Odometry Integrity Monitoring via Solution Separation
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Solution Overview
Problem
Existing navigation systems face challenges in ensuring the integrity of odometry measurements, particularly in safety-critical applications where reliable sensor data is crucial, and current methods may not effectively detect faults or maintain performance when GNSS measurements are unavailable.
Innovation Solution
A system and method that incorporates imaging sensors with GNSS receivers and inertial measurement units, using a solution separation methodology to compute full and sub-solutions, and employing a state cloning method within a Kalman filter to determine the integrity of odometry and pseudorange measurements, ensuring reliable navigation even in GNSS-denied environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If solution separation methodology is used to monitor integrity of odometry measurements, then reliability of navigation system is improved, but device complexity increases due to multiple sensors and computational algorithms
Solution Approach 1:
The navigation system is segmented into multiple independent measurement sources (odometry from imaging sensors, pseudorange from GNSS receiver, inertial measurements from IMU) that can be individually monitored and evaluated. The solution separation methodology divides the measurement set into subsets to independently assess the integrity of each source, allowing fault isolation without requiring complete system redesign.
Solution Approach 2:
The computational device performs multiple functions: it computes navigation solutions, monitors measurement integrity, detects sensor faults, and maintains positioning accuracy across different operating conditions (GNSS-available and GNSS-denied environments). This multi-functionality is achieved through the integrated solution separation framework that handles both navigation computation and integrity monitoring within a unified system.
2Measurement precision
If multiple sensors and solution separation methodology are employed, then measurement integrity is improved, but computational requirements and processing time increase
Solution Approach 1:
The system performs preliminary integrity assessment by computing multiple independent solutions (full solution using all measurements, and sub-solutions using measurement subsets) in parallel. This preliminary computation allows early detection of measurement inconsistencies before final navigation solution is adopted, enabling proactive fault detection without delaying navigation updates.
Solution Approach 2:
The solution separation methodology computes multiple sub-solutions that use subsets of available measurements rather than requiring complete processing of all data. This partial action approach allows the system to assess integrity using only necessary measurement subsets, reducing overall computational burden while maintaining thorough integrity monitoring coverage.
3Adaptability or versatility
If odometry information from imaging sensors is integrated with GNSS measurements, then navigation performance is improved in GNSS-denied environments, but difficulty in detecting and measuring faults increases
Solution Approach 1:
The integrity monitoring system applies localized assessment to each measurement source independently. Odometry measurements from imaging sensors are evaluated separately from GNSS pseudorange measurements, with each subset subjected to its own integrity checks. This local quality approach allows the system to identify which specific measurement source contains faults, simplifying fault detection despite the diversity of sensor types.
Solution Approach 2:
The solution separation methodology acts as an intermediary framework that mediates between multiple heterogeneous measurement sources (odometry, GNSS, inertial). By introducing this intermediate assessment layer, the system can uniformly evaluate the integrity of different sensor types without requiring complex cross-sensor fault detection algorithms, thus reducing overall measurement difficulty.
Data Source
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AI summary
Systems and methods for integrity monitoring of odometry measurements within a navigation system are provided herein. In certain embodiments, a system includes imaging sensors that generate image frames from optical inputs. The system also includes a GNSS receiver that provides pseudorange measurements; and computational devices that receive the image frames and the pseudorange measurements. Further, the computational devices compute odometry information from image frames acquired at different times; and calculate a full solution for the system based on the pseudorange measurements and the odometry information. Additionally, the computational devices calculate sub-solutions for the system based on subsets of the pseudorange measurements and the odometry information, wherein one of the sub-solutions is not based on the odometry information. Moreover, the computational device determines the integrity of the pseudorange measurements, the odometry information, and a position estimated by the navigation system based on a comparison of the full and sub-solutions.