Surface Penetrating Radar Vehicle Localization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current autonomous navigation systems face challenges in maintaining precise vehicle location within a lane, especially in variable environments due to limitations in GPS accuracy and sensitivity to weather conditions, illumination changes, and dynamic scene elements, which affects the robustness of map-based localization methods.
Innovation Solution
The use of surface penetrating radar (SPR) to acquire and compare images of subsurface regions along a vehicle track with previously acquired images, determining location data for precise vehicle guidance and navigation, employing a mobile SPR system with a radar processor and registration module to generate control signals for vehicle movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS receivers are used to provide global localization, then the system can obtain location information, but the precision is insufficient to stay within a lane of traffic and accuracy degrades in environments with multipath or shadowing
Solution Approach 1:
The patent introduces surface penetrating radar as an intermediary measurement system between the vehicle and the environment. Instead of relying directly on GPS signals that are blocked or degraded by environmental factors, the radar penetrates the ground surface to detect subsurface features, serving as a mediator that provides location information independent of atmospheric conditions and signal blockage
Solution Approach 2:
The patent replaces the electromagnetic wave-based GPS system with a radar-based subsurface detection system. By substituting the measurement mechanism from satellite-based electromagnetic signals to ground-penetrating electromagnetic waves, the system achieves immunity to multipath effects and signal shadowing while maintaining location determination capability
2Ease of manufacture
If passive visual methods are used for map-matching localization, then the system can operate without additional infrastructure, but performance deteriorates due to changes in scene illumination
Solution Approach 1:
The patent changes the measurement parameter from optical intensity (affected by illumination) to radar reflectivity (affected by subsurface material properties). By transitioning from measuring light intensity to measuring radar wave reflection from subsurface features, the system maintains operational simplicity while achieving illumination-invariant localization accuracy
Solution Approach 2:
The patent moves the measurement from the surface optical dimension to the subsurface radar dimension. Instead of analyzing surface visual features that vary with lighting, the system probes the subsurface dimension where material properties remain constant regardless of illumination conditions, providing stable localization references
3Measurement precision
If active sensors such as LIDAR are used for sensing, then the problem of inconsistent scene illumination is solved, but the systems require expensive precision-engineered electro-optical-mechanical systems
Solution Approach 1:
The patent employs radar technology that is less expensive and less complex than precision-engineered LIDAR systems. By using readily available radar components rather than expensive electro-optical-mechanical systems, the patent achieves comparable or superior localization accuracy while reducing device complexity and cost
Solution Approach 2:
The patent replaces complex electro-optical-mechanical LIDAR systems with a simpler radar-based system. By substituting the sensing mechanism from optical ranging to radar imaging, the system eliminates the need for precision mechanical scanning components while maintaining active sensing capabilities and localization accuracy
4Ease of manufacture
If visual sensing methods are used, then the system can operate without additional infrastructure, but performance is impacted by weather conditions such as snow, fog, rain and dust
Solution Approach 1:
The patent introduces subsurface radar detection as an intermediary measurement approach that bypasses atmospheric conditions. Instead of directly sensing surface features through the atmosphere (which is blocked by weather), the radar waves penetrate the ground surface to detect subsurface features, using the earth itself as a mediator that is immune to weather effects
Solution Approach 2:
The patent transitions from surface-level optical sensing to subsurface radar sensing. By moving the measurement domain from the atmospheric surface layer (affected by weather) to the subsurface layer (protected from weather), the system maintains operational simplicity while achieving weather-independent reliability
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method provides accurate vehicle localization to within 2 cm rms, enabling precise lane maintenance and robust navigation in various weather conditions and dynamic environments without requiring environmental modifications, and can be applied to diverse vehicle types and terrains.
Implementation Method 1
acquiring surface penetrating radar (SPR) images of a subsurface region
Implementation Method 2
a mobile SPR system having an array of antenna elements each configured to transmit a radar signal into a subsurface region and to receive a return radar signal from the subsurface region
Data Source
AI summary
Described are a method and a system for localization of a vehicle. The method includes the acquisition of SPR images of a subsurface region along a vehicle track. Acquired SPR images are compared to SPR images previously acquired for a subsurface region that at least partially overlaps the subsurface region along the vehicle track. In some embodiments, the comparison includes an image correlation procedure. Location data for the vehicle are determined based in part on location data for the SPR images previously acquired for the second subsurface region. Location data can be used to guide the vehicle along a desired path. The relatively static nature of features in the subsurface region provides the method with advantages over other sensor-based navigation systems that may be adversely affected by weather conditions, dynamic features and time-varying illumination. The method can be used in a variety of applications, including self-driving automobiles and autonomous platforms.