Masking Detection in Radar Devices Using Subrange Reference Functions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing detection systems fail to promptly identify masking situations caused by opaque objects, leading to incomplete or inaccurate detection of targets, which can result in false alarms or missed dangerous conditions in both intrusion and industrial applications.
Innovation Solution
A method that generates and compares electromagnetic detection profiles within a specific subrange of the field of view, using a reference function to detect significant deviations and incorporating convergence analysis and time derivative calculations to differentiate between masking and non-masking conditions, while also removing background profiles to identify moving objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the device monitors the entire field of view, then target detection coverage is improved, but the complexity of detecting masking increases
Solution Approach 1:
The field of view is segmented into a subrange (near field, 0.5-2 meters from the device) and a far range. Masking detection is specifically performed in the subrange where masking objects typically appear, while target detection covers the entire field of view. This segmentation allows the system to monitor for masking without having to analyze the entire field of view continuously, reducing computational complexity while maintaining reliable detection coverage.
2Measurement precision
If the device generates alarm signals for any detection profile deviation, then masking detection sensitivity is improved, but false alarm rate increases
Solution Approach 1:
The system dynamically adjusts the reference function based on environmental conditions and operational state. The reference function is updated periodically or when significant environmental changes are detected, allowing the system to adapt to changing conditions such as weather, lighting, and background objects. This dynamic adjustment maintains high masking detection sensitivity while reducing false alarms caused by environmental variations.
Solution Approach 2:
The system employs feedback mechanisms where detection results are fed back to adjust the reference function and detection parameters. When masking is detected or environmental changes are observed, the system learns from these patterns and adjusts its sensitivity thresholds accordingly, improving both detection accuracy and false alarm reduction over time.
3Adaptability or versatility
If the device updates the reference function frequently, then adaptation to environmental changes is improved, but detection stability deteriorates
Solution Approach 1:
The reference function is updated periodically at predetermined intervals rather than continuously or too frequently. This periodic update strategy allows the system to adapt to environmental changes over time while maintaining stability during normal operation. The system balances adaptability by updating the reference function regularly to reflect environmental changes while avoiding excessive updates that would introduce noise and reduce detection stability.
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
Effectively detects masking states, reducing false alarms and ensuring accurate target detection by distinguishing between masking and non-masking conditions, even in the presence of environmental changes like rain, and recognizing new stationary objects in the environment.
Implementation Method 1
radar systems, can transmit an electromagnetic signal into an environment to be monitored and receive a signal reflected from the objects to identify their position
Implementation Method 2
generating and receiving electromagnetic signals, from which a detection profile is obtained
Data Source
AI summary
Herein disclosed is a method of detecting a masking state of a device for detecting a target in an environment, which generates transmission signals, such as radio signals, and receives reception signals in a field of view. The field of view extends from a minimum distance to a maximum distance. The method provides a signal amplitude reference function over distance from the device in a subrange of the field of view extending from the minimum distance to an intermediate distance between the maximum distance and the minimum distance. Then, at each detection cycle a reception signal is detected and a detection profile is obtained, the detection profile is compared in the subrange with the reference function, and a masking signal is generated only if the detection profile assumes at least one value that differs from the reference function in the subrange by more than one predetermined difference.