5 results about "Automatic dependent surveillance-broadcast" patented technology

This invention discloses an abnormal behavior detection method for ships based on an ADS-B big data platform, specifically relating to the field of ship navigation safety monitoring technology. The method involves acquiring automatic correlation surveillance broadcast data of ships in a target sea area, constructing a ship trajectory evolution matrix, and generating a ship micro-disturbance motion feature tensor. It also involves constructing a ship neighborhood interaction topology network and calculating the trajectory disturbance propagation weights between nodes to form an abnormal propagation probability matrix. Furthermore, it establishes a coupling response relationship between the local trajectory disturbance energy sequence and the neighborhood interaction intensity through temporal folding mapping, generating an abnormal behavior evolution prediction curve and calculating an abnormal energy aggregation index. Combined with the abnormal propagation probability matrix, it generates a risk distribution map of abnormal ship behavior, extracts implicit behavior indicators, and dynamically matches them with preset abnormal behavior patterns. This invention can effectively identify micro-scale abnormal navigation behavior in complex sea environments, improving the accuracy of abnormal ship behavior detection and early warning capabilities.

A system and a method include a control unit configured to determine situational information regarding a plurality of aircraft within an airspace. The control unit is configured to determine the situational information based on automatic dependent surveillance-broadcast (ADS-B) signals output by the plurality of aircraft and received by an ADS-B receiver of a tracking sub-system.

A system and method are described for identifying the location of jamming or spoofing of information that is used in a Global Navigation Satellite System (GNSS) geolocation system, in areas in which it is difficult or impractical to install detection devices. The system and method make use of existing vessel-tracking technologies, such as Automatic Dependent Surveillance– Broadcast (ADS-B) – for aircraft vessels – and Automatic Identification System (AIS) – for naval vessels, to collect data on the speed and trajectory of large numbers of vessels and to use that data to extrapolate areas in which spoofing or jamming may be occurring. The system and method include techniques for sampling tracking data over periods of time in order to establish when data is sufficiently anomalous to indicate the potential for spoofing or jamming to be occurring for a particular tracked vessel. The overall system and method also includes a weighting protocol for data from multiple vessels to predict areas in which spoofing or jamming may be occurring by assigning anomalous vessel signals that are geographically nearby to values as to their potential to indicate spoofing or jamming, and thus calculating an area around those vessels as potentially subject to spoofing or jamming. A processing hub or multiple processing hubs include facilities to compare location information received by a group of vessels with anomalous signals and to determine whether the location information for those vessels is consistent with predicted location information for those vessels. In the event that there is a discrepancy between the predicted location information and the received location information, the processing hub or hubs can take a number of remediative actions, such as assigning the calculated area as one that has been identified as being subject to spoofing or jamming, and sending a warning signal to vessels in that calculated area that their GNSS location information may not be reliable. The system and method of the present invention can also alert affected vessels of the need to switch to a backup or alternative geolocation or navigation system, when it is determined that the GNSS geolocation system is determined to be inaccurate or unavailable in an area in which the vessels are currently located. Artificial Intelligence (AI) or Machine Learning (ML) can be used to better predict and correlate data so the most accurate approximation of where spoofing or jamming is occurs may be identified and subscribers to the system may be alerted.

A system and method for aircraft surface navigation is disclosed. The method may include receiving W-band data from a W-band sensor configured to detect objects including non-cooperative aircraft. The method may also include receiving Automatic Dependent Surveillance-Broadcast (ADS-B) data from an ADS-B receiver configured to receive ADS-B signals from cooperative aircraft. Additionally, the method may involve identifying navigation information based on the W-band data and the ADS-B data, the navigation information comprising cooperative traffic and non-cooperative traffic, and displaying the navigation information via a display.

A system for localization of an autonomous vehicle includes a plurality of radio receivers configured to receive automatic dependent surveillance-broadcast (ADS-B) radio signals transmitted by a plurality of overhead aircraft, and at least one processor coupled to at least one memory and configured to perform operations comprising: based upon a first, a second, and a third ADS-B radio signals transmitted by a first, a second, and a third overhead aircraft, respectively, computing an angle from, and a distance between, a radio receiver to a respective overhead aircraft, and computing a relative motion of the respective overhead aircraft; and based upon position information included in the first, second, and third ADS-B radio signals, and using the first angle, second angle, third angle, first distance, second distance, third distance, the relative motion of each of the first, second, and third overhead aircraft, performing multilateration to determine a position of the autonomous vehicle.