Multi-Sensor Inferred Location Filtering for GPS Spoof Detection
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Solution Overview
Problem
Vehicles, particularly smaller platforms and autonomous systems, are vulnerable to GPS spoofing attacks, which disrupt navigation and mission execution in contested environments.
Innovation Solution
A system combining data from non-positional sensors like IMUs and RSSI to infer a device's location and confidence level, using a Kalman filter to integrate location information and detect spoofing, enabling navigation control based on inferred location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS satellite-based signals are used to determine vehicle position, then navigation capability is provided, but the system becomes vulnerable to spoofing attacks that corrupt position integrity
Solution Approach 1:
The patent introduces an intermediary system consisting of multiple sensors (IMU, barometer, camera, GPS receiver) and a processor that mediates between the vulnerable GPS signals and the navigation system. The processor fuses data from multiple sources to produce a more reliable position estimate, filtering out spoofed GPS signals through cross-validation with other sensor data.
Solution Approach 2:
The patent merges multiple independent sensing systems (inertial measurement, barometric pressure, visual recognition, and GPS) into a unified navigation system. By combining these diverse sensors, the system creates redundancy that makes it resistant to spoofing attacks on any single sensor, particularly GPS, while maintaining reliable position determination.
2Reliability
If multiple sensors are combined to determine position, then spoofing detection capability is improved, but device complexity increases
Solution Approach 1:
The patent implements a processor that performs multiple functions: it processes data from various sensors, fuses the data using filtering algorithms, detects spoofing conditions, and controls navigation. This multi-functional approach consolidates complexity into a single processing unit rather than requiring separate dedicated systems for each function.
Solution Approach 2:
The system uses its own multiple sensors to self-validate position information. The IMU, barometer, camera, and GPS work together to互相 verify each other's data, with the system automatically detecting inconsistencies that indicate spoofing without requiring external validation systems.
Data Source
AI summary
A device includes two or more sensors. The device also includes one or more processors coupled to a memory and configured to obtain first sensor data from a first sensor of the two or more sensors and obtain second sensor data from a second sensor of the two or more sensors. The processors are further configured to determine a first position estimate of the device based on the first sensor data and determine a second position estimate of the device based on the second sensor data. The processors are further configured to provide input data based on the first position estimate and the second position estimate to a filter to determine an inferred location of the device and a confidence value associated with the inferred location. The processors are further configured to control navigation of the device based, at least in part, on the inferred location.