Sliding Window Radiation Detection for Moving Sources
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Solution Overview
Problem
Existing radiation detection systems face a trade-off between accurate detection and localization of moving radiation sources, as long integration times improve detection but increase uncertainty, while short integration times enhance localization but may lead to false alarms and reduced detection performance.
Innovation Solution
Implementing a sliding window integration method that combines long and short integration times to achieve precise localization of radiation sources, where a long integration time window is applied initially, followed by a short window to track the source's movement, allowing for accurate detection and localization of moving radiation sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If long integration time is used, then detection accuracy is improved, but localization precision deteriorates
Solution Approach 1:
The patent divides the integration process into two distinct stages: a first integration period for detection and a second integration period for localization. This segmentation allows each stage to use optimized integration times - longer for detection accuracy and shorter for localization precision - thereby resolving the contradiction between the two requirements.
Solution Approach 2:
The patent dynamically adjusts the integration time based on the operational stage. The system transitions from a longer integration period during the detection phase to a shorter integration period during the localization phase, making the integration time adaptive rather than fixed, thus optimizing both detection accuracy and localization precision at different times.
2Measurement precision
If short integration time is used, then localization precision is improved, but detection performance deteriorates
Solution Approach 1:
The patent segments the operational timeline into two phases: an initial phase using short integration time for rapid localization, and a subsequent phase using longer integration time for accurate detection. This temporal segmentation ensures that localization precision is achieved without compromising overall detection performance.
Solution Approach 2:
The patent performs preliminary localization using short integration time before committing to a longer detection integration period. This preliminary action establishes the source location quickly, allowing the system to then optimize for detection accuracy in the subsequent phase without risking missed detections.
3Reliability
If long integration time is used, then false alarms are reduced, but detection time increases
Solution Approach 1:
The patent divides the detection process into two time segments: a first integration period optimized for reducing false alarms through longer averaging, and a second integration period for rapid confirmation. This segmentation reduces the overall detection time while maintaining false alarm reduction benefits.
Solution Approach 2:
The patent maintains continuous integration operations across both phases, where the second integration period overlaps or follows immediately after the first. This continuous action ensures that detection time is minimized while the cumulative effect of both integration periods maintains low false alarm rates.
Data Source
AI summary
A system includes a count detector, a communication medium; and a processor coupled to the count detector. The processor continuously receives a plurality of pulses from the count detector. A pulse indicates a detection of a radiation unit emitted from a source material or a background. The processor determines a first period of time based on an expected range of speed of a carrier of the source material, and integrates the plurality of pulses over the first period of time, thereby yielding an integrated count associated with a time at a midpoint of the first period of time. The processor creates a continuous time series of count profiles from a plurality of integrated counts that are computed using a plurality of windows within the first period of time, and shifts each window over a second period of time. The second period of time is shorter than the first period of time. The processor estimates a background count from a history of the count profiles, computes an adaptive threshold based on the estimated background count, and detects the source material when consecutives of the integrated counts exceed the adaptive threshold.