Tactical Imager Adaptive Tracking via Sensor Signals
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing remote sensor systems for tactical imaging face challenges such as flooding networks with raw data, generating false alarms, and having limited battery life, which affects their ability to effectively track and capture images of targets, especially small ones at a distance.
Innovation Solution
A system where sensors detect events and generate signals to adjust the imager's target tracking and recognition algorithms, allowing for adaptive image acquisition and processing based on sensor data, thereby improving the accuracy and efficiency of target tracking and reducing false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the imager uses a loose definition of motion to detect targets, then more targets are detected, but false alarms increase due to detecting moving objects like grass, trees, and dust
Solution Approach 1:
The patent introduces motion vectors as an intermediary to differentiate between legitimate targets and false alarm sources. By calculating motion vectors from sequential images and comparing them against expected target motion patterns, the system can identify whether detected motion corresponds to actual targets or environmental disturbances like blowing grass and trees
Solution Approach 2:
The system dynamically adjusts the motion detection threshold based on scene characteristics and target type. By changing the parameter of motion sensitivity, the imager can adapt to different operational conditions, reducing false alarms while maintaining target detection capability across varying environments
2Object-generated harmful factors
If the imager uses a tight definition of motion to reduce false alarms, then false alarms decrease, but targets are missed or detection range is reduced
Solution Approach 1:
The patent implements dynamic adjustment of motion detection parameters based on real-time analysis of motion vectors and scene context. The system transitions from static threshold settings to dynamic parameter adjustment, allowing the motion definition to adapt between loose and tight based on current operational needs and environmental conditions
Solution Approach 2:
The system uses feedback from motion vector analysis to continuously refine detection parameters. By analyzing the characteristics of detected motion and comparing against expected target behavior, the imager adjusts its motion definition in real-time, ensuring optimal balance between false alarm reduction and target detection
3Measurement precision
If the imager is deployed closer to the target area to capture small targets, then small targets are easier to track, but deployment flexibility and coverage area are reduced
Solution Approach 1:
The patent replaces the mechanical solution of physical proximity with an algorithmic approach using motion vectors and adaptive image processing. By substituting the need for close physical deployment with sophisticated digital signal processing and motion analysis, the system achieves small target detection capability while maintaining deployment flexibility and remote operation
4Measurement precision
If sensors continuously monitor to detect targets, then target detection capability is improved, but battery life is reduced
Solution Approach 1:
The patent implements periodic imaging triggered by sensor events rather than continuous operation. The imager remains dormant until sensors detect a potential target event, at which point it activates to capture images. This periodic action pattern significantly reduces power consumption while maintaining effective target detection capability throughout the mission duration
Solution Approach 2:
The system uses sensor data to autonomously control imager activation, creating a self-service mechanism where the detection system triggers the imaging function only when needed. This eliminates the need for continuous monitoring and manual control, optimizing the balance between detection capability and power consumption
Data Source
AI summary
Certain embodiments provide systems and methods for target image acquisition using sensor data. The system includes at least one sensor adapted to detect an event and generate a signal based at least in part on the event. The system also includes an imager obtaining an image of a target and target area based on a target tracking and recognition algorithm. The imager is configured to trigger image acquisition based at least in part on the signal from the sensor. The imager adjusts the target tracking and recognition algorithm based at least in part on sensor data in the signal. In certain embodiments, the imager may also adjust an image acquisition threshold for obtaining an image based on the sensor data.