Self-Position Measuring Device Using Inertial Reference Points
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Solution Overview
Problem
Current self-position measurement techniques for movable bodies, such as UAVs, face challenges when GPS signals are deceived or jammed, leading to inaccurate position recognition and potential crashes, and existing methods like geonavigation and celonavigation require extensive database checks, increasing calculation load and processing time.
Innovation Solution
A self-position measuring device equipped with an inertial navigation unit, a database of geographic and celestial information, and a navigation method selector that estimates the vehicle's region, generates reference points, and selects the navigation method with the least error by comparing ground and celestial information against estimated data, allowing for accurate position measurement without relying on external signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If geonavigation or celonavigation is used for self-position measurement without GPS, then reliability is improved by not depending on external signals that can be deceived or jammed, but device complexity increases and calculation load increases due to extensive database checks
Solution Approach 1:
The patent divides the continuous search space into discrete reference points based on inertial navigation position. The existing region is segmented into multiple reference points, and database checks are performed only at these specific points rather than continuously across the entire region, reducing calculation load while maintaining reliability.
Solution Approach 2:
The patent performs preliminary estimation of the existing region using inertial navigation before conducting detailed database checks. By pre-defining the search area and generating reference points in advance, the system reduces the subsequent calculation burden when performing geonavigation or celonavigation database comparisons.
2Reliability
If geonavigation or celonavigation is used for self-position measurement without GPS, then reliability is improved by not depending on external signals that can be deceived or jammed, but processing time increases due to extensive database checks
Solution Approach 1:
The patent segments the database checking process to occur only at discrete reference points rather than continuously. By dividing the existing region into specific reference points and performing checks only at these locations, the processing time is significantly reduced while maintaining accurate position determination.
Solution Approach 2:
The patent performs database checks at multiple reference points (excessive action) rather than at every possible location (full action). This partial sampling approach provides sufficient accuracy for position determination while dramatically reducing the total processing time required compared to exhaustive database searching.
3Measurement precision
If multiple reference points are generated by dividing the existing region, then measurement precision is improved by enabling selection of the navigation method with the lowest error, but device complexity increases due to additional processing steps
Solution Approach 1:
The patent uses feedback by comparing database information at multiple reference points with actual sensor data to determine which reference point provides the best match. This feedback mechanism enables selection of the navigation method (geonavigation or celonavigation) that yields the lowest error, improving measurement precision while managing complexity through systematic comparison.
Data Source
AI summary
A self-position measuring device includes an information generator, a position extractor, and a navigation method selector. The information generator generates estimated information that is expected to be obtained when at least one of the ground information and the celestial information is obtained, at each of multiple reference points generated on the basis of measured inertial navigation position. The position extractor checks at least the one of the ground information and the celestial information against the estimated information at each of the multiple reference points and extracts a position of a specific reference point corresponding to specific estimated information with a highest matching degree. The navigation method selector selects, on the basis of the specific reference point, a navigation method with less navigational error as a navigation method for measuring the self-position.