Adaptive Navigation Filter for GPS-Denied Error Accumulation
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Solution Overview
Problem
Existing navigation systems face challenges in GPS-denied environments, including error accumulation over time, high dependency on platform and sensor type, high acquisition and maintenance costs, and incompatibility with small military platforms, leading to limited usability and accuracy in military navigation applications.
Innovation Solution
The adaptive navigation system, ANAGDA, performs geo-registration fusion using a hierarchical architecture that senses and processes data from various sources, including IMU, cameras, and other sensors, to provide optimal Positioning, Navigation, and Timing (PNT) state, independent of specific sensors and platforms, allowing for seamless operation in GPS and non-GPS environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing GPS-denied navigation methods are used, then navigation capability in GPS-denied environments is provided, but error accumulation occurs over time
Solution Approach 1:
The patent combines multiple navigation methods (inertial navigation, visual navigation, terrain navigation, and GPS) into a unified adaptive filter system. This merging allows the system to leverage the strengths of each method while compensating for their individual weaknesses, particularly the error accumulation problem in GPS-denied environments by using GPS when available to reset and calibrate the other navigation methods.
Solution Approach 2:
The system dynamically adapts its navigation method based on environmental conditions and GPS availability. The adaptive filter continuously adjusts the weighting and fusion of different navigation sources in real-time, switching between GPS-dependent and GPS-independent modes as needed, thereby maintaining high accuracy while providing robust GPS-denied navigation capability.
2Reliability
If existing GPS-denied navigation methods are used, then navigation capability is provided, but size, weight, and power requirements increase
Solution Approach 1:
The adaptive filter architecture is designed to be platform-agnostic and sensor-agnostic, capable of operating on various military platforms (aircraft, ships, weapons, ground vehicles) with different sensor configurations. This universality allows small platforms to use the same navigation software without requiring heavy dedicated hardware, as the system adapts to use whatever sensors are available on each platform.
Solution Approach 2:
The system automatically selects and fuses the most appropriate navigation sources based on what is available, eliminating the need for extensive pre-mission planning and manual configuration. The adaptive filter self-adjusts to the platform's capabilities, reducing the burden on platform designers to over-provision for worst-case scenarios.
3Reliability
If existing GPS-denied navigation methods are used, then navigation capability is provided, but dependency on platform and sensor type increases
Solution Approach 1:
The adaptive filter is explicitly designed to be independent of specific sensor types and platform configurations. It can process data from inertial measurement units, cameras, LIDAR, radar, and other sensors regardless of their specific characteristics, making the navigation solution universally applicable across different military platforms without requiring platform-specific customization.
Solution Approach 2:
The system changes its operational parameters dynamically based on sensor availability and environmental conditions. The adaptive filter adjusts its fusion weights, time constants, and algorithmic behavior to match the specific sensor characteristics and data rates available on each platform, thereby achieving sensor-agnostic operation while maintaining optimal performance.
4Reliability
If existing GPS-denied navigation methods are used, then navigation capability is provided, but acquisition and maintenance costs increase
Solution Approach 1:
The software-based adaptive filter can be deployed on off-the-shelf, commercially available sensors and platforms, eliminating the need for expensive custom-built navigation systems. The system is designed to run on standard computing hardware and can be updated or replaced through software updates rather than requiring expensive hardware replacements, significantly reducing acquisition and lifecycle costs.
5Reliability
If existing GPS-denied navigation methods are used, then navigation capability is provided, but extensive pre-mission planning is required
Solution Approach 1:
The adaptive filter automatically performs sensor selection, data fusion, and navigation solution computation without requiring extensive pre-mission configuration or planning. The system self-adjusts to available sensors and environmental conditions in real-time, eliminating the need for detailed pre-mission sensor calibration and configuration that characterizes traditional GPS-denied navigation systems.
Data Source
AI summary
An adaptive navigation system for airborne, ground and dismount applications. The system performs adaptive fusion of all sensed signals, information sources, and databases that may be available on a single or multiple cooperative platforms to provide optimal Positioning, Navigation, and Timing (PNT) state. To reduce error building over time, the system incorporates the concept of geo-registration fusion into the ANAGDA filter. The architecture of the ANAGDA filter consists of user/application configurable functionalities in hierarchical layers. The sensing layer senses the environment and contains the required databases such as surveyed landmarks, and Digital Terrain Elevation Data/Digital Elevation Model (DTED/DEM). The processing layer has a Smart Sensor Resource Manager which is a performance-based sensor/feature selection module. The measurement abstraction layer isolates the filter from hardware specifics. The fusion layer performs the Inertial Measurement Unit (IMU) data integration with sensor measurements, and feature fusion.