receiver to determine a plurality of new periodic autocorrelation functions or spectral correlation functions for a plurality of pairs of signal inputs among the set of new signal inputs.
is further configured to repeat one or more times, and
The one or more processors:
determining a new set of geolocations of the plurality of wireless emitters using the new periodic autocorrelation function or the new spectral correlation function, and
tracking a set of geolocations and one or more new geolocations of the plurality of wireless emitters over time.
Further configured to repeat one or more times,
system.
According to clause 11,
Determining the set of geolocations of the plurality of wireless emitters comprises:
determining a speed set of the plurality of wireless emitters.
Including,
system. In a method for determining traffic participant location and speed information by an autonomous vehicle,
The above method is,
obtaining a set of signal inputs corresponding to radio emissions associated with a plurality of traffic participants received from three or more antennas;
processing the set of signal inputs using a correlation receiver to determine a plurality of periodic autocorrelation functions or spectral correlation functions for a plurality of pairs of signal inputs of the set of signal inputs,
determining a set of geolocation and/or speed measurement information for the plurality of traffic participants using the periodic autocorrelation function or the spectral correlation function, and
Using the set of geolocation and/or speedometry information by a data processor of an autonomous vehicle to determine navigation commands for the autonomous vehicle.
Including,
method.
According to clause 21,
The obtaining step and the processing step
Repeating the steps one or more times and
Determining additional or more accurate geographic location and speed measurement information for the plurality of traffic participants
Containing more,
method.
According to clause 21,
Processing the set of signal inputs includes:
processing a plurality of signal input pairs 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 emissions from the three or more antennas;
determining a set of angles of arrival of the wireless emission at the three or more antennas using the set of time delays, and
determining the set of geographic locations of the plurality of traffic participants using the set of angles of arrival.
Including,
method.
According to clause 21,
Radio emissions associated with said traffic participants are:
Radio emissions generated by radio emitters of said traffic participants
Including,
method.
According to clause 21,
Transportation participants among the above plurality of transportation participants are:
vehicle or pedestrian,
method.
According to clause 21,
Radio emissions associated with said traffic participants are:
Radio emissions reflected by said traffic participants
Including,
method.
According to clause 21,
generating new wireless emissions and directing the new wireless emissions toward a plurality of traffic participants.
It further includes,
The wireless emission is,
Reflection of said new radio emissions from at least one traffic participant
Including,
method.
According to clause 21,
analyzing one or more of the periodic autocorrelation function or the spectral correlation function to identify a set of classes or types of emitters associated with the plurality of traffic participants.
Containing more,
method.
According to clause 21,
providing the set of geolocation and speed measurement information to another autonomous vehicle corresponding to a traffic participant of the plurality of traffic participants.
Containing more,
method.
According to clause 21,
The correlation receiver is,
It is a component of the autonomous vehicle,
The autonomous vehicle,
Corresponding to a traffic participant among the plurality of traffic participants,
method.
According to clause 21,
The correlation receiver is,
away from the plurality of traffic participants,
The above method is,
Wirelessly transmitting the set of geolocation and speed measurement information to the autonomous vehicle for use in determining or applying the commands to the autonomous vehicle.
Containing more,
method.
In a system for determining traffic participant location and speed measurement information,
The system is,
3 or more antennas,
a correlation receiver positioned to communicate data with the three or more antennas, and
one or more processors
Including,
The correlated receiver is,
A set of signal inputs corresponding to radio emissions associated with a plurality of traffic participants received at said three or more antennas 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. is configured to process,
The processor,
determine a set of geolocation and/or speed measurement information for the plurality of traffic participants using the periodic autocorrelation function or the spectral correlation function; and
configured to determine navigation commands for an autonomous vehicle using the set of geolocation and/or geometric information,
system.
According to clause 32,
The correlation receiver is,
obtaining a new set of signal inputs corresponding to radio emissions associated with the plurality of traffic participants received at the three or more antennas;
Processing the set of new signal inputs using the correlation receiver to determine a plurality of new periodic autocorrelation functions or spectral correlation functions for a plurality of pairs of signal inputs among the set of new signal inputs.
is further configured to repeat one or more times,
The one or more processors:
further configured to determine additional or more accurate geolocation and speed measurement information for the plurality of traffic participants,
system.
According to clause 32,
Processing the set of signal inputs includes:
processing a plurality of signal input pairs 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 emissions from the three or more antennas;
using the set of time delays to determine a set of angles of arrival of the wireless emission at the three or more antennas, and
determining the set of geographic locations of the plurality of traffic participants using the set of angles of arrival;
Including,
system.
According to clause 32,
Radio emissions associated with traffic participants are:
Radio emissions generated by radio emitters of said traffic participants
Including,
system.
According to clause 32,
Transportation participants among the above plurality of transportation participants are:
vehicle or pedestrian,
system.
According to clause 32,
Radio emissions associated with said traffic participants are:
Radio emissions reflected by said traffic participants
Including,
system.
According to clause 32,
The one or more processors:
further configured to analyze one or more of the periodic autocorrelation function or the spectral correlation function to identify a set of classes or types of emitters associated with the plurality of traffic participants,
system.
According to clause 32,
The one or more processors:
further configured to provide the set of geolocation and speed measurement information to one or more other autonomous vehicles corresponding to a traffic participant in the plurality of traffic participants,
system.
According to clause 32,
The correlation receiver and the one or more processors:
Components of the autonomous vehicle,
system.