Vehicle signal threat detection

Abstract

Methods and systems are provided including receiving radio wave transmissions; processing the radio wave transmissions to identify one or more radio wave signals corresponding to unmanned vehicles (UVs); comparing the identified one or more radio wave signals with a mains power frequency to determine whether at least one of the one or more radio wave signals is modulated at the mains power frequency; determining that there is no mains power modulation of at least one of the one or more radio wave signals; and responsively issuing an alert of possible UV presence.

Description

VEHICLE SIGNAL THREAT DETECTIONFIELD OF THE INVENTION

[0001] The present invention relates to surveillance systems for monitoring unmanned or manned aerial, land, or sea vehicles and in particular to methods and systems for remote vehicle detection.BACKGROUND

[0002] Drones and other small, unmanned vehicles (UVs) are used more and more for military and espionage purposes. The US Federal Aviation Administration (FAA) estimated that in 2017 there were three million drones worldwide. Drones may replace many types of ground-based delivery vehicles. However, as drones and other vehicles proliferate, the threats they present will require rapid detection and identification by defense forces. (Note: hereinbelow, “drone” refers to any type of unmanned aerial vehicle, or UAV. The term UV refers to drones and other unmanned vehicles including, but not limited to: cars, ships and mobile robots.)

[0003] The ability to detect an incoming vehicle attack (whether manned or unmanned) is therefore increasingly important. Ideally, at least several seconds of warning should be provided to defense forces, meaning that detection of an incoming vehicle, particularly a UAV, should be successfully performed at a distance of a kilometer or more. An appropriate warning distance may be from at least one kilometer, in all weather and lighting conditions (including arrival from the direction of the sun), as well as in conditions of low visibility, such as smoke, dust and sand. These requirements pose serious problems for surveillance methods such as optical, thermal, acoustic and even radar detection.

[0004] Some vehicle detection methods focus on capturing control signals transmittedbetween a control unit and the vehicle. However, these signals may be obscured by a variety of means.SUMMARY

[0005] Embodiments of the present invention provide systems and methods including receiving radio wave transmissions, identifying one or more radio wave signals corresponding to UAVs, and comparing the identified one or more radio wave signals with a mains power frequency to determine whether at least one of the one or more radio wave signals is modulated at the mains power frequency. If there is no mains power modulation of at least one of the one or more radio wave signals, the system issues an alert of possible UAV presence.BRIEF DESCRIPTION OF DRAWINGS

[0006] For a better understanding of various embodiments of the invention and to show how the same may be carried into effect, reference will now be made, by way of example, to the accompanying drawings. Structural details of the invention are shown to provide a fundamental understanding of the invention, the description, taken with the drawings, making apparent to those skilled in the art how the several forms of the invention may be embodied in practice.

[0007] In the accompanying drawings:

[0008] Fig. 1 is a schematic block diagram for vehicle signal detection, particularly unmanned vehicle (UV) signal detection, according to embodiments of the present invention;

[0009] Fig. 2 is a flow diagram of a process for vehicle signal detection, according to embodiments of the present invention;

[0010] Fig. 3 is a graph of a radio wave transmission including a signal indicative of an unmanned vehicle, according to embodiments of the present invention; and

[0011] Fig. 4 is a graph of the same signal indicative of an unmanned vehicle, in another time base to indicate a mains alternating current frequency modulation, according to embodiments of the present invention; and

[0012] Fig. 5 is a flow diagram of a process for vehicle signal detection, with predetermination of identifying signal characteristics, according to embodiments of the present invention.DETAILED DESCRIPTION

[0013] It is to be understood that the invention and its application are not limited to the system and methods described below or to the arrangement of the components set forth or illustrated in the drawings, but are applicable to embodiments that may be practiced or conducted in various ways.

[0014] Unmanned vehicles (UVs) as well as manned vehicles (MVs) can be used for armed attacks, disruption of operations, and for espionage. The term "restricted site" is used hereinbelow to refer to any site that may be the target of such attack or espionage and therefore could benefit from a system of advanced warning of approaching UVs and MVs, particularly unmanned aerial vehicles (UAVs). Such restricted sites may include civil infrastructure sites, businesses, residential areas, and agriculture areas, as well as government and military sites.

[0015] Fig. 1 is a schematic diagram, depicting components of a system 100 for detecting incoming vehicles, particularly unmanned aerial vehicles (UAVs), according to some embodiments of the present invention. Hereinbelow, system 100 is also referred to asa Defense Control Unit (DCU).

