Autonomous Range-Only Terrain Navigation
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Solution Overview
Problem
Existing terrain-aided navigation systems, such as TERCOM, require labor-intensive mission-specific map preparation, are constrained to straight flight paths, and suffer from false correlations due to the assumption that the first return from a conventional radar altimeter is directly below the vehicle, limiting flexibility and accuracy.
Innovation Solution
Autonomous Range-Only Terrain Aided Navigation (AROTAN) uses a generic terrain height database independent of flight path, aligns a dynamic search space to vehicle uncertainty, and performs continuous correlation with range-only measurements from a conventional radar altimeter, allowing for precise navigation without pre-planned maps or external signals like GPS.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional radar altimeter first return is assumed to be directly below the vehicle, then the navigation system can be simplified, but false correlations occur and accuracy deteriorates
Solution Approach 1:
The patent introduces an intermediary computational model that accounts for radar beam geometry and terrain interaction. Instead of directly assuming the first return is below the vehicle, the system uses a radar altimeter model to compute the actual terrain intersection point, serving as a mediator between the simple range measurement and the accurate position determination.
Solution Approach 2:
The system changes the parameter representation from simple vertical height to a more complex geometric relationship involving beam angle, range, and terrain slope. By transforming the problem parameters to include these additional geometric factors, the system resolves the contradiction between simplicity and accuracy.
2Ease of manufacture
If mission-specific terrain maps are prepared in advance with fixed grid alignment, then correlation processing is simplified, but flexibility and adaptability deteriorate
Solution Approach 1:
The patent implements dynamic grid alignment that adapts to the actual flight path and vehicle orientation. Instead of using fixed pre-planned grid orientations, the system dynamically rotates and positions the correlation grid based on real-time flight data, allowing the same system to adapt to different missions without re-preparing maps.
Solution Approach 2:
The system creates a universal terrain database structure that can serve multiple mission types. By separating the terrain data storage from the mission-specific correlation parameters, the same terrain database can be used for various flight paths, orientations, and vehicle types, eliminating the need for mission-specific map preparation.
3Measurement precision
If terrain database cells are spaced to match measurement spacing at a particular vehicle speed, then correlation accuracy is improved, but the system becomes constrained to that speed and spacing
Solution Approach 1:
The system dynamically adjusts the correlation grid spacing and sampling rate based on the actual vehicle speed and measurement rate. Instead of using fixed grid spacing, the system resamples the terrain database on-the-fly to match the current measurement density, maintaining correlation accuracy across varying speeds.
Solution Approach 2:
The patent changes the correlation parameters dynamically based on vehicle speed and measurement rate. By adjusting grid spacing, sampling intervals, and correlation window size as functions of these parameters, the system maintains optimal performance across different operating conditions without being constrained to a single speed.
4Device complexity
If the search space is kept constant over the measurement history, then processing complexity is reduced, but accuracy deteriorates when initial position uncertainty is large
Solution Approach 1:
The system implements a dynamic search space that evolves over the measurement history. Starting with a large search space to accommodate initial position uncertainty, the system progressively reduces and refines the search space as more measurements are collected and position uncertainty decreases, optimizing both accuracy and computational efficiency.
Solution Approach 2:
The patent performs preliminary correlation searches over a broad search space to identify candidate regions, then performs refined searches in those regions. This two-stage approach allows the system to handle large initial uncertainties by first establishing a rough position estimate, then improving precision with focused processing.
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
AROTAN enables quick and continuous navigation corrections over varying terrain, applicable to a broader range of airborne vehicles, including small ones, without the need for multiple antennas or boresight calibration, and provides accurate position fixes in all weather conditions.
Implementation Method 1
uses a conventional radar altimeter
Data Source
AI summary
AROTAN provides for autonomous terrain aided navigation that is fully independent of the position uncertainty of the vehicle during flight. AROTAN aligns a grid to the search space and periodically updates the search space during the measurement history to account for growth in position uncertainty. AROTAN computes terrain sufficiency statistics for a moving history to provide robust criteria for when to perform the correlation. A post-correlation refinement provides an additional correction of the horizontal position error and a correction of the altitude. AROTAN can quickly provide the vehicle's location based on the correlation from a single measurement history.