Automated Multisensor Data Fusion for ISR Platforms
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current ISR data fusion systems require extensive human intervention for sensor data analysis, leading to inefficiencies and errors due to the sheer volume of data and the need for expert interpretation across multiple sensor technologies, resulting in lower detection accuracy and higher false alarm rates.
Innovation Solution
A system that automates the fusion of data from multiple sensors using computational methods and software, reducing human operator involvement by calculating and combining detection probabilities across different sensor modalities, such as SAR and hyperspectral data, to provide a unified and normalized output for decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data from multiple sensors are combined to improve detection performance, then detection accuracy improves, but system complexity increases
Solution Approach 1:
The patent segments the complex data fusion problem into distinct processing stages: data collection from multiple sensors, data pre-processing and registration, feature extraction, data association, and fusion decision-making. Each stage handles specific tasks independently, making the overall complex system manageable and implementable while maintaining high detection accuracy through coordinated multi-sensor data processing
Solution Approach 2:
The patent introduces intermediary components such as data association algorithms and feature extraction modules that act as mediators between raw sensor data and final detection results. These intermediaries transform heterogeneous sensor data into standardized formats, enabling effective fusion while reducing the complexity of direct multi-sensor integration
2Measurement precision
If extensive human intervention is used for sensor data analysis, then interpretation accuracy improves, but productivity decreases
Solution Approach 1:
The patent implements self-service mechanisms through automated data fusion algorithms that independently perform data collection, processing, association, and analysis without requiring continuous human intervention. The system autonomously evaluates detection results and generates reports, significantly improving productivity while maintaining interpretation accuracy through sophisticated algorithmic processing
Solution Approach 2:
The patent replaces manual human analysis (mechanical system) with automated computational algorithms. The data fusion system uses computer-based processing to perform tasks previously requiring human analysts, including data registration, feature extraction, and detection decision-making, thereby dramatically increasing analysis efficiency while preserving accuracy through consistent algorithmic application
3Reliability
If the volume of sensor data increases to detect difficult targets, then detection capability improves, but false alarm rate increases
Solution Approach 1:
The patent incorporates feedback mechanisms where detection results and performance metrics are continuously evaluated and used to adjust data association parameters and fusion algorithms. The system learns from past detections and false alarms, dynamically optimizing the balance between detection capability and false alarm rate based on actual operational performance and environmental conditions
Solution Approach 2:
The patent dynamically changes processing parameters such as detection thresholds, association gates, and fusion weights based on target characteristics, environmental conditions, and sensor performance. By adapting these parameters in real-time, the system maintains high detection capability for difficult targets while adjusting sensitivity to minimize false alarm rates in different operational scenarios
Data Source
AI summary
The present invention encompasses a physical or virtual, computational, analysis, fusion and correlation system that can automatically, systematically and independently analyze collected sensor data (upstream) aboard or streaming from aerial vehicles and/or other fixed or mobile single or multi-sensor platforms. The resultant data is fused and presented locally, remotely or at ground stations in near real time, as it is collected from local and/or remote sensors. The invention improves detection and reduces false detections compared to existing systems using portable apparatus or cloud based computation and capabilities designed to reduce the role of the human operator in the review, fusion and analysis of cross modality sensor data collected from ISR (Intelligence, Surveillance and Reconnaissance) aerial vehicles or other fixed and mobile ISR platforms. The invention replaces human sensor data analysts with hardware and software providing two significant advantages over the current manual methods.