Aircraft Obstacle Sensor Data Filtering
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Solution Overview
Problem
Current obstacle detection systems in aircraft face challenges with high-performance LIDAR sensors that generate a large number of points, including irrelevant data, overwhelming pilots and making it difficult to quickly identify real dangers amidst numerous obstacle points.
Innovation Solution
A method that filters out irrelevant obstacle points by defining a detection volume and using an algorithm to aggregate and reposition measurements over time, retaining only relevant points that pose a real danger for display, allowing for a simpler and more intelligible representation of the aircraft's environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If a high-performance LIDAR obstacle sensor is used to detect obstacles at long distances with a wide angular field, then the detection range and angular coverage are improved, but the number of detected obstacle points increases significantly, making data processing more difficult and overwhelming the display system
Solution Approach 1:
The patent divides the surrounding space into multiple detection zones (first detection zone closer to aircraft, second detection zone farther away) and applies different filtering criteria to each zone. This segmentation allows the system to process and prioritize obstacle points based on their distance and relevance to the aircraft, reducing the overall processing complexity while maintaining comprehensive coverage.
Solution Approach 2:
The patent extracts and displays only the most relevant obstacle points based on predefined criteria (distance thresholds, angular fields, and zone-specific filters). By taking out only the critical obstacle information from the large set of detected points, the system reduces data processing complexity and prevents display overload while maintaining safety.
2Loss of information
If all detected obstacle points are displayed to provide complete information, then the information completeness is improved, but the pilot's ability to quickly identify real dangers is reduced due to information overload
Solution Approach 1:
The patent applies different display priorities and visual characteristics to obstacle points based on their location and relevance. Obstacle points in the first detection zone (closer to aircraft) are displayed with higher priority than those in the second zone. This local quality differentiation helps pilots quickly identify critical threats while maintaining information about less urgent obstacles.
Solution Approach 2:
The system extracts and prioritizes display of obstacle points that meet specific relevance criteria, filtering out less critical information. This selective extraction maintains essential safety information while reducing the overall display complexity, allowing pilots to focus on immediate threats without complete information loss.
3Volume of moving object
If multiple obstacle sensors are used to compensate for limited scanning range, then the angular coverage is improved, but the system mass increases
Solution Approach 1:
The patent employs dynamic filtering and aggregation algorithms that adapt to aircraft attitude changes (roll and pitch). When the aircraft rotates, the system dynamically adjusts the detection volume orientation and repositions obstacle points accordingly. This dynamic adaptation allows a single sensor to maintain effective coverage despite attitude changes, eliminating the need for multiple sensors.
Solution Approach 2:
The system changes the parameters of the detection volume (orientation, position, and boundaries) based on aircraft attitude and flight conditions. By adjusting these parameters dynamically, a single LIDAR sensor can effectively cover the required angular field regardless of aircraft orientation, avoiding the need to add more sensors and increase system mass.
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
This approach significantly reduces the complexity of data for pilots, enhancing their ability to quickly understand and respond to actual threats by focusing on relevant obstacle points within a defined safety volume, thereby improving flight safety and reducing workload.
Implementation Method 1
the obstacle sensor may include an obstacle sensor of the type known by the acronym LIDAR and the English expression 'Llght Detection And Ranging'
Data Source
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AI summary
The present invention relates to a method for detecting obstacles (60) in the vicinity of an aircraft (1). This method comprises the following steps: - scanning a surrounding space (70) using an obstacle sensor (15), said obstacle sensor (15) generating positioning data relating to a plurality of obstacle points (75); determination, among said obstacle points (75), of each relevant point (80) located within a predetermined detection volume (85), the detection volume (85) being different from said surrounding space (70); displaying said relevant points (80) on a display.