UAV Detection via Datagram Frequency Spectrum Analysis
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Solution Overview
Problem
The security of sensitive information is compromised by covert surveillance methods, including UAV-based surveillance and malicious modification of telephone systems, as well as unauthorized UAVs using packetized wireless data networks, necessitating a method to detect constant-datagram-rate network traffic indicative of UAV presence.
Innovation Solution
A system and method utilizing frequency spectrum analysis of datagram arrival times to classify wireless data traffic, involving capturing data from Wi-Fi receivers, sorting by media access control-layer parameters, and using threshold functions to detect peaks, which can identify constant-datagram-rate traffic potentially containing video or command messages from UAVs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequency spectrum analysis is performed on all captured wireless data traffic, then detection accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent segments the analysis process by first filtering traffic at the MAC layer to identify constant-datagram-rate streams, then performing frequency spectrum analysis only on those specific streams rather than all captured traffic. This segmentation maintains detection accuracy for UAV traffic while reducing overall processing time and computational resources.
Solution Approach 2:
The patent performs preliminary filtering and classification of wireless data traffic before conducting frequency spectrum analysis. By pre-identifying constant-datagram-rate streams through MAC layer filtering, the system prepares the data in advance, enabling faster and more efficient subsequent analysis without compromising detection accuracy.
2Measurement precision
If multiple Wi-Fi receivers are used to capture network data traffic, then detection coverage improves, but device complexity increases
Solution Approach 1:
The patent employs multiple Wi-Fi receivers that can be periodically switched between different radio-frequency channels, allowing a single receiver to perform multiple channel monitoring functions. This multi-functionality approach improves detection coverage across multiple channels while avoiding the need for multiple simultaneously operating receivers, thus reducing system complexity.
3Measurement precision
If filtering is applied to separate constant-datagram-rate traffic from other traffic, then detection precision improves, but processing complexity increases
Solution Approach 1:
The patent replaces complex manual filtering processes with automated frequency spectrum analysis and threshold-based detection algorithms. The system automatically identifies constant-datagram-rate traffic patterns through mathematical analysis of datagram arrival times, substituting mechanical filtering complexity with computational algorithms that improve detection precision without requiring manual intervention.
Data Source
AI summary
A system and method for detecting unmanned aerial vehicles (UAV) includes capturing a set of wireless data traffic from a wireless transmission and performing frequency spectrum analysis on datagram arrival times to classify the wireless data traffic based upon potential constant-datagram-rate data content that may be indicative that at least a portion of the wireless data traffic is emanating from a UAV. The wireless data traffic may be captured from one or more Wi-Fi receivers and sorted based upon transmission parameters prior to performing the frequency spectrum analysis. Detected peak frequencies may be used to determine if any constant-datagram-rate traffic within the wireless data traffic potentially contains data traffic streaming from a UAV. Directional antennas and/or a phased array of antennas can be used to determine the direction of propagation of the wireless transmission and further classify the wireless data traffic based on potential emanation from a UAV.