[0016] System 100 includes one or more antennas 102, which sense electromagnetic radiation emissions, i.e., radio wave transmissions, from sources that many include an intruding vehicle, such as a drone 104 (i.e., a UAV), or other mobile vehicles (i.e., not powered by a fixed power source, such as battery or fuel -powered vehicles). The system may also detect radio from other non-mobile electrical equipment, such as a stationary motor 106, that receive power from a mains electric power source (e.g., 50 / 60 Hz power). The antenna also may be configured as four separate antennas, oriented in four perpendicular directions to provide a directional indication of incoming signals. Multiple antennas may be used to provide more precise coordinates of an incoming vehicle, for example by triangulation of results.

[0017] Electrical signals provided by the antenna 102 may be processed by one or more signal filters 108, which may include a low-pass and / or bandpass filter. The signals may then be processed and amplified by a receiver 110, which is described further hereinbelow with respect to Figs. 2 and 3. The receiver signal output is then sampled and processed by a processor, indicated in the figure as system-on-a-chip (SOC) 112. Any suitable processor technology may be employed to perform the signal processing described herein. A compact unit may employ a system-on-a-chip, while alternative signal processing implementations may include microcontrollers and stand-alone personal computers, as well as multiple, distributed units. In some embodiments, the receiver or the SOC may include a field programmable gate array (FPGA), programmed to make multiple simultaneous measurements, to facilitate calculation of multiple locations of an incoming vehicle, thereby also allowing calculation of incoming vehicle speed.

[0018] The SOC 112 also may receive input from an AC frequency and / or phasedetector 120, which provides a signal at the frequency and / or phase of a mains power supply 122.

[0019] The SOC 112 may compare the received signals (i.e., electromagnetic radiation) with stored examples of known (i.e., previously determined) signal characteristics of vehicles, such as UV’s and UAVs. Testing to obtain examples of signal characteristics is described in US Patent Application Publication US 2022 / 0003525 Al, titled, “Vehicle detection system and methods,” (to Leor Hardy, the inventor of the present invention), the teachings of which are incorporated herein by reference. Known signal characteristics (e.g., patterns) may include, for example, pulses from UAV motors in the range 30 to 400 MHz, or non-modulated signals from electronic circuits of DC-operated vehicles in the range 1400 to 1800 MHz.

[0020] When previously identified signals characteristic of an incoming signal are detected, the SOC 112 then compares modulation of the detected signals with the mains power frequency. When a signal is mains-power frequency modulated, it is determined to be stationary, and therefore not a mobile threat.

[0021] The process of detecting signals based on previously determined signal characteristics (also referred to herein as “identifying signal characteristics”) is described below with respect to Fig. 5. Alternatively, as described below with respect to Fig. 2, the SOC 112 may operate without having a set of previously determined signal patterns, instead scanning signals in a range of frequencies and determining whether or not detected signals are modulated by a mains-power frequency.

[0022] When a detected signal does not include mains power modulation, one or more security alerts may be generated by the SOC 112 and transmitted to an alert system 130, which may trigger enemy vehicle interception mechanisms (e.g., net launchers, radiojammers, anti-drone drones, and / or lasers). The alert system may also perform alternative or additional functions, such as issuing alarms to human operators and notifying external security forces. The SOC 112 may continue to send data to the alert system to permit ongoing tracking of an incoming vehicle.

[0023] The processing by the SOC 112 may also include processing multiple received data streams from multiple antennas, for example in order to triangulate a position of a UV (particularly a UAV). Processing may include processing streams to determine additional features of a UV incoming path, such as determining a position and speed of a drone, or identification of multiple incoming UVs in a pack.

[0024] Fig. 2 is a flow diagram, depicting a process 200 of detecting incoming unmanned vehicles, according to some embodiments of the present invention. Steps of the process 200 are as follows.

[0025] At a step 212, the radio receiver is configured to receive radio signals at range of frequencies including frequencies previously determined to include identifying signals (that is signals with the identifying characteristics described above). The sensitivity of the radio receiver is configured to measure radiation at a diminished dBpV / m level required for detected intruding vehicles in the target restricted area, such as 1 km or more. The frequency range of the radio receiver may be set to a wide range based on known ranges of characteristic signals of vehicles that may be a threat, such as a range of 30 to 1600 MHz.

[0026] At a step 220, the SOC 112 (or similarly configured processor) scans the received range of radio waves to detect potential “signals of interest.” “Signals of interest” are typically signals with levels above background noise. Such signals may be further tested by a machine learning algorithm including with the SOC to determine if the signals include recognizable patterns, such as modulating frequencies. That is, signal waveforms atmultiple received frequencies may be analyzed by a machine learning system or by other algorithms to identify recurring patterns.

