Tightly Coupled Radar Positioning for Urban Map Feedback
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Solution Overview
Problem
Traditional self-driving vehicle navigation systems face challenges in achieving accurate and reliable positioning due to errors in Inertial Measurement Units (IMU) and limitations of Global Navigation Satellite Systems (GNSS) in dense urban areas, where GNSS signals are often blocked or affected by multipath, leading to reduced accuracy and availability.
Innovation Solution
The integration of radar measurements with motion sensor data using a nonlinear state estimation technique to generate an integrated navigation solution, which updates the nonlinear measurement models and map information to provide feedback for improving map accuracy and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional IMU/GNSS integration is used for positioning, then the system can provide navigation solutions, but positioning accuracy deteriorates in dense urban areas due to GNSS signal blockage and multipath effects
Solution Approach 1:
The patent combines radar measurements with IMU data through tight coupling integration, merging two different sensing modalities (radio wave-based radar and motion-based IMU) to create a hybrid navigation system that overcomes the limitations of each individual system in urban canyons
Solution Approach 2:
Radar measurements serve as an intermediary source of environmental information that bridges the gap between IMU's relative motion tracking and the need for absolute positioning, providing independent range and velocity measurements that do not depend on GNSS satellite visibility
2Measurement precision
If GNSS signals are used for absolute positioning, then positioning does not drift over time, but signal availability deteriorates in dense urban areas due to blockage and multipath
Solution Approach 1:
The system implements feedback through the nonlinear measurement model where radar measurements continuously update and correct the IMU-derived position estimates, creating a closed-loop system that maintains positioning stability without relying on GNSS signal availability
Solution Approach 2:
The patent changes the measurement parameters from GNSS-based pseudorange and carrier phase to radar-based range and velocity measurements, fundamentally altering how positioning information is obtained to work independently of satellite signal conditions
3Reliability
If map information is used to constrain positioning, then navigation reliability improves, but map accuracy deteriorates due to errors in original data gathering and temporary changes
Solution Approach 1:
The system performs preliminary action by using radar and IMU to determine accurate current position and orientation before comparing with map information, establishing a reliable reference frame that can identify and correct map errors rather than being constrained by them
Data Source
AI summary
Feedback for map information is based on an integrated navigation solution for a device within a moving platform using obtained motion sensor data from a sensor assembly of the device, obtained radar measurements for the platform and obtained map information for an environment encompassing the platform. An integrated navigation solution is generated based at least in part on the obtained motion sensor data using a nonlinear state estimation technique that uses a nonlinear measurement model for radar measurements. The map information is assessed based at least in part on the integrated navigation solution and radar measurements so that feedback for the map information can be provided.