Moving Object Location Estimation Using Intensity Pattern Matching
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Solution Overview
Problem
Existing location estimation systems for autonomous moving objects within predetermined regions face challenges in accurately determining the location of these objects due to limitations in detecting and interpreting environmental data, particularly in complex or dynamic geographic boundaries.
Innovation Solution
The system employs a location estimation apparatus integrated with detection sections that obtain intensity and distance information, which are used to determine intensity patterns along the moving path, allowing for subarea determination and precise location estimation within the target region, utilizing a combination of hardware and software components for data processing and communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS signal-based positioning is used for autonomous moving objects, then location information can be obtained, but measurement precision deteriorates in complex or dynamic geographic boundaries where GPS signals are limited or unavailable
Solution Approach 1:
The patent divides the target region into multiple subareas with different geographic boundary characteristics. GPS-based positioning is used in open areas where signals are reliable, while sensor-based intensity pattern matching is used in complex regions with dynamic boundaries. This segmentation allows the system to select the appropriate positioning method based on the local environment, thereby maintaining high measurement precision and reliability across all regions.
Solution Approach 2:
The patent introduces an intermediary system that combines GPS positioning with sensor-based intensity pattern matching. When GPS signals are unavailable or unreliable in complex regions, the system uses detection sections to measure environmental intensities (such as electromagnetic, acoustic, or optical fields) and matches these patterns against pre-stored maps to determine location. This intermediary approach bridges the gap where GPS alone fails, improving both precision and reliability.
2Measurement precision
If sensor-based intensity pattern matching is used to improve location accuracy in complex regions, then measurement precision improves, but device complexity increases due to additional detection sections and data processing requirements
Solution Approach 1:
The patent designs detection sections with multi-functionality that can measure various types of environmental intensities (electromagnetic, acoustic, optical, etc.) depending on the application scenario. The same basic detection hardware can be configured for different sensing modalities, reducing the need for separate specialized devices for each type of intensity measurement. This universality improves location precision across diverse environments while controlling device complexity through shared components.
Solution Approach 2:
The system performs preliminary actions by pre-measuring and storing intensity patterns for multiple subareas during a mapping phase before actual navigation begins. During operation, the detection sections only need to measure current intensities and match them against the pre-stored patterns, rather than performing complex real-time calculations. This preliminary preparation reduces the computational burden during active use, improving location precision while managing device complexity.
3Measurement precision
If multiple detection sections are deployed to cover complex regions, then location estimation accuracy improves, but use of energy increases due to additional sensors and continuous measurement requirements
Solution Approach 1:
The patent implements periodic measurement cycles where detection sections take intensity measurements at predetermined time intervals rather than continuously. The system determines whether a measurement is necessary based on factors such as changes in moving object speed, transitions between different types of regions (open vs. complex), or deviations from expected trajectories. This periodic approach maintains location estimation accuracy by capturing relevant environmental changes while significantly reducing energy consumption compared to continuous monitoring.
Solution Approach 2:
The system applies partial measurement action by selectively activating only the detection sections and measurement modes needed for the current operational context. In open regions where GPS is reliable, the system uses minimal sensing. In complex regions, it activates appropriate detection sections. The system also adjusts measurement frequency and intensity based on whether the moving object is in a critical positioning zone or a well-understood area, thereby maintaining accuracy where needed while reducing energy use in less critical situations.
Data Source
AI summary
It includes an intensity pattern determination section to determine an intensity pattern indicating a distribution of a magnitude of a target quantity in at least a part of a moving path of the moving object, a subarea determination section to determine, among a plurality of subareas, one or more subareas having an intensity pattern which matches or is similar to an intensity pattern determined by the intensity pattern determination section based on map information which associates area identification information which identifies each of a plurality of subareas included in a target region having a predetermined geographic range and an intensity parameter indicating a magnitude of a target quantity premeasured in the subarea, and an output section to output, as a location of the moving object, one or more subareas determined by the subarea determination section.