[0027] The SOC then determines whether or not detected signals (i.e., “signals of interest”) are modulated by the mains power frequency (e.g., 50 or 60 Hz). I f such modulation is present in all signals received, then the process forks, at a step 222, to repeat the steps 212 and 220 of detecting radio wave signals and testing them.

[0028] If there is no mains modulation of an identified signal, this is an indication that an incoming vehicle (e.g., UV, MV or UAV), may be present. Consequently, at a step 224, the system may be configured to issue a warning alert to a defense system, such as a counter-drone system. The alert may include parameters such as vehicle position and speed.

[0029] The oscilloscope recording of Fig. 3 indicates a sample of an identifying signal characteristic, showing that there is a pulse wave signal characteristic emitted by some UAVs, with a pulse repetition interval PRI of 35?.s.s. Other identifying signal characteristics may include:; pulse width (PW); pulse rise and fall times; inter-pulse amplitude, frequency or phase modulation; slow amplitude modulation; spectrum width; and spectrum shape. Modulation can be seen, for example, in the oscilloscope recording of Fig. 4. The sweep is set at 100 ms, and the 50 Hz mains modulation can be seen as 5 peaks (i.e., 50 Hz times .1 second) rising above the noise.

[0030] As described above, the SOC 112 (i.e., the system processor) may determine the mains power frequency by receiving input from an AC frequency detector, which provides a signal at the frequency of a mains power supply. Alternatively, the SOC may be configured to identify three or more radio wave signals corresponding to vehicles, such as UAVs. If all three or more signals share a common modulation in the range of a mains power frequency they are from a stationary source. If there is at least one that does not sharea common, modulating, mains frequency, the additional one or more signals without the modulating frequency are assumed to be signals from mobile vehicles and an alert is triggered.

[0031] The system may also identify multiple vehicles having similar or different identifying characteristics. In an area in which there are legitimate UVs (e.g., UAVs, that is, drones), such as a business site receiving UAV shipments or dispatching UAV deliveries, system 100 may also be configured to protect the area against illegitimate UVs, while permitting the presence of authenticated UVs.

[0032] Fig. 5 is a flow diagram, depicting a process 500 of detecting incoming vehicles, according to further embodiments of the present invention. In addition to steps described above with respect to process 200 of Fig. 2, process 500 includes a calibration / test stage 502 including two steps. Test signals from a vehicle under test are received at a step 504, and the vehicle’s signal characteristics are determined at a step 506.

[0033] Testing to identify radio wave signal characteristic of vehicles (e.g., UVs or MVs), is described, for example, in the above-mentioned US Patent Application Publication US 2022 / 0003525. As described therein, a test vehicle may be operated in an anechoic chamber, that is, an electromagnetically-insulated chamber. Such a chamber absorbs electromagnetic radiation, thereby reducing reflected waves, while also reducing the presence of external electromagnetic radiation. Radio wave emissions from a test vehicle are measured and recorded at multiple frequencies. Such emissions may be due to several vehicle sources, such as emissions from device motors and from oscillators used as clocks in processors or as local oscillators (LO) in GPS and other receivers. At the step 504, a spectrograph may be configured to scan a range of frequencies emitted by a test vehicle, for example in a range of 30 MHz to 1.6 GHz, as well as frequencies that are at knownoscillations, such as 1.6 GHz for a GPS receiver. Determining the signal characteristics (i.e., “fingerprint”) of a test vehicle does not require testing it from a close distance, but the determination of identifying electromagnetic radiation characteristics is simplified when external noise is reduced. In one embodiment, key frequencies are determined that are then used to "fingerprint" a given vehicle, that is, to determine identifying signal characteristics.

[0034] At the second test step 506, the multiple measured frequencies are analyzed. Algorithms, such as algorithms generated by machine learning, may be applied to determine if signals present at the measured frequencies include recognizable patterns, such as modulating frequencies or the frequency itself. That is, waveforms at the multiple measured frequencies may be analyzed by a machine learning system or by other predetermined algorithms to identify recurring signal patterns.

[0035] Oscillators in a UAV emit radiation as described in "SGP-330 GPS RECEIVER Electromagnetic Emission — FCC MEASUREMENT REPORT," by South Korean manufacturer Samyung Enc. A GPS receiver emits radio frequency signals at levels near 40 dBpV / m. The signal frequencies indicated in the article indicate the emission of harmonics of a 16MHz crystal. Characteristic signals may also include signals in the 1400 to 1800 MHz range generated by drone processor clock circuits and by drone radio wave receivers oscillators. Signal reception at a recurring amplitude modulating frequency of 200 KHz was also detected from one UAV.

