Dynamic Terrain Protection Envelope Switching for Aircraft
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Solution Overview
Problem
Existing terrain awareness warning systems for aircraft lack an efficient method to dynamically select and adjust protection envelopes based on varying flight parameters, which can lead to inadequate warnings for avoiding terrain collisions.
Innovation Solution
A neural network-based algorithm is used to select the most suitable protection envelopes from predefined sets based on current flight parameters, including speed, altitude, and other dynamic factors, for both fixed-wing and rotary-wing aircraft, allowing for real-time adjustment of protection envelope dimensions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional terrain awareness warning systems use fixed protection envelopes, then the system structure is simple, but the system cannot adapt to varying flight parameters and provides inadequate warnings
Solution Approach 1:
The protection envelope dimensions are made dynamic by continuously adjusting them based on real-time flight parameters such as speed, altitude, and vertical speed. The system calculates different envelope sizes for different flight conditions, transforming a static safety margin into a dynamic adaptive protection zone that grows or shrinks according to aircraft performance characteristics.
Solution Approach 2:
The system changes the parameters defining the protection envelope (horizontal and vertical dimensions) as a function of flight parameters. By establishing mathematical relationships between flight conditions and envelope dimensions, the system automatically adjusts protection levels without requiring complex manual intervention, resolving the contradiction between adaptability and complexity.
2Measurement precision
If the system dynamically adjusts protection envelopes based on multiple flight parameters, then warning accuracy improves, but computational complexity increases
Solution Approach 1:
The protection envelope is segmented into horizontal and vertical components, each adjusted independently based on relevant flight parameters. This segmentation allows the system to handle complex multi-parameter dependencies through modular calculations, improving warning accuracy while managing computational complexity through structured problem decomposition.
Solution Approach 2:
The system pre-establishes the mathematical relationships and algorithms for calculating protection envelope dimensions based on flight parameters. By preparing the computational framework in advance with predefined adjustment rules, the system achieves high warning accuracy during operation without requiring complex real-time computations, thus balancing precision with computational efficiency.
3Reliability
If fixed protection envelopes are used, then the system is easier to operate, but it provides inadequate terrain collision warnings for different flight regimes
Solution Approach 1:
The system automatically determines the appropriate protection envelope dimensions by self-adjusting based on sensed flight parameters. The aircraft's own operational data (speed, altitude, vertical speed) directly controls the envelope configuration without requiring pilot input or manual system adjustment, thereby maintaining ease of operation while significantly improving warning effectiveness across different flight regimes.
Data Source
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Figure 2
AI summary
Apparatus for forward looking terrain avoidance (FLTA) in an aircraft, including a processor and at least one sensor, each sensor being coupled with the processor, the processor for executing at least one neural network based algorithm, the at least one sensor for monitoring a plurality of flight parameters of the aircraft thereby generating a plurality of monitored flight parameters, the processor dividing the performance envelope of the aircraft into predefined flight regimes, wherein for each predefined flight regime, the processor defining and storing a suitable protection envelope type, the processor determining an estimated flight regime of the aircraft using the neural network based algorithm based on the plurality of monitored flight parameters, and the processor selecting a respective suitable protection envelope type for the aircraft based on the estimated flight regime.