Method and apparatus for cooperative early threat detection and avoidance in C-V2X. In one aspect, the apparatus detects a threat entity within a threat zone based on data signals received from the threat entity, wherein the threat entity obstructs wireless spectrum or resources utilized in cooperative or automated driving decisions. The apparatus transmits, to at least one second wireless device, a message indicating the threat entity within the threat zone.

A configuration for virtual sensing via sensor sharing for C-V2X scheduling. The apparatus receives, from a first wireless device, a message indicating a threat entity within a threat zone. The threat entity transmits data that interferes with transmission of BSMs. The apparatus determines a candidate resource of a set of candidate resources on which to transmit a BSM based at least in part on the message indicating information related to the threat entity from the first wireless device. The apparatus transmits, to at least a third wireless device, the BSM on a determined candidate resource.

A interference detection device (22) perform the following actions: receiving individual position data from mobile terminals (4(j)) which individual position data indicates an area (12(j)) in which individual ones of the mobile terminals (4(j)) are located based on positioning signals received by the mobile terminals (4(j)); identifying if individual position data may have been affected by one or more interfering signals transmitted by interfering device (14(m)) and interfering with the positioning signals; (A) identifying if a number of mobile terminals (4.sub.v(j)) in a first area (18) is higher than a maximum threshold number, and, if so, determining that individual position data of the number of mobile terminals (4.sub.v(j)) may have been affected by the interfering signals; or (B) identifying if a number of the mobile terminals (4(j)) in a second area (36) is lower than a minimum threshold number; and, if so, determining that individual position data of the number of mobile terminals (4(j)) may have been affected by interfering signals; or (C) receiving further individual position data which indicates further areas (18) in which mobile terminals (4(j)) are located based on another positioning technique than a positioning technique used to determine the individual position data as received from the mobile terminals (4(j)); determining if the areas (12(j)) overlap with the further areas (18) at least to a minimum extent, and, if not, determining that individual position data of the mobile terminals (4(j)) may have been affected by the interfering signals.

Systems, methods, and apparatus for identifying, tracking, and disrupting UAVs are described herein. Sensor data can be received from one or more portable countermeasure devices or sensors. The sensor data can relate to an object detected proximate to a particular airspace. The system can analyze the sensor data relating to the object to determine a location of the object and determine that the object is flying within the particular airspace based at least in part on location data. A portable countermeasure device can be identified that corresponds to the location of the object. The system can transmit information about the object to the identified portable countermeasure device. The portable countermeasure device can transmit additional data relating to the object to the system.

Provided is a method and a computer device for performing the method for defending a perimeter against a small unmanned aerial system (sUAS). The method includes detecting a presence of a wireless access point (WAP) associated with a sUAS; analyzing data packets intercepted from the WAP; determining the type of sUAS based on the data packets that were intercepted using a machine learning classifier; determining one or more exploits from a library of exploits to initiate against the sUAS based on the type of sUAS determined by the machine learning classifier; and transmitting the one or more exploits to the sUAS.

The system and methods described herein aids in the defense of unmanned vehicles, such as aerial vehicles, from wifi cyber attacks. Such attacks usually do not last long and in the case of many point-to-point command and control systems, the attacks originate from close proximity to the unmanned vehicle. The system and methods described herein allow a team to rapidly identify and physically respond to an adversary trying to take control of the unmanned vehicle. Another aspect of the embodiment taught herein is to allow for the location of a wifi signal in a hands-free manner by able to visualize the source of the signal using an augmented reality display coupled to an antenna array.

A method, a node and a detector for detecting an interfering signal in a wireless network communication system comprising a network manager and several nodes, each node (202B) comprising a detector (204) for receiving input signals from at least one antenna, a delay component (205) for delaying a received input signal, and a receiver (206RX) for determining an energy pattern of expected received input signals. The detector (204) is configured to send an alarm signal to the receiver (206RX) depending on the presence or absence of an interfering signal from an interferer 203 and an active/inactive state of the receiver (206RX).

Systems, methods, and apparatus for identifying, tracking, and disrupting UAVs are described herein. A tracking system can include one or more first computing devices that receive sensor data associated with an object in a particular airspace from one or more sensors. The first computing device can analyze the sensor data relating to the object to determine information about the object. A portable countermeasure device can include one or more second computing devices. The second computing device can receive the information relating to the object. The second computing device can display a visual indicator indicating the information on a display.

A null steering adjuster in a stationary wireless network identifies the presence or absence of a current set of phase differences in a dataset. The dataset includes legitimate sets of phase differences detected between radio frequency signals received by multiple antennas from respective legitimate sources. The current set of phase differences is detected between radio frequency signals currently received by the antennas. When the current set of phase differences is absent from the dataset, a null is created in the antenna pattern of the antennas in the direction of the currently-received radio frequency signals. When the current set of phase differences is present in the dataset, the antenna pattern is maintained.

A wireless communication system having base stations and remotely located terminal units. The base stations and the remotely located terminal units communicate data over operational wireless communication links assigned to respective sub-channels having tiles separated by frequency and time. Detectors for analyzing extraneous received signals in unassigned tiles of the communication links discriminate between a first type of extraneous signals detected in unassigned tiles of one sub-frame and also detected in other unassigned tiles, and a second type of extraneous signals detected in the unassigned tiles but not detected in other unassigned tiles. The reaction of the base stations is different based on the type of extraneous signals.