[0036] A pulse pattern generated by a drone DC to AC converter, power-generating circuit, has also been identified in the range of 30 to 400 MHz. Such consistent patterns may be denoted as identifying characteristics.

[0037] The signal power of signals during testing with vehicles in close proximity to the receiver is significantly greater than during field operation, which requires appropriatecalibration to receive signals from more distant vehicles. For example a signal measured as -50 dBm, at a distance of 1 meter would be measured as -110 dBm from a distance of one kilometer. This level of power can be picked up by various means, such as by a super heterodyne receiver, or by a direct demodulation radio receiver, or by processing the raw data from an analog to digital converter. Identifying characteristics such as cycle time and waveform can differentiate the signal from other signals at similar frequencies.

[0038] After testing, an operational stage 510 may be executed by the system 100, in order to protect a restricted area.

[0039] At a step 212, (previously described with respect to process 200 of Fig. 2), the radio receiver is configured to receive radio signals at the frequencies that may include signals with the identifying characteristics (i.e., identified during the test stage).

[0040] The sensitivity of the radio receiver may be configured to measure radiation at a diminished dBpV / m level required for detected intruding vehicles in a large restricted area, such as 1 km or more. The frequency range of the radio receiver may be set to a wide range according to the results determined at the step 206. For example, a wideband radio receiver may be configured for receiving frequencies of 30 to 1600 MHz.

[0041] At a step 514, the SOC (or similarly configured processor) compares received signals with the identifying characteristics of vehicles (i.e., UVs and MVs) to determine if such characteristics are present. If not present, the process forks at a step 516 to repeat the steps 212 and 514 of detecting radio wave signals and testing them.

[0042] If identifying characteristics are present, the SOC then determines if the identifying characteristics are modulated by the mains power frequency (e.g., 50 or 60 Hz), at a step 520. If such modulation is present, then the process forks, at the step 222 (as described above with respect to Fig. 2), to repeat the step 212 of receiving radio wavesignals and then subsequent steps of analyzing those signals.

[0043] If there is no mains modulation of the identifying signal characteristics, this is an indication that an incoming vehicle, such as a UAV, may be present. Consequently, at the step 224, as described above with respect to Fig. 2, the system may be configured to issue a warning alert to a defense system, such as a counter-drone system. The alert may include parameters such as vehicle position and speed.

[0044] As described above, the SOC may also determine the mains power frequency by receiving input from an AC frequency detector that provides a signal at the frequency of a mains power supply. Alternatively, the processor may be configured to identify three or more radio wave signals corresponding to vehicles, such as UAVs., as described above with respect to Fig. 2. If all three or more signals share a common modulation in the range of a mains power frequency they are from a stationary source. If there is at least one that does not share a common, modulating, mains frequency, those one or more signals may be signals from mobile vehicles and an alert is triggered.

[0045] EXAMPLES

[0046] An example 1 of the present invention method, for identifying presence of an unmanned vehicle (UV), includes: receiving radio wave transmissions; processing the radio wave transmissions to identify one or more radio wave signals with no mains power modulation; and responsively issuing an alert of possible UV presence.

[0047] An example 2 is a method including features of example 1 and processing the radio wave transmissions by matching the one or more radio wave signals to previously determined radio wave signals corresponding to UVs, as well as comparing the matched one or more radio wave signals with the mains power frequency and determining that there is no mains power modulation of at least one of the one or more matched radio wave signals.The process may further include issuing the alert of possible UV presence responsively to determining the lack of mains power modulation.

[0048] An example 3 is a method including the features of example 2, and in which comparing the matched one or more radio wave signals with the mains power frequency comprises identifying three or more radio wave signals corresponding to UVs; comparing modulation of the three or more identified signals to determine whether there is a common mains power modulation frequency of at least two of the identified signals. Upon determining that there is no mains power modulation of at least one of the one or more radio wave signals, the process further includes determining that the common mains power modulation is not shared by at least one of the three or more radio wave signals.

[0049] An example 4 is a method including the features of any of the above examples, and at least one of the identified one or more radio wave signals is identified as being a signal in the 1400 to 1800 MHz range generated by drone processor clock circuits and by drone radio wave receivers oscillators.

[0050] An example 5 is a method including the features of any of the above examples, and at least one of the identified one or more radio wave signals is identified by a pulse pattern generated by a drone DC to AC converter power generating circuit in the range of 30 to 400 MHz.

[0051] Further examples include systems for identifying presence of an unmanned vehicle (UV), including: a receiver configured to receive radio wave transmissions; and a processor having associated non-transient memory with instructions that when executed implement steps including: receiving radio wave transmissions; processing the radio wave transmissions to identify one or more radio wave signals with no mains power modulation; and responsively issuing an alert of possible UV presence. Additional exemplary systemsare configured to perform any of the methods described by the previous examples.

