Abstract: The present subject matter provides various technical solutions to technical problems facing UAV detection, threat assessment, and mitigation purposes. UAV detection may be accomplished using a variety of UAV sensors and systems, which may be used in an Unmanned Aerial System Mitigation and Detection system to generate a UAV Automated Threat Assessment and a UAV mitigation solution. The UAV Automated Threat Assessment may be generated by combining input from various sensors and systems. For example, the UAV Automated Threat Assessment may selectively combine data received from geographically arranged sensors, assemble the input from those sensors using a user-adjustable artificial neural network (ANN), determine whether a potential intruding UAV is not a threat, is transiting, is loitering, or is attacking, and generates a mitigation solution output to an operator that includes an automated mitigation notification.

Abstract: The present subject matter provides various technical solutions to technical problems facing UAV detection, threat assessment, and mitigation purposes. UAV detection may be accomplished using a variety of UAV sensors and systems, which may be used in an Unmanned Aerial System Mitigation and Detection system to generate a UAV Automated Threat Assessment and a UAV mitigation solution. The UAV Automated Threat Assessment may be generated by combining input from various sensors and systems. For example, the UAV Automated Threat Assessment may selectively combine data received from geographically arranged sensors, assemble the input from those sensors using a user-adjustable artificial neural network (ANN), determine whether a potential intruding UAV is not a threat, is transiting, is loitering, or is attacking, and generates a mitigation solution output to an operator that includes an automated mitigation notification.

Abstract: The present subject matter provides various technical solutions to technical problems facing UAV detection and mitigation. Information received from UAV detection sensors may be analyzed or matched against known UAV characteristics. The analysis or matching may be used to identify the UAV, analyze the UAV characteristics or navigational behavior, and classify the UAV behavior and the UAV itself. The UAV may be classified as either compliant, ignorant (e.g., unintentional) and noncompliant, or purposeful (e.g., intentional) and noncompliant. The UAV classification may be improved by using UAV characteristic analysis performed by an artificial neural network (ANN) algorithm using specific UAV classifiers. A UAV mitigation command or mitigation response may be generated based on the UAV characteristic analysis combined with a UAV safety risk assessment. The mitigation command may cause nondestructive interference, destruction, capture, or another UAV mitigation response.

Abstract: The present subject matter provides various technical solutions to technical problems facing UAV detection and mitigation. Information received from UAV detection sensors may be analyzed or matched against known UAV characteristics. The analysis or matching may be used to identify the UAV, analyze the UAV characteristics or navigational behavior, and classify the UAV behavior and the UAV itself. The UAV may be classified as either compliant, ignorant (e.g., unintentional) and noncompliant, or purposeful (e.g., intentional) and noncompliant. The UAV classification may be improved by using UAV characteristic analysis performed by an artificial neural network (ANN) algorithm using specific UAV classifiers. A UAV mitigation command or mitigation response may be generated based on the UAV characteristic analysis combined with a UAV safety risk assessment. The mitigation command may cause nondestructive interference, destruction, capture, or another UAV mitigation response.