Vehicle Environmental Display Sensor Fusion
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Solution Overview
Problem
Conventional radar imaging systems lack elevation angle measurement, failing to provide accurate three-dimensional views of the environment, and existing technologies like lidar struggle with visibility in adverse conditions, limiting pilots' situational awareness, especially in low-light or dusty environments.
Innovation Solution
A real-time imaging system that aggregates pre-existing database data with real-time sensor data from 3-D sensors like radar and lidar, and 2-D cameras to create a synthetic image, using a multi-resolution 3-D data structure for enhanced situational awareness, allowing for quick reactions in dynamic environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional radar imaging systems are used, then navigation and surveillance functions are provided, but elevation angle measurement is lacking and three-dimensional views cannot be achieved
Solution Approach 1:
The patent combines radar and lidar data fusion to achieve three-dimensional environmental mapping. The system integrates radar's all-weather capability with lidar's precise range and elevation measurements, merging multiple data sources to overcome the limitations of conventional radar alone and provide accurate 3D views without requiring a single complex sensor system.
Solution Approach 2:
The imaging system performs multiple functions including navigation, surveillance, target tracking, identification, and three-dimensional environmental mapping. By designing a system that can execute diverse operations across different operational conditions, the patent achieves multi-functionality that addresses various measurement needs without requiring separate specialized systems.
2Measurement precision
If lidar is used for high-resolution imaging, then detailed scene information is obtained, but visibility is lost in dust storms and adverse conditions
Solution Approach 1:
The patent uses radar data as an intermediary to complement lidar measurements. When lidar visibility is degraded by dust or adverse conditions, radar provides all-weather detection capability that penetrates obscurants. The system fuses these intermediate data sources, allowing the lidar-high-resolution system to maintain reliability by falling back on radar's penetrating capability when needed.
Solution Approach 2:
The imaging system functions as a composite sensing system that integrates radar and lidar data. Similar to composite materials combining different properties, this composite sensing approach merges radar's all-weather penetration with lidar's high-resolution capability, creating a system that maintains both resolution and reliability across varying environmental conditions.
3Loss of information
If multiple data sources are aggregated in real-time, then comprehensive situational awareness is achieved, but data processing complexity increases
Solution Approach 1:
The patent segments the data fusion process into distinct functional modules: radar data processing, lidar data processing, data registration, and scene rendering. By dividing the complex aggregation task into manageable segments that can be processed independently and then integrated, the system achieves comprehensive situational awareness while controlling processing complexity through modular architecture.
4Ease of operation
If conventional top-down radar perspective is used, then plan view navigation is provided, but pilot's perspective view from different angles is not available
Solution Approach 1:
The patent transforms the conventional two-dimensional top-down radar perspective into three-dimensional views by integrating elevation data from lidar and radar range measurements. This dimensional transformation allows the system to render images from multiple perspectives including the pilot's forward view, side views, and other angular perspectives, providing adaptability across different viewing requirements while maintaining navigation utility.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides a comprehensive, real-time, three-dimensional view of the environment, improving situational awareness by integrating data from various sources, enhancing pilot reaction times and accuracy in adverse conditions.
Implementation Method 1
radar imagery is conventionally accomplished by a two-dimensional scan (range and azimuth)
Implementation Method 2
laser radar (typically referred to as 'lidar,' 'LiDAR,' or 'LIDAR), which employs a laser to determine distances to a target
Data Source
AI summary
An imaging system for a moving vehicle aggregates pre-existing data with sensor data to provide an image of the surrounding environment in real-time. The pre-existing data are combined with data from one or more 3-D sensors, and 2-D information from a camera, to create a scene model that is rendered for display. The system accepts data from a 3-D sensor, transforms the data into a 3-D data structure, fuses the pre-existing scene data with the 3-D data structure and 2-D image data from a 2-D sensor to create a combined scene model, and renders the combined scene model for display. The system may also weight aspects of data from first and second sensors to select at least one aspect from the first sensor and another aspect from the second sensor; wherein fusing the pre-existing scene data with the sensor data uses the selected aspect from the first sensor and the selected aspect from the second sensor.