[0052] It is to be understood that all or part of a process and of a system implementing the process of the present invention may be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations thereof. All or part of the process and system may be implemented as a computer program product, tangibly embodied in an information carrier, such as a machine -readable storage device or in a propagated signal, for execution by, or to control the operation of, data processing apparatus, such as a programmable processor, computer, or deployed to be executed on multiple computers at one website or distributed across multiple websites. Memory storage may also include multiple distributed memory units, including one or more types of storage media. Examples of storage media include, but are not limited to, magnetic media, optical media, and integrated circuits. A computer configured to implement the process may access, provide, transmit, receive, and modify information over wired or wireless networks. The computing may have one or more processors and one or more network interface modules. Processors may be configured as a multi-processing or distributed processing system. Network interface modules may control the sending and receiving of data packets over networks.

[0053] It is to be further understood that the scope of the present invention includes variations and modifications thereof which would occur to persons skilled in the art upon reading the foregoing description and which are not disclosed in the prior art.

[0054] It is to be understood with respect to the above description that although various features of the invention may be described in the context of a single embodiment, the features may also be provided separately or in any suitable combination. Conversely, although the invention may be described herein in the context of separate embodiments forclarity, the invention may also be implemented in a single embodiment. Certain embodiments of the invention may include features from different embodiments disclosed above, and certain embodiments may incorporate elements from other embodiments disclosed above. Meanings of technical and scientific terms used herein are to be commonly understood as by one of ordinary skill in the art to which the invention belongs, unless otherwise defined. Method steps associated with the system and process can be rearranged and / or one or more such steps can be omitted to achieve the same, or similar, results to those described herein.

Claims

CLAIMS1. A method for identifying presence of an unmanned vehicle (UV) comprising: receiving radio wave transmissions; processing the radio wave transmissions to identify one or more radio wave signals with no mains power modulation; and responsively issuing an alert of possible UV presence.

2. The method of claim 1, wherein processing the radio wave transmissions comprises matching the one or more radio wave signals to previously determined radio wave signals corresponding to UVs; comparing the matched one or more radio wave signals with the mains power frequency and determining that there is no mains power modulation of at least one of the one or more matched radio wave signals; and responsively issuing the alert of possible UV presence.

3. The method of claim 2, wherein comparing the matched one or more radio wave signals with the mains power frequency comprises identifying three or more radio wave signals corresponding to UVs; comparing modulation of the three or more identified signals to determine whether there is a common mains power modulation frequency of at least two of the identified signals; and wherein determining that there is no mains power modulation of at least one of the one or more radio wave signals comprises determining that the common mains power modulation is not shared by at least one of the three or more radio wave signals.

4. The method of claim 1, wherein at least one of the identified one or more radio wave signals is identified as being a signal in the 1400 to 1800 MHz range generated by drone processor clock circuits and by drone radio wave receivers oscillators.

5. The method of claim 1, wherein at least one of the identified one or more radio wave signals is identified by a pulse pattern generated by a drone DC to AC converter power generating circuit in the range of 30 to 400 MHz.

6. A system for identifying presence of an unmanned vehicle (UV) comprising: a receiver configured to receive radio wave transmissions; and a processor having associated non-transient memory with instructions that when executed implement steps comprising: receiving radio wave transmissions; processing the radio wave transmissions to identify one or more radio wave signals with no mains power modulation; and responsively issuing an alert of possible UV presence.

7. The system of claim 6, wherein processing the radio wave transmissions comprises: matching the radio wave transmissions to one or more previously determined radio wave signals corresponding to UVs; comparing the matched one or more radio wave signals with the mains power frequency and determining that there is no mains power modulation of at least one of the one or more matched radio wave signals; and responsively issuing the alert of possible UV presence.

8. The system of claim 7, wherein further comprising: identifying three or more radio wave signals corresponding to UVs; comparing modulation of the three or more identified signals to determine whether there is a common mains power modulation frequency of at least two of the identified signals; and determining that there is no mains power modulation of at least one of the one or more radio wave signals by determining that the common mains power modulation is not shared by the at least one radio wave signals.

9. The system of claim 6, wherein at least one of the identified one or more radio wave signals corresponding to UVs is identified as being a signal in the 1400 to 1800 MHz range generated by drone processor clock circuits and by drone radio wave receivers oscillators.

10. The system of claim 6, wherein at least one of the identified one or more radio wave signals corresponding to UVs is identified by a pulse pattern generated by a drone DC toAC converter power generating circuit in the range of 30 to 400 MHz.

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