Transmitter Probability Mapping Using Terrain and Context Fusion
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Solution Overview
Problem
Existing electromagnetic wave localization methods fail to accurately locate potentially mobile transmitters by considering the environmental context and geographical information, leading to inefficient and risky surveillance missions.
Innovation Solution
A system that generates a probability map of emitter presence by integrating multiple geographical and contextual information sources, including terrain, terrain type, and emitter relationships, using a multi-criteria approach to refine transmitter locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional localization methods using only electromagnetic signal measurements are used, then the localization process is simple, but the accuracy of transmitter location is insufficient and cannot account for environmental constraints
Solution Approach 1:
The patent merges electromagnetic signal measurements with multiple geographical and contextual information sources (terrain data, terrain type classification, emitter relationship data) to create a comprehensive probability map. This combination allows the system to account for environmental constraints while determining transmitter locations, thereby improving measurement precision without requiring a complete redesign of the localization system.
Solution Approach 2:
The patent introduces a probability map as an intermediary representation that synthesizes information from multiple sources. This probability map serves as a mediator between raw signal measurements and final location determination, allowing the system to incorporate environmental constraints and contextual information while maintaining a structured approach to localization.
2Productivity
If the search area is defined without considering geographical context, then the search process is straightforward, but the search time increases and mission risk increases
Solution Approach 1:
The patent performs preliminary analysis by generating a probability map that incorporates terrain data, terrain type classification, and emitter relationship information before conducting the actual search. This preliminary action identifies high-probability zones in advance, allowing operators to focus search efforts on the most likely locations and significantly reducing the time required to locate transmitters.
Solution Approach 2:
The patent applies different levels of probability weighting to different geographical areas based on local characteristics such as terrain type and proximity to known emitters. Instead of treating the entire search area uniformly, the system identifies and focuses resources on specific high-probability zones, thereby improving search efficiency and reducing overall search time.
3Measurement precision
If uncertainty is represented by a simple ellipse, then the representation is simple, but it cannot accurately represent complex threat zones with varying probability distributions
Solution Approach 1:
The patent transitions from representing uncertainty in two dimensions (an ellipse in the spatial plane) to representing uncertainty across multiple dimensions by creating a probability map with varying probability values at different locations. This dimensional expansion allows the system to capture complex probability distributions and environmental constraints that cannot be represented by a simple geometric shape.
Solution Approach 2:
The patent segments the search area into multiple discrete zones with different probability values based on geographical and contextual information. Instead of using a single continuous ellipse, the system divides the area into grid cells or regions, each with its own probability of containing a transmitter, allowing for more accurate representation of complex uncertainty patterns.
Data Source
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AI summary
Computer-implemented method for generating a probability map for the presence of a transmitter, the method comprising the steps of: Determining (101, 104) at least one first probability map for the presence of a transmitter of a first type taken from among: A location map for a transmitter, obtained by a location sensor, A location map for a transmitter with knowledge of the location of at least one other transmitter, obtained from a priori inter-transmitter proximity information, Determining (101, 102, 103, 104) at least one second probability map for the presence of a transmitter of a second type taken from among: A location map for a transmitter based on the relief of a region, A location map for a transmitter based on a semantic cartography of a region, A location map for a transmitter of the first type, Fusing (105) at least one first probability map for the presence of a transmitter of the first type with at least one second probability map for a transmitter of the different, second type.