Adaptive TERCOM Navigation Reference Basket Array
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Solution Overview
Problem
Traditional TERCOM navigation systems face processor loading delays and inefficiencies due to batch processing of altitude samples, requiring pre-programmed flight plans based on terrain type, which limits real-time course correction capabilities.
Innovation Solution
The system dynamically correlates aircraft sample points with a reference basket array, adjusting its size based on uncertainty estimates, and iteratively improves correlation quality until a predetermined threshold is met, allowing for real-time position error calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the traditional TERCOM navigation system batches processes the entire sequence of altitude samples at once to calculate position error, then the position error can be determined, but significant processor loading occurs and a delay of 2-3 seconds happens before the position error estimate is available
Solution Approach 1:
The patent divides the batch processing of altitude samples into incremental updates. Instead of processing the entire sequence at once, the system processes samples as they are collected, updating the position error estimate incrementally. This segmentation allows the system to provide position error estimates continuously rather than waiting for the complete batch, reducing the delay from 2-3 seconds to near-real-time updates while maintaining determination accuracy.
Solution Approach 2:
The system performs preliminary correlation setup and reference map preparation before actual navigation use. The reference map is pre-processed and stored in an optimized format, and correlation parameters are pre-configured based on expected terrain characteristics. This preliminary action reduces the computational burden during real-time operation, allowing faster position error estimation without sacrificing precision.
2Reliability
If the reference map is made large to cover potential position error areas, then the correlation algorithm can converge on a best fit solution even with larger expected errors, but the correlation algorithm wastes time and processor resources calculating best fit solutions for irrelevant terrain areas
Solution Approach 1:
The patent applies local quality by making the reference map dynamically adaptable to local terrain characteristics and expected position accuracy. Instead of using a uniformly large reference map, the system adjusts the reference map size and scope based on local factors such as terrain complexity, expected navigation accuracy, and confidence in the inertial navigation system. This allows the correlation algorithm to focus computational resources on relevant terrain areas only, improving efficiency while maintaining reliability for convergence.
Solution Approach 2:
The reference map size and scope are made dynamic rather than static. The system adjusts the reference map dimensions based on real-time factors including expected position error from the inertial navigation system, terrain slope variation, and correlation progress. This dynamic adjustment ensures the reference map is large enough to guarantee convergence but not so large as to waste processor resources on irrelevant areas, optimizing both reliability and productivity.
3Productivity
If the reference map size is reduced to minimize processor resource usage, then calculation time is reduced, but the correlation algorithm may not converge on a best fit solution
Solution Approach 1:
The system implements feedback mechanisms that monitor correlation progress and quality during the matching process. As the correlation algorithm processes the reference map, it continuously evaluates whether a satisfactory best fit solution is being achieved. This feedback allows the system to dynamically adjust the reference map size during computation - expanding it if convergence is not occurring and reducing it if a good solution is found. This ensures productivity is maximized while reliability of convergence is maintained through real-time monitoring and adjustment.
Data Source
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AI summary
Systems and methods for terrain contour matching navigation are provided. In one embodiment, a method for terrain contour matching navigation comprises: receiving at least one sample point representing the position of an aircraft, the at least one sample point including a horizontal position and an altitude sample; correlating a first sample point of the at least one sample point across a reference basket array having a plurality of elements; determining a correlation quality; when the correlation quality does not achieve a pre-determined quality threshold, performing at least one additional correlation of an additional sample point of the at least one sample point across the reference basket array; and when the correlation quality does achieve a pre-determined quality threshold, calculating a position error based on the correlating of the first sample point and any additional correlations of any additional